Figure 1. Vaginal Birth After Cesarean (VBAC) – Analytical Framework
The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-Based Practice Centers (EPCs), sponsors the development of evidence reports and technology assessments to assist public- and private-sector organizations in their efforts to improve the quality of health care in the United States. The reports and assessments provide organizations with comprehensive, science-based information on common, costly medical conditions and new health care technologies. The EPCs systematically review the relevant scientific literature on topics assigned to them by AHRQ and conduct additional analyses when appropriate prior to developing their reports and assessments.
To bring the broadest range of experts into the development of evidence reports and health technology assessments, AHRQ encourages the EPCs to form partnerships and enter into collaborations with other medical and research organizations. The EPCs work with these partner organizations to ensure that the evidence reports and technology assessments they produce will become building blocks for health care quality improvement projects throughout the Nation. The reports undergo peer review prior to their release.
AHRQ expects that the EPC evidence reports and technology assessments will inform individual health plans, providers, and purchasers as well as the health care system as a whole by providing important information to help improve health care quality.
We welcome written comments on this evidence report. They may be sent to: Director, Center for Practice and Technology Assessment, Agency for Healthcare Research and Quality, 6010 Executive Blvd., Suite 300, Rockville, MD 20852.
Carolyn M. Clancy, M.D.
Acting Director
Agency for Healthcare Research and Quality
Robert Graham, M.D.
Director, Center for Practice and Technology Assessment
Agency for Healthcare Research and Quality
The authors of this report are responsible for its content. Statements in the report should not be construed as endorsement by the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services of a particular drug, device, test, treatment, or other clinical service.
The research team would like to express our regard and appreciation for the efforts of Patty Davies, MS, for database searching; Benjamin K.S. Chan, MS, for statistical support; A.J. Mayhew for editing; Susan Wingenfeld, Lynne Schwabe, Nina Mahmud, and James Wallace for program support; Linda Slattery for administrative support; and everyone else who shared support and ideas throughout the development of this report. We would also like to thank Rosaly Correa-de-Araujo, MD, MSc, PhD, of the Agency for Healthcare Research and Quality for her help as our Task Order Officer.
We also thank the representatives from the American College of Obstetricians and Gynecologists and the American Academy of Family Physicians, our technical expert panel, our peer reviewers, and those on the uterine rupture terminology conference call for their invaluable contributions.
Objectives. The literature was systematically reviewed to compare the benefits and harms of a trial of labor (TOL) and an elective repeat cesarean delivery (ERCD), and to examine factors that influence decisionmaking.
Search strategy. Published literature on all vaginal birth after cesarean (VBAC) topics was identified by multiple searches of MEDLINE® (1966 to 2002) and HealthSTAR (1975 to 2002), from reference lists of systematic reviews, and from local and national experts. Online searches were performed on Cochrane systematic reviews and controlled trials registry, Centre for Reviews and Dissemination sites, and EMBASE databases. For topics related to patient preferences and satisfaction, PsycINFO and CINAHL® databases were also searched.
Selection criteria. Studies begun or published before 1980 and studies that focused on patients with specific conditions such as gestational diabetes, human immunodeficiency virus, preeclampsia, and so on were excluded. Studies that exclusively focused on nulliparous women; vertical, lower vertical, “classical” or “classic” cesarean incisions; vaginal breech delivery; preterm delivery; multiple gestation; or low birth weight were also excluded.
Data Collection and Analysis. A technical advisory panel provided input from obstetricians, family physicians, nurse midwives, payers, and patients to ensure that the project addressed clinical questions and issues. An analytic framework was developed and later refined with input from national experts and members of the technical panel. The framework relates the 10 topics reviewed on clinical decision-making for pregnant women with prior cesarean delivery. The strength and suitability of the evidence regarding the risks of major maternal and infant morbidity and mortality associated with TOL and ERCD is the main focus of this report. Studies were rated for quality. We included 180 articles with original data about maternal and infant outcomes relevant to a key question in one or more topic areas.
Main Results. The literature concerning TOL and ERCD is flawed in several ways: imprecise measurement of outcomes (e.g., maternal infection, perinatal death), making it difficult to determine the portion of events directly attributable to maternal choice of delivery route; lack of standards for terminology (e.g., no standard classification for severity of uterine rupture, nor attribution specifically to the disruption of the cesarean scar); and limited attention to comparability between groups (e.g., studies of ERCD where it is unclear whether patients were eligible for TOL). Similarly, important definitional confounding prevents determination of whether signs, such as prolonged fetal bradycardia, have any predictive premonitory value.
There is no direct evidence regarding the benefits and harms of TOL relative to ERCD in women who are similar in every respect except choice of delivery route. Several large cohort studies provide indirect evidence about relative benefits and harms of TOL versus ERCD. Overall, these studies report an increased risk of perinatal death and symptomatic uterine rupture of a cesarean scar with TOL, no increased risk of asymptomatic uterine rupture (dehiscence), maternal death or hysterectomy from either route, and increased risk of infection from ERCD. However, the magnitude of risk is uncertain due to methodologic deficiencies of the studies.
Further studies are needed to test the reliability and usefulness of economic models and predictive tools.
The literature concerning factors that influence patient decisionmaking and satisfaction with childbirth was poor, giving us little insights into patient's priorities.
Conclusions. The deficiencies in the literature about the relative benefits and harms of TOL versus ERCD are striking. Patients, clinicians, insurers, and policymakers do not have the data they need to make truly informed decisions about appropriate delivery choices following one of the most common surgical procedures performed on women. Given the rising prevalence of this condition, and potential for devastating consequences for thousands of women and children each year, obtaining accurate data should be a high research priority.
This report provides a framework for comparing the harms and benefits of delivery options for women with prior cesarean delivery (CD). The information is designed to help consumers, providers, payers, and policymakers in decisionmaking about repeat cesarean or trial of labor (TOL).
In 2000, 22.9 percent of all births in the United States occurred by CD. This rate is the highest total CD rate reported since data collection began in 1989. The vaginal birth after cesarean (VBAC) rate, defined as the proportion of women with a prior CD who delivered vaginally, steadily increased from 1989 to 1996. As allowing TOL became more common, practice variation became a larger concern, e.g., expanding criteria for eligibility and medical induction, and for augmentation of labor. In parallel with this liberalization of criteria and management, highly publicized articles suggested that maternal and fetal risks were perceived to be increasing. Subsequently, the VBAC rate has decreased 27 percent from 1996 to 2000. Currently, a crisis in malpractice rates is decreasing the availability of maternity care providers and raising concerns that patients may have limited options, less access to care, and perhaps be at increased risk for complications.
The strength and suitability of the evidence regarding the risks of major maternal and infant morbidity and mortality associated with TOL or elective repeat cesarean delivery (ERCD) in women with prior low transverse or unknown scar. The scope of the review was to examine events that were specifically related to having had a prior CD. Comparisons purely about vaginal versus cesarean delivery such as incontinence, pelvic support disorders, and respiratory consequences but not specifically about VBAC or repeat cesarean, were not considered, though these topics are important to consider when deciding upon route of delivery. In judging the suitability of evidence, we took the perspective that the first thing a decision-maker would want to know is whether the risk of these complications is higher for a trial of labor, versus an elective cesarean delivery, under optimal conditions of care. That is, the most relevant evidence would compare the outcomes and risks of a properly managed trial of labor to that of a properly conducted elective cesarean delivery. Some components of obstetric care, as well as some aspects of the setting of this care, might increase the risks of TOL or ERCD. For example, it has been hypothesized that the use (or misuse) of drugs for induction and augmentation might increase the risk of uterine rupture in patients who have had a prior cesarean delivery. We examined the strength of evidence that these factors influence these outcomes and adverse effects and to what extent these factors can explain the results of observational studies of VBAC complications.
Two types of key questions were addressed. The first group (Questions 1–7) compares the outcomes of a TOL and an ERCD:
What is the frequency of vaginal delivery in women who undergo a TOL (spontaneous onset, induced, and augmented) after prior low transverse cesarean or unknown scar?
How accurate are risk assessment tools for identifying patients who will have a vaginal delivery after a TOL?
What are the relative harms associated with a TOL (spontaneous onset, induced, and augmented) and repeat cesarean?
What is the incidence of uterine rupture, and are there methods for preventing major morbidity and mortality due to uterine rupture?
What are the health status and health-related quality of life for VBAC and repeat cesarean patients?
Regarding VBAC and repeat cesarean, what factors influence patient satisfaction/dissatisfaction with their childbirth experience?
How are economic outcomes related to VBAC, repeat CD, and their respective complications?
The second group (Questions 8–10) address factors influencing the decision to have a TOL:
What individual factors influence route of delivery?
What factors influence a patient's decisionmaking regarding VBAC or ERCD?
How do legislation, policy, guidelines, provider characteristics, insurance type, and access to care affect health outcomes for VBAC candidates?
Relevant studies were identified from multiple searches of MEDLINE® (1966 to 2002) and HealthSTAR (1975 to 2002), from the reference lists of systematic reviews and from local and national experts. The online Cochrane systematic reviews and controlled trials registries, DARE, National Centre for Reviews and Dissemination, and EMBASE databases were searched for relevant literature on specific topics as well. For topics related to patient preferences and satisfaction, PsycINFO and CINAHL® databases were searched. Databases were searched twice during the course of the project, with the final search in March 2002. For all VBAC topics combined, 14,449 citations were retrieved, including 4,867 about spontaneous labor and uterine rupture, 2,528 about ERCD, 2,416 about induction of labor, 2,945 citations about predictors, 1,257 about patient satisfaction, preference and health status, and 436 about cost and access.
All searches were limited to English-language articles published since 1980 (the date of the NIH Consensus Conference on VBAC) in developed countries. The report focused on studies that identified a group of patients with prior cesarean. For patient preferences and satisfaction, studies of the general birthing population, were considered if there were no studies that identified patients with prior cesarean. Studies were excluded if they focused on patients with particular conditions such as gestational diabetes, HIV, preeclampsia, and so on. Exclusions were also made for studies that focused primarily on the following: nulliparous women, vertical, lower vertical, “classical” or “classic” cesarean, vaginal breech delivery, preterm delivery, multiple gestation, or low birth weight.
Two investigators reviewed a random set of titles and abstracts for each topic to select articles for full-text review. When an appropriate level of reliability was reached for inclusion and exclusion of studies, the primary investigator reviewed the remaining titles and abstracts on the topic. Investigators read the full-text version of the retrieved papers and reapplied the initial eligibility criteria. Data from 224 studies were abstracted and included in the evidence tables described in the results section of this report.
Included study designs were determined by topic area. Study designs of included articles consisted of randomized controlled trials, cohort studies, case-control studies, cross-sectional studies, large case series (more than 10 subjects), and economic or decision models. All data were abstracted by the lead investigator for the topic. If the lead investigator encountered difficulty in finding or interpreting information in the published report, a second investigator reviewed the article and a consensus was reached.
To assess the internal validity of individual studies, we applied a set of design-specific criteria developed by the current U.S. Preventive Services Task Force and additional criteria developed by the NHS Centre for Reviews and Dissemination, based at the University of York in England. In general, studies were rated good if they met all criteria, fair if they addressed some but not all criteria, and poor if they had a “fatal flaw.” Investigators were asked to use the study quality ratings as previously described to determine for their topic which quality components were most important in assessing internal validity. This process allowed for some individual topic fit for fatal flaws, etc. A second investigator independently rated all included articles, and disagreements were resolved by consensus.
Where appropriate, meta-analysis was performed using WinBugs® or StatsDirect® software. To reduce potential bias, only studies of fair or good quality were included in the analyses.
Rates of vaginal delivery when attempting TOL ranged from 60 to 82 percent. The largest population-based study reported a rate of 60.4 percent. The combined vaginal delivery rate for all prospective cohort studies, largely conducted in tertiary care centers and University settings, was 75.9 percent.
There are limited data on the effect of medical induction and augmentation of labor.
There was a 10-percent reduction in the likelihood of vaginal delivery when oxytocin was used for ether induction or augmentation. There was a similar trend in reduced likelihood of vaginal delivery with prostaglandins.
Two validated scoring systems categorized women into groups with likelihoods of vaginal delivery ranging from roughly 45 to 95 percent.
One tool was able to stratify more of the population (up to 50 percent of women choosing TOL) into high and low probability subgroups, with a relatively low false-positive rate.
By using a prospective cohort design and the largest study population, the best scoring system created a 10-point score based on the presence or absence of five variables commonly available for most patient admissions.
An RCT clearly demonstrated the inability of X-ray pelvimetry (XRP) to predict route of delivery reliably.
Imaging studies that combined the measurements of the pelvis and fetus showed promising results, but were limited by their lack of control for confounding and biases.
In the absence of RCTs of TOL versus repeat cesarean, evidence that is most generalizable comes from large country, State, or regional population-based studies (referred to as population-based studies) followed by large multicenter cohort studies, large single-institution or single-practice cohort studies, then smaller cohort studies, respectively.
There is no direct evidence regarding the benefits and harms of TOL relative to ERCD in women who are similar in every respect except choice of delivery route.
Several fair and good quality studies provide indirect evidence about relative benefits and harms of each route.
Maternal death rates did not differ between TOL and ERCD.
The best evidence suggests that hysterectomy rates do not differ between TOL and ERCD.
No studies examined specifically the risks of incontinence or pelvic support disorders in women with prior cesarean.
Rates of infection were increased in ERCD versus TOL overall. Studies that performed subgroup analyses for TOL with and without vaginal delivery consistently found increased rates of infection for women who attempted TOL but ultimately had a cesarean delivery.
There is conflicting evidence regarding whether induction of labor affects infection rates.
There is insufficient evidence regarding the effect of selected route of delivery and Apgar score or respiratory morbidity.
No study measured infant death directly attributable to a mother's choice of TOL or repeat CD.
There is uncertainty about the magnitude of risk of perinatal death due to TOL. Results from two large studies differ in the magnitude of increased risk from TOL versus ERCD (90/1,000 TOL versus 50/1,000 ERCD compared with 12.9/1,000 TOL versus 1.1/1,000 ERCD). Neither study provides direct evidence of risk.
The use of terms among studies is inconsistent.
Definitions among studies for similar terms are ambiguous.
There is no difference in asymptomatic uterine rupture rates in TOL versus ERCD.
Symptomatic uterine rupture is significantly more common in TOL versus ERCD, with an increased risk of 2.7/1000.
Based on the frequency and severity of symptomatic uterine rupture, the risk of perinatal death due to a rupture of a uterine scar is 1.5/10,000 and the risk of maternal hysterectomy is 4.8/10,000. These rates of serious complications such as perinatal death are probably more precise than overall risks from studies measuring death directly.
The definition of uterine rupture as an outcome is confounded by a definition that includes the potential predictor of fetal heart rate (FHR) tracing abnormality.
Measurement of frequency of occurrence, predictors for what population is at greatest risk, and predictors for poor outcomes are not possible, because of the lack of standard case definition.
There were no studies of health status or health-related quality of life for VBAC or repeat CD patients.
Studies of patient satisfaction largely consisted of the patient's own provider obtaining information about patient satisfaction, introducing the possibility of measurement bias.
Only two cross-sectional studies used methods other than the patient's own provider to obtain satisfaction information.
No study measured satisfaction for the three types of delivery outcomes that could be experienced by women with prior CDs (VBAC, TOL followed by CD, or ERCD).
For a TOL success probability of 76 percent or greater, TOL is more cost-effective and provides higher quality of life.
Further evaluation is needed of the sensitivity of the probability cut point of 76 percent to other potential predictor variables.
The vast majority of studies looking at individual factors that influence the route of delivery were of poor quality due to the lack of control for confounding factors.
The factors that were significantly associated with an increased likelihood of vaginal delivery (i.e., successful TOL) were maternal age less than 40 years, prior vaginal delivery (particularly vaginal delivery after cesarean), a nonrecurrent indication for the prior CD, and favorable cervical factors.
The factors that were significantly associated with a decreased likelihood of vaginal delivery (i.e., failed TOL) were an increasing number of prior CD, gestational age greater than 40 weeks, birthweight greater than 4000 g, and augmentation of labor.
Patient preferences for birth choice are unclear because of the heterogeneity of the 11 included studies.
Several factors appear related to choice for TOL (White race; prior vaginal delivery; lower levels of anxiety during the pregnancy).
Lack of medical information along with cultural ideologies might account for minority women being less likely to attempt a TOL when compared with White women.
A woman's choice for delivery was often based on social motives (e.g., easier recovery, so she can care for baby and children at home).
Only four of 11 studies cited safety for mother or baby as important reasons for delivery choice.
It remains unclear whether VBAC education increases the proportion of women who choose TOL.
Studies of legislation, policy, guidelines, hospital characteristics, provider characteristics, insurance type, or access to care focus exclusively on VBAC rates rather than safety.
No study provides direct evidence for the impact of malpractice issues on VBAC or ERCD.
One study reported that VBAC rates increased when legislation was enacted that standardized VBAC guidelines had to be provided to obstetric providers.
The best evidence suggests that use of opinion leaders provides a greater likelihood of changing practice compared with audit and feedback.
Studies of provider characteristics failed to control for important variables such as patient selection bias.
VBAC rates were higher in teaching hospitals compared to private, community, regional, or non-teaching hospitals.
Three studies conflicted over the effect of hospitals containing a neonatal intensive care unit (NICU).
There was conflicting evidence regarding whether insurance status predicts VBAC.
The following summarizes the type of study design, the quality of the evidence from studies, and the suitability of the study design to answer the particular question for each key question.
| Key Question | Study Type* | Quality of Evidence | Suitability of Study Design† |
|---|---|---|---|
| Question 1 | |||
| What is the frequency of vaginal delivery in women who undergo a TOL (spontaneous onset, induced, and augmented) after prior low transverse cesarean or unknown scar? | II-2 | Fair-Good: Several large prospective and retrospective studies; mostly consistent findings. | Greatest |
| Question 2 | |||
| How accurate are risk assessment tools for identifying patients who will have a vaginal delivery after a TOL? | |||
| Predictive tools | II-2 | Fair-Good: Large fair and good quality cohort studies suggest tools can provide additional information to predict likelihood of vaginal delivery. | Greatest |
| Imaging modalities | I | Good: Good quality RCT demonstrated that imaging was ineffective to predict vaginal birth. | Greatest |
| Question 3 | |||
| What are the relative harms associated with a TOL (spontaneous onset, induced and augmented) and repeat cesarean? | II-2 | Fair-Poor: Several large cohort studies were inconsistent in their definitions for important health outcomes. | Moderate |
| Maternal Death | Fair: Studies consistently found no increased risk of maternal death from TOL versus ERCD. | Least | |
| Hysterectomy | Fair-Poor: Many studies failed to report indication for hysterectomy. | Moderate | |
| Transfusion | Fair: Two studies with consistent findings of slightly increased risk for transfusion in TOL, although not significant in one. | Moderate | |
| Infection | Poor: Definitions were inconsistent among studies. | Moderate | |
| Incontinence/Pelvic Floor | No studies. | Moderate | |
| Infant Death | Poor: Most studies found increased risk of perinatal death for TOL versus ERCD, but the magnitude of the increase varied greatly. | Least | |
| Neurologic impairment | Poor: Few studies of poor quality. | Least | |
| Respiratory impairment | No studies. | Moderate | |
| Question 4 | |||
| What is the incidence of uterine rupture of a cesarean scar, and are there methods for preventing poor clinical outcomes? | |||
| Incidence | II-2 | Fair-Poor: Several large cohort studies which were inconsistent in terminology; many with consistent findings of increased risk of symptomatic uterine rupture in TOL versus ERCD. | Moderate |
| Methods for preventing poor outcomes | II-3 | Poor: Few studies, variation in case definition. Fetal bradycardia was frequently associated with uterine rupture; however, inclusion of fetal tracing findings in the definition of uterine rupture makes it difficult to assess the true value. | Least |
| Question 5 | |||
| What are the health status and health-related quality of life for VBAC and repeat cesarean patients? | None | No studies of women with prior CD. | NA |
| Question 6 | |||
| Regarding VBAC and repeat cesarean, what factors influence patient satisfaction/dissatisfaction with their childbirth experience? | III | Fair: Two cross-sectional studies with varied findings. | Least |
| Question 7 | |||
| How are economic outcomes related to VBAC, repeat CD, and their respective complications? | Econ | Fair-Good: One good economic model suggests VBAC is cost-effective and provides higher quality of life when chance of vaginal delivery is 76 percent or greater. | Greatest |
| Question 8 | |||
| What individual factors influence route of delivery? | II-2 | Fair-Poor: Several retrospective cohort studies conducted; all vary in items considered, each with limited adjustment for confounders. | Moderate |
| Question 9 | |||
| What factors influence a patient's decision making regarding VBAC or ERCD? | I, II, III | Fair: One good RCT and eight fair quality cohort or cross-sectional studies found women who preferred TOL were more likely to be White, valued the process of labor, and valued social motives such as ease of recovery. | Moderate |
| Question 10 | |||
| How do legislation, policy, guidelines, provider characteristics, insurance type, and access to care affect health outcomes for VBAC candidates? | |||
| Legislation | II-3 | Poor: Few studies that examined only the impact on VBAC rates not safety. None examined the impact of the crisis in malpractice rates on access or safety. | Moderate |
| Guidelines | I, II | Fair-Good: Several studies with consistent findings that provision of guidelines especially with recommendations of opinion leaders increased VBAC rates; no studies on safety. | Moderate |
| Provider Characteristics | II | Poor: Several studies, none of which adjusted for differences in baseline risk or potential confounders. | Moderate |
| Hospital | II | Fair: Consistent findings that teaching hospitals had higher VBAC rates; no comparisons for safety. | Moderate |
| Insurance | II | Fair: Several studies with conflicting findings. | Moderate |
Study design categories—I: randomized, controlled trials; II-1: controlled trials without randomization; II-2: cohort or case-control; II-3: multiple time series; III: opinions, descriptive epidemiology. U.S. Preventive Services Task Force (1996).
Suitability of study design categories—Greatest: For comparison studies: Concurrent comparison groups and prospective measurement of exposure and outcome; For rates: population-based or multicenter prospective cohort studies. Moderate: All retrospective designs or multiple pre or post measurements but no concurrent comparison group; Least: Single pre and post measurements and no concurrent comparison group or exposure and outcome measured in a single group at the same point in time. Community Preventive Services Task Force (2000).
Data are insufficient to allow conclusions about the most appropriate delivery choice for a given patient.
Studies suffered from inconsistent and imprecise definitions for important outcomes.
Studies frequently failed to ensure comparability between TOL and ERCD groups.
No study or collection of studies, provide data about the impact of practice variation, provider characteristics, legal considerations such as the effect of rising malpractice rates on the safety of TOL or ERCD.
The degree to which the association between fetal bradycardia and poor perinatal outcome from uterine rupture rather than confounding by factors detection bias is unclear.
The degree to which the association between TOL and perinatal death reflects causation rather than confounding by factors such as misclassification of cases, lethal conditions of the fetus, or detection bias is unclear.
Future research should focus on conducting methodologically rigorous studies to provide direct evidence regarding the relative benefits and harms of TOL and ERCD. If randomized trials are not done, good-quality studies of TOL versus ERCD must pay attention to the following:
Population. Studies should be conducted in populations of women who are similar in every respect except choice of delivery route (comparability of groups).
Specificity of intervention. Studies should pay close attention to and account for the importance of co-interventions such as use of oxytocin and other medical agents for augmentation or induction of labor.
Precise and standard outcome measures. Variations in reporting of important clinical outcomes were striking. Studies should consider the following factors in developing outcome measures:
Etiology. Outcomes such as hysterectomy, infection, maternal mortality, and perinatal mortality must pay specific attention to explicitly identifying the etiology. Lack of precision in this regard allows for both under and overreporting of cases due to misclassification. Examples include whether hysterectomy was performed due to maternal hemorrhage secondary to clinically significant uterine rupture versus hemorrhage due to abruption, uterine rupture through the uterine fundus in a woman with a low transverse incision either due to trauma or other non-incisional causes, and perinatal death due to lethal anomaly versus intolerance or management of labor.
Standard terminology. In order to accurately measure outcomes, there must be a consistent terminology. Lack of this prevents accurate and meaningful comparisons of risks for each delivery choice. Outcomes such as infection, hemorrhage, and uterine rupture were not consistently defined.
Separating prevention/prediction strategies from outcomes. As long as potentially important predictors of events such as prolonged fetal bradycardia as a predictor for clinically significant uterine rupture are included in the definition of uterine rupture, their true value as a predictor rather than a confounder will remain unknown.
Additional studies are needed to measure the accuracy and yields of existing predictive tools.
Future studies of predictive tools should include measurements of the consequences of false-positive screens and false-negative screens to determine whether there are clinically important harms that result from screening.
The costs (rather than charges) of labor and delivery and of the surgical processes are poorly understood. Detailed time-in-motion studies would help to estimate these costs.
This report provides a framework for comparing the harms and benefits of delivery options for women with prior cesarean delivery (CD). The information is designed to help consumers, providers, payers, and policymakers in decision-making about repeat cesarean or trial of labor (TOL).
An evidence report focuses attention on the strengths and limits of evidence from published studies about the effectiveness and/or harms of a clinical intervention. The development of an evidence report begins with a careful formulation of the problem. In this phase, a preliminary review of the literature and input from patients, clinicians, experts, and payers ensures that the scope of the project addresses clinical questions and issues that arise in everyday practice. An analytic framework is developed and used to identify the patient populations, interventions, health outcomes, and harms. Studies that measure health outcomes (such as maternal and infant mortality) are emphasized over studies of intermediate outcomes (such as nonreassuring fetal tracing). Studies providing evidence of a direct association between an intervention (elective repeat cesarean delivery [ERCD]) and health outcome (such as infant death) are said to provide direct evidence and are given greater weight than studies that provide indirect evidence.
An evidence report also emphasizes the quality of the evidence, giving weight to studies that are appropriately designed to answer a question and meet high methodologic standards that reduce the likelihood of biased results. To compare two different treatments or management strategies, the results of well-done, randomized controlled trials (RCTs) are regarded as better evidence than results of cohort, case-control, or cross-sectional studies. These designs, in turn, are considered better evidence than uncontrolled trials or case series. On the other hand, to assess a diagnostic test or prediction tool, certain observational study designs can provide the highest-quality evidence.
An evidence report pays particular attention to the generalizability of efficacy studies performed in controlled or academic settings. Observational studies that reflect actual clinical effectiveness in unselected patients and community settings can provide information that is more generally applicable than studies of highly selected subjects. In the context of developing clinical guidelines, evidence reports are useful because they define the limits of the evidence and clarify when the assertions about the value of the intervention are based on strong evidence from clinical studies. The quality of the evidence on effectiveness is a key component, but not the only component, in decisionmaking about clinical policies. Additional criteria include acceptability to physicians or patients, the potential for unrecognized harms, and cost-effectiveness.
Discussions about vaginal delivery after prior CD first appeared in the literature in 1916. Cragin, who is attributed with coining the phrase “once a cesarean, always a cesarean,” described cases of women surviving vaginal birth after cesarean (VBAC).1
With the development of safer surgical techniques and ancillary services (e.g., blood typing and transfusion, antibiotic therapy), the risk of CD decreased. By 1980, 16.5 percent of deliveries were conducted by cesarean. This was a marked increase from the rate of 5.5 percent in 1970.2 As cesarean rates increased, national interest arose in reducing the rate of repeat cesarean, the leading indication for CD.3 The National Institute of Child Health and Human Development (NICHD) convened a Consensus Development Conference in 1980 to assess why cesarean rates were rising and to determine whether CD resulted in improved fetal outcomes. It was determined that TOL after prior low transverse cesarean posed low risk to fetus and mother, but more data with larger numbers were needed. After 1980, VBAC rates rose. A series of highly publicized articles suggested that VBAC was associated with higher risks of uterine rupture4 and maternal5 and perinatal morbidity.6 Currently, a crisis in malpractice rates is decreasing the availability of maternity care providers and potentially limiting options for patients.
In 2000, 22.9 percent of all births in the United States occurred by CD.2 This rate is the highest total CD rate reported since data collection began in 1989.
| Year | Total1 | Primary2 | VBAC rate3 |
|---|---|---|---|
| 2000 | 22.9 | 16.0 | 20.7 |
| 1999 | 22.0 | 15.5 | 23.4 |
| 1998 | 21.2 | 14.9 | 26.3 |
| 1997 | 20.8 | 14.6 | 27.4 |
| 1996 | 20.7 | 14.6 | 28.3 |
| 1995 | 20.8 | 14.7 | 27.5 |
| 1994 | 21.2 | 14.9 | 26.3 |
| 1993 | 21.8 | 15.3 | 24.3 |
| 1992 | 22.3 | 15.6 | 22.6 |
| 1991 | 22.6 | 15.9 | 21.3 |
| 19904 | 22.7 | 16.0 | 19.9 |
| 19895 | 22.8 | 16.1 | 18.9 |
Adapted from Menacker, 2001.7 Trends in Cesarean Birth and Vaginal Birth After Previous Cesarean, 1991-1999. National Vital Statistics Report, V49, #13, p2.
Percent of all live births by CD.
Number of primary cesarean per 100 live births to women who have not had a prior CD.
Number of VBAC deliveries per 100 live births to women with a prior CD.
Excludes data for Oklahoma, which did not report method of delivery on the birth certificate. The reporting area comprised 99 percent of births in 1999.
Excludes data for Louisiana, Maryland, Nebraska, Nevada, and Oklahoma, which did not report method of delivery on the birth certificate. The reporting area comprised 94 percent of births in 1989.
As allowing TOL became more common, practice variation became a larger concern, e.g., expanding criteria for eligibility and medical induction, and for augmentation of labor. In parallel with this liberalization of criteria and management, maternal and fetal risks were perceived to be increasing. Patterns of care provision began to be explored as potential explanations for perceptions of increasing risks.
For most women who have had a prior CD, obstetric care is provided by nurse midwives, family practitioners or obstetrician-gynecologists. In 2000, physicians attended 91.6 percent of all deliveries and midwives attended 7.8 percent.2 Ninety-nine percent of all births were delivered in a hospital.2 As of 1994, 13 percent of all deliveries attended by a physician were performed by family practice and general practice physicians, and 85 percent were performed by obstetrician-gynecologists.9 Among obstetrician-gynecologists, 18 percent of all deliveries were by cesarean.10 According to 2001 survey data from the American Academy of Family Physicians, 29.8 percent of family physicians perform obstetrics.11 Of family physicians who do perform cesareans, 4.7 percent perform them within a hospital practice and 2.5 percent perform them only with consultation. Sixty-seven percent report that they would not desire to perform them; however, 3.9 percent report that they do not perform cesareans because the liability is prohibitive or because of fear of a liability suit.11 Though 22.5 percent of both urban and rural family physicians report performing routine deliveries, differences by geographic location are evident. Of rural family physicians, 5.7 percent report performing cesareans, and 18.6 percent report caring for patients undergoing VBAC; the comparable figures for urban family physicians are 4.9 percent and 15.5 percent, respectively.
A technical advisory panel (Appendix A) was assembled to provide input from patients, clinicians, and payers to ensure that the scope of the project addressed clinical questions and issues that arise in everyday practice. The panel included obstetricians, family physicians, nurse midwives, payers, and patients. This panel and our national experts and partners provided ongoing assistance throughout the project.
The analytic framework (Figure 1
All of the benefits and risks listed in the figure may be affected by the method of delivery. However, only some of the risks, such as uterine rupture and, possibly, infant death and damage, are thought to be influenced by having had a prior cesarean section. In defining the scope for this review, we emphasized the benefits and risks that have been reported in studies that included women who have had a previous cesarean delivery. Comparisons of outcomes purely between vaginal and cesarean delivery, but not specifically about VBAC or repeat cesarean delivery, such as breastfeeding, incontinence12, 13 pelvic support disorders, or infant respiratory sequelae14 were not considered. Though these are outside the scope of this report, they are certainly important to a woman in deciding between attempted vaginal or cesarean delivery.
The strength and suitability of the evidence regarding the risks of major maternal and infant morbidity and mortality associated with VBAC is the main focus of this report. In judging the suitability of evidence, we took the perspective that the first thing a decisionmaker would want to know is whether the risk of these complications is higher for a trial of labor versus an elective cesarean delivery, under optimal conditions of care. That is, the most relevant evidence would compare the outcomes and risks of a properly managed trial of labor to that of a properly conducted elective cesarean delivery. From this perspective, a study comparing the results of VBAC and ERCD that provided little or no information about the quality or content of obstetric care, or that occurred so long ago that the quality of care would be considered poor by today's standards, has little value for patients who are cared for by clinicians who are capable of providing high-quality, up-to-date care.
We addressed two types of key questions. The first group (Questions 1–7) compares the outcomes of a TOL and an ERCD:
Question 1. What is the frequency of vaginal delivery in women who undergo a TOL (spontaneous onset, induced, and augmented) after prior low transverse cesarean or unknown scar?
Question 2. How accurate are risk assessment tools for identifying patients who will have a vaginal delivery after a TOL?
Question 3. What are the relative harms associated with a TOL (spontaneous onset, induced and augmented) and repeat cesarean?
Question 4. What is the incidence of uterine rupture, and are there methods for preventing major maternal and infant morbidity or mortality due to uterine rupture?
Question 5. What are the health status and health-related quality of life for VBAC and repeat cesarean patients?
Question 6. Regarding VBAC and repeat cesarean, what factors influence patient satisfaction/dissatisfaction with their childbirth experience?
Question 7. How are economic outcomes related to VBAC, repeat CD, and their respective complications?
The second group (Questions 8–10) concern factors influencing the decision to have a TOL:
Question 8. What individual factors influence route of delivery?
Question 9. What factors influence a patient's decisionmaking regarding VBAC or ERCD?
Question 10. How do legislation, policy, guidelines, provider characteristics, insurance type, and access to care affect health outcomes for VBAC candidates?
Relevant studies were identified from multiple searches of MEDLINE (1966 to 2002) and HealthSTAR (1975 to 2002), from the reference lists of systematic reviews, and from local and national experts (Appendix A). For relevant literature on specific topics, we also searched the online Cochrane systematic reviews and controlled trials registries, DARE, National Centre for Reviews and Dissemination, and EMBASE databases (Appendix B, search strategies and characteristics).
Databases were searched twice during the course of the project, with the final search in March 2002. Retrieved abstracts were entered into an electronic database (EndNote®). Figure 2
A lead investigator was assigned for each topic. Two investigators reviewed a random set of titles and abstracts for each topic to select articles for full-text review. When an appropriate level of reliability was reached for inclusion and exclusion of studies, the primary investigator reviewed the rest of the titles and abstracts on the topic. A research assistant tracked the inclusion status and names of reviewers for each abstract reviewed. We retrieved the full text articles of citations that had original data about maternal and infant outcomes relevant to a key question in one or more topic areas.
Studies begun or published before the 1980 National Institute of Health, Consensus Conference on Vaginal Birth after Cesarean, were excluded. The report focused on studies that identified a group of patients with prior cesarean. Studies of the general birthing population were considered if there were no studies that identified patients with prior cesarean. Studies were excluded if they focused on patients with particular conditions such as gestational diabetes, human immunodeficiency virus (HIV), preeclampsia, etc.
Exclusions at the title and abstract level were also made for studies that focused on the following: nulliparous patients, vertical, lower vertical, “classical” or “classic” cesarean incision, an inability to differentiate outcomes based upon scar type, vaginal breech delivery, preterm delivery, multiple gestation, or low birth weight. Animal studies, cadaver studies, and studies available exclusively in abstract form were also excluded.
Undeveloped or developing countries were excluded (Appendix C). If the authors described their country as “developing” in either the abstract or the article, it was excluded. Investigators noted this in either the text or evidence tables. Case reports with less than 10 subjects with prior CD were excluded. We also excluded editorials, letters, and nonEnglish language papers.
Case reports, case series, and general population studies (large: n = 100 or greater; small: n = less than 100), were identified but as a rule were not included in the review. Details on suspect or missing data are listed in Appendix D.
When two reviewers disagreed about eligibility, the lead investigator for the topic reexamined the abstract and determined whether the full text of the article should be retrieved. Investigators were encouraged to flag abstracts they believed could be relevant for other topics. Support staff maintained a database to refer these citations to the appropriate investigator if the citations were not already present in the topic-specific abstract database.
After this review, the following were retrieved for full text review: 157 articles about predictors; 528 about TOL and/or uterine rupture; 132 about ERCD; 152 about induction of labor; 81 about patient satisfaction, preference, and health status; and 281 about cost and access. An additional 320 studies were retrieved after reviewing reference lists of studies and by suggestion of the expert panel or leading researchers in the field. The full texts of these 1,651 studies were retrieved from the library or ordered through inter-library loan. During the abstract review process, 10 VBAC-related systematic reviews were identified and retrieved for review.
Investigators read the full-text version of the retrieved papers and re-applied the initial eligibility criteria. For all topics, we excluded articles if they did not provide sufficient information to determine the methods for selecting subjects and for analyzing data. For some topics, additional criteria were applied to select studies that were systematically reviewed and included in evidence tables as follows.
Data from 180 studies were abstracted and included in the evidence tables described in the results section of this report. Appendix E has details on studies excluded at the paper review level for reasons other than described in the methods section.
The following information about the patient population, study design, study outcomes, and study quality was extracted from full-text, published studies of VBAC and TOL, induction of labor, ERCD, or uterine rupture, and was used to construct evidence tables: identifying information (study name, years of observation); setting (population-based, referral clinic-based, other); study design (randomized trial, prospective, etc.); interventions (induction, augmentation medications); outcomes studied (infant, maternal, cost, etc.); length of followup; statistical methods for handling confounders (statistical adjustment, stratification, none) and attrition; numbers of subjects recruited, included, and completing study; and characteristics of the sample (demographic variables, number of previous births, other risk factors). For economic evaluations, we also extracted the type of economic evaluation, the primary outcomes reported, data sources, cost unit, discount rate, and what characteristics were varied in the sensitivity analyses and results. Abbreviations and acronyms for study material can be found at the end of the report.
All data were abstracted by the lead investigator for the topic. If the lead investigator encountered difficulty in finding or interpreting information in the published report, a second investigator reviewed the article and a consensus was reached.
To assess the internal validity of individual studies, we applied a set of criteria developed by the current United States Preventive Services Task Force and additional criteria developed by the NHS Centre for Reviews and Dissemination, based at the University of York in England. Appendix G shows a detailed description of the quality ratings and tables with quality-rated studies. A brief description of ratings with criteria by study design follows.
RCTs or cohort studies. A study was rated good-quality if it met all the following criteria: comparable groups were assembled initially and maintained throughout the study (followup at least 80 percent); reliable and valid measurement instruments were used and applied equally to the groups; interventions were spelled out clearly; important outcomes were considered; appropriate attention was given to confounders in analysis; and intention-to-treat analysis was used in RCTs.
A study received a fair rating if any of the following problems were seen: generally comparable groups were assembled initially but some question remained whether some (although not major) differences occurred in followup; measurement instruments were acceptable (although not the best) and generally applied equally; some, but not all, important outcomes were considered; some, but not all, potential confounders were accounted for; and intention-to-treat analysis was used in RCTs.
Studies were given a poor rating if any of the following fatal flaws existed: groups assembled initially were not close to being comparable or were not maintained throughout the study; unreliable or invalid measurement instruments were used or instruments were not applied equally among groups (including not masking outcome assessment); key confounders were given little or no attention; and intention-to-treat analysis was lacking in RCTs.
Case-control studies. A study which met the following criteria was rated good-quality: appropriate ascertainment of cases and nonbiased selection of case and control participants; exclusion criteria applied equally to cases and controls; accurate diagnostic procedures and measurements applied equally to cases and controls; and appropriate attention to confounding variables.
Studies were rated fair if they were recent, relevant, without major apparent selection or diagnostic work-up bias, or accounted for some but not all important confounding variables.
A poor rating was given to a study in this category if it had major selection or diagnostic work-up biases, or inattention to confounding variables.
Economic or cost model studies. For the economic evaluations, Udvarhelyi's16 ratings were given for six criteria: perspective, benefits, cost data, discounting, sensitivity, and incremental cost-effectiveness ratio (C/E). We assigned to each criterion ratings of good (fulfilled criterion), fair (addressed criterion but not completely or with minor flaw), poor (failed to either address criterion or had a fatal flaw relative to criterion), or not applicable (criterion was not relevant in the context of the evaluation).
Investigators were asked to use the study quality ratings as previously described to determine for their topic which quality components were most important in assessing internal validity. This process allowed for some individual topic fit for fatal flaws, etc.
Spontaneous labor and repeat cesarean. To identify which studies to include, we applied a “best evidence” approach.17 For TOL (SL) and ERCD, we included large population-based and prospective cohort studies. Cohort studies were included because RCTs of delivery method have not been done.
Predictive tools. For this topic, we decided that three of the eight criteria for cohort studies were the most important in determining the quality of each study: (1) comparable groups, (2) clear definition of groups and sufficient description of the distribution of prognostic factors, and (3) consideration of and adjustment for important confounders. Quality was rated as good if all three criteria were met, fair if the groups were comparable and there was adjustment for confounders, and poor if the groups were not comparable or there was no adjustment for confounders.
In addition to the above-mentioned criteria, the evaluation of these diagnostic tests included several of the factors presented by Reid18 and Sox,19 which were: (1) using a prospective study design, (2) avoiding workup or verification bias (i.e., applying the test to all of those eligible for a TOL), and (3) specifying test reproducibility.
Patient satisfaction and health status. Investigators put particular importance on whether the measures for patient health status and psychosocial outcomes were clearly described, including any validation or reliability testing of new health status tools. Specifically, for patient preferences and satisfaction, we put emphasis on methods used to assess patient preferences. Studies that used a method that was independent from the patient's own provider were rated higher than those where the provider assessed this information.
Cost or economic analysis. Specifically for this topic, a poor rating was given for lack of description of the perspective of the economic evaluation, lack of description of the benefits, inclusion of charge data rather than cost data, lack of inclusion of all relevant adverse events, lack of inclusion of discounting (for studies with a time horizon greater than 1 year), lack of sensitivity analyses, and lack of incremental comparisons of alternatives (use of an incremental C/E to compare a more costly alternative to a less costly one).
Access/resources. The studies evaluated were all either databases or cohort studies. The former were typically large national databases and were evaluated using the same criteria as for cohort studies. The main quality criteria used were whether the groups evaluated were comparable at baseline and were controlled for potential confounding variables (including risk adjustment if the groups were not comparable at baseline).
Where appropriate, meta-analysis was performed using WinBugs® or StatsDirect® software. To reduce potential bias, only studies of fair or good quality were included in analyses (Appendix G). StatsDirect® was used for comparative studies (e.g., TOL versus ERCD) and WinBugs® was used for noncomparative data (e.g., data for vaginal delivery rates in TOL).
Model estimation using WinBugs® was done using a Bayesian data analytic framework. WinBugs® uses a method of Markov chain Monte Carlo called Gibbs sampling to simulate posterior probability distributions. Noninformative prior probability distributions were used. Absolute risk differences were calculated for each study, and pooled using both random and fixed effects models. Only results from the random effects models are presented, unless these two methods produced significantly divergent results. Statistical heterogeneity was examined. Point estimates using the mean and 95 percent confidence intervals were calculated from 10,000 draws from five Markov chains.
Meta-analysis using StatsDirect® used DerSimonian and Laird random effects methods. The Q statistic tests whether it is reasonable to assume that the treatment effects in the studies to be combined are estimating a single underlying effect size. When the test is significant (e.g., p < 0.05) there is significant heterogeneity between the studies' effect sizes. This indicates that the variation seen is greater than that expected from random sampling error. The Q statistic, forest plots and any statistical pooling were done using the StatsDirect® software package (CamCode, England). Where statistically significant heterogeneity was found, pooling was not undertaken.
Data extraction and data entry were performed using Microsoft Excel 2000®. Because of the nature of this topic and the need for confounding consideration, further analysis involving the calculation of summary estimates using random effects modeling was not considered. Adjusted odds ratios (ORs) for the likelihood of VBAC from each study formed the basis for evaluation. In the situation where the study provided adjusted OR for the likelihood of a failed TOL, the inverse ratio was taken, to approximate the OR for the likelihood of VBAC.
What is the frequency of vaginal delivery in women who undergo a TOL (spontaneous onset, induced, and augmented) after prior low transverse cesarean or unknown scar?
In the population-based study, which was performed in Nova Scotia, 3,249 (52.9 percent) of 6,317 women with one prior nonvertical CD chose a TOL, and 1,962 of them (60.4 percent) delivered vaginally.5 Women attending tertiary care hospitals were at least twice as likely to choose a TOL and more likely to deliver vaginally than women attending regional or community hospitals. The authors did not distinguish vaginal delivery rates for women requiring medical augmentation or induction versus women who did not require medical assistance in labor.
In the prospective cohort studies, largely conducted in university and tertiary care settings, vaginal delivery rates for all women attempting a TOL ranged from 62–82 percent, with a pooled rate of 75.9 (95 percent CI, 69.9 to 81.5).
*The vertical line, at “0”, indicates no effect. The study mean is indicated by a vertical line surrounded by a diamond. The size of the diamond indicates sample size in relation to the other studies on the plot. The rectangle represents the 95 percent CIs around the study mean. If the rectangle is entirely to the left of the line the difference is statistically significant and oxytocin is associated with a decrease in achieving vaginal delivery compared to spontaneous onset of labor.
Two observational studies reported rates for induction and augmentation separately.25, 30 In one of these studies the vaginal delivery rate of patients requiring oxytocin induction was lower than that of patients requiring only augmentation (risk difference 1.4 percent),25 while in the other study the rate was slightly higher (risk difference 3 percent).30 Neither finding was statistically significant (Figure 4
In comparing prostaglandins (any type) with spontaneous labor (Figure 5
Although the results of the observational studies are generally consistent, these studies are inherently limited by confounding. Even in studies that controlled statistically for several potential confounders, the risk of requiring CD might be increased by the indications for medication for induction and augmentation, rather than the medication itself.
Two RCTs32, 35 also provided information regarding vaginal delivery rates for medical augmentation or induction of labor. Neither RCT compared medicated to spontaneous nonmedicated labor because medical induction and augmentation of labor were allowed in both intervention and controls. One trial compared expectant management with administration of prostaglandin E2 (PGE2) gel for cervical ripening at weekly intervals from 39 to 41 weeks' gestation, for the same time period.32 Oxytocin was used in both groups for augmentation or induction as needed. This study found a VBAC delivery rate of 49 percent in both intervention and expectant management. The second RCT compared mifepristone versus placebo for 2 days followed 2 days later by induction with prostaglandins, oxytocin, and/or artificial rupture of membranes as needed.35 The VBAC delivery rates were 69 percent for the mifepristone group and 50 percent for controls.
Data were insufficient to determine whether there was a relationship between the dose of induction agents and the vaginal delivery rate. Only one fair-quality study reported data on the mean, range, or maximum doses.
Rates of vaginal delivery when attempting TOL ranged from 60–82 percent. The largest population-based study reported a rate of 60.4 percent. The combined vaginal delivery rate for all prospective cohort studies, largely conducted in university or tertiary care settings, was 75.9 percent
There was a 10 percent reduction in the likelihood of vaginal delivery when oxytocin was used for ether induction or augmentation. There was a similar trend for prostaglandins.
How accurate are risk assessment tools for identifying patients who will have a vaginal delivery after a TOL?
| Variable | Beta Coefficient | Point Value |
|---|---|---|
| Age under 40 years | 0.95 | 2 |
| Vaginal birth history | ||
| Before and after 1st cesarean | 2.21 | 4 |
| After 1st cesarean | 1.22 | 2 |
| Before 1st cesarean | 0.43 | 1 |
| None | Referent | 0 |
| Reason other than FTP for 1st cesarean | 0.66 | 1 |
| Cervical effacement at admission | ||
| > 75% | 1.00 | 2 |
| 25%–75% | 0.58 | 1 |
| <25% | Referent | |
| Cervical dilation 4cm or more at admission | 0.77 | 1 |
Taken from Flamm, 199736
| Score | # of subjects with score | % of subjects with VBAC |
|---|---|---|
| 0 to 2 | 114 | 49.1 |
| 3 | 329 | 59.9 |
| 4 | 595 | 66.7 |
| 5 | 660 | 77.0 |
| 6 | 360 | 88.6 |
| 7 | 189 | 92.6 |
| 8 to 10 | 158 | 94.9 |
| Total | 2405 | 74.9 |
Taken from Flamm, 199736
Other scoring systems were developed retrospectively and have not been validated in a second sample.
Would these prediction tools be useful in practice? The probability that a woman would have a vaginal delivery is likely to influence her enthusiasm about trial of labor. Additionally, women who have a cesarean after a lengthy trial of labor are more likely to sustain adverse events such as uterine rupture or infection. Therefore, a tool that could accurately predict a woman's likelihood of achieving vaginal delivery with minimal adverse sequelae would be of interest to clinicians and patients. The value of a prediction tool depends on how it affects decisions about the likelihood of false positive and false negative tests (e.g., its accuracy), and the relative costs (harms) of false positive and/or negative results. The vaginal delivery rate in Flamm's population (e.g.. the overall rate of vaginal delivery), was 74.9 percent. Thirty percent of his population would be predicted to have a high probability of vaginal delivery (e.g., score or 6–10), and 18 percent were predicted to have a low likelihood of vaginal delivery (e.g., scores of 0–3). Slightly over half of the population would gain no additional information from using the predictive tool. Ten percent of the population or 253/2,405 may have been advised to have a cesarean, due to tool's prediction of low likelihood of vaginal delivery, when they would have been able to have a vaginal delivery. This may be acceptable as the harms of having a repeat cesarean may be low. What may be of higher concern is the false positive rate, or the chance that the tool would have encouraged TOL but the patient ended up with a cesarean. This is of higher concern because this group is of higher likelihood of sustaining complications from TOL such as infection and uterine rupture. This tool has a relatively low false positive rate of 2.6 percent (63/2405). Troyer's population had a similar vaginal delivery rate of 73 percent. The tool only provided additional information, to 32 percent of the population, with 22 percent predicted to have a high chance of vaginal delivery (e.g. score of 0), and 10 percent predicted to have a low chance (e.g. score of 3 or 4). This tool had a similar false positive rate of 2 percent (5/264), and slightly improved false negative rate at 4.5 percent (9/264). When this tool was used in a population with a lower pretest probability for vaginal delivery, both the false positive rate and false negative rate improved. Vinueza's population had a 63 percent vaginal delivery rate, 21 percent were predicted to have a high chance of vaginal delivery, and 10 percent a low chance. The false positive rate fell to 0.4 percent (1/263) and the false negative rate also fell to 3 percent (9/263). Thus, Flamm's tool may be preferred, from a diagnostic test perspective, due to an ability to stratify more of the population into high and low probability subgroups with a low false positive rate.
Seven studies43–49 examined the role of imaging modalities in predicting the outcome of a TOL after prior CD. In these studies a variety of imaging factors were considered, including the two fundamental aspects of labor: passage (pelvic dimensions) and passenger (fetal dimensions).
Four studies44, 45, 47, 49 focused primarily on the imaging of the passage using X-ray pelvimetry (XRP). Of these studies, three were retrospective cohorts 44, 45, 49 that were given poor-quality ratings because of inadequate control of confounding or effect modifiers, unequal application of measurements, and unidentified patient spectrum composition. The fourth study was a good-quality RCT by Thubisi.47 Half of the 288 subjects were assigned to receive an antepartum XRP evaluation; the remaining subjects were allocated to the postpartum XRP evaluation group. Of those in the antepartum group, 84 were considered to have an adequate pelvis and 23 of these delivered vaginally (27.7 percent). All of the patients considered on antepartum XRP to have an inadequate pelvis had an ERCD. Of those in the postpartum XRP group, 41.6 percent (60/144) delivered vaginally. In the postpartum XRP group considered to have an inadequate pelvis based on clinical examination, 60 percent (33/55) had a vaginal delivery, compared with 30 percent (27/89) of those considered to have an adequate pelvis. This study provides strong evidence that XRP is a poor predictor of TOL outcome and might unnecessarily increase CD rates.
Three poor-quality prospective cohort studies43, 46, 48 examined the value of a scoring system based on a variety of fetal and maternal pelvic measurements and calculated circumferences (fetal head, fetal abdomen, pelvic inlet, and midpelvis), to predict vaginal delivery. Two46, 48 of the three studies that focused on the fetal-pelvic index found that it was significantly associated with vaginal delivery; however, all three studies lacked adequate control for confounders and suffered from verification or workup bias.18
Two validated scoring systems categorized women into groups with likelihoods of vaginal delivery ranging from roughly 45–95 percent.36, 40
Flamm's tool was able to stratify more of the population into high and low probability subgroups, with a relatively low false-positive rate.36
By using a prospective cohort design and the largest study population, the best scoring system created a 10-point score based on the presence or absence of five variables commonly available for most patient admissions.36
An RCT clearly demonstrated the inability of XRP to predict route of delivery reliably.47
Imaging studies that combined the measurements of the pelvis and fetus showed promising results, but were limited by their lack of control for confounding and biases.46, 48
What are the relative harms associated with a TOL (spontaneous onset, induced, and augmented) and repeat CD?
No controlled trials directly compare the harms of a spontaneous TOL (without medical induction or augmentation), a medically augmented or induced TOL, and ERCD. The ideal study would compare the outcomes of women who were similar in every respect except that some had elected a TOL and others an ERCD. The ideal study would also determine whether, in the setting of VBAC, complications were associated with SL or only with labors in which oxytocin was used for induction or augmentation.
Three maternal complications were investigated: major maternal hemorrhage (requiring transfusion or hysterectomy), maternal infection (as manifested by endomyometritis, wound infection, and/or postpartum/puerperal fever), and maternal death (uterine rupture is detailed in question 4). While not all articles addressed each maternal complication, several addressed key aspects of these sequelae.
Two good-quality studies5, 20 provided information concerning both transfusion and hysterectomy rates. Rates of maternal hemorrhage requiring transfusion were 1.1 percent in the TOL group versus 1.3 percent for repeat CD in the large population-based study (NS)5 and 0.72 percent versus 1.72 percent for the prospective cohort study (p=.0001).20
While several studies provided information concerning hysterectomy, none specifically documented the indication for hysterectomy. Comparisons between TOL and elective CD were reported in three studies.5, 20, 30 The best evidence comes from the one large population-based study5 that found no difference in hysterectomy rates in TOL (0.2 percent) versus ERCD (0.2 percent). Unlike the two prospective studies reporting this outcome, McMahon attempted to exclude “elective” repeat CDs for medical or obstetric indications such as placenta previa.
The two prospective cohort studies reported higher hysterectomy rates in repeat CD: 0.12 TOL versus 0.27 percent ERCD20 and 0.27 TOL versus 3.2 percent in ERCD.30 These provide weaker evidence because the cesarean group may have included women who had an indication for CD and would not have been candidates for a TOL. In fact, in the latter study, Paul mentions that only 62 of the 157 “elective” repeat CD group were considered to be eligible for TOL. Thus it is possible that the higher rates of hysterectomy could be due to medical or obstetric conditions such as hemorrhage secondary to placenta previa. Hysterectomy rates were reported in only one induction study, reporting 0.2 percent in induced and 0.08 percent in SL patients.28 Overall, there was a trend toward increased risk for hysterectomy in induced labor (increased risk 0.12 percent) and ERCD (increased risk 0–3 percent). These studies did not specify whether hysterectomies were performed for hemorrhage or other indication (cervical cancer, myomatous uterus).
Studies reporting maternal infection rates are limited by lack of explicit definitions or by combining many sources of infection, which make specific clinical insights limited. No study provides data on the risk for spontaneous TOL that is free from medical augmentation. Two studies5, 24 defined infection clearly and compared the incidence in TOL and ERCD groups. Both definitions combined puerperal infection and abdominal wound infection. In the larger study,5 which defined maternal infection as puerperal fever (temperature >38 degrees C; uterine, urinary, pulmonary, or wound infection; or sepsis) or abdominal wound infection, the rates were 5.3 percent in TOL versus 6.4 percent in ERCD. Subgroup analyses found that women who had a TOL but did not delivery vaginally (e.g. failed TOL), had significantly higher infection rates than women who were able to deliver vaginally (failed TOL 8 percent versus successful TOL 3.5 percent). This finding was reported consistently among prospective cohort studies that performed similar subgroup analyses23, 26, 30 (11 to 30 percent increased risk of infection for failed TOL). The other study, a fair-quality prospective cohort,24 reported maternal infection rates (including endomyometritis and wound infection) of 6.79 percent in TOL versus 9.73 percent in ERCD.
Compared with spontaneous onset of labor, there appears to be a trend toward increasing risk of infection when labor is induced (1–4 percent increased risk) and with ERCD (2–3 percent increased risk). However, only one study of induction agents evaluated this outcome, and found zero in the induced group and 5 percent in the SL group.34
Six studies examined maternal death rates. The large population-based study found no maternal deaths in either TOL or ERCD groups totaling 6,138 women.5 In five prospective cohort studies involving approximately 19,000 patients, there were two deaths among women having a TOL and two among women having a repeat CD.20–23, 27 No maternal deaths were mentioned in any studies of induction of labor (n = 7,525).
APGAR scores. There are insufficient data to compare infant Apgar scores for a TOL versus ERCD. In one fair-quality prospective cohort study,20 more infants born from TOL had 5-minute Apgar less than 7 (1.47 percent versus 0.68 percent, p=.004).20
Infant death. No study has measured infant death directly attributable to a mother's choice of TOL or repeat CD. Two large, population-based studies provide information about whether TOL poses increased risk of infant death compared with ERCD.5, 6 Each has important strengths and limitations. One study5 (n = 6,138) reported perinatal death rates of 9/1,000 in the TOL group versus 5/1,000 in the repeat CD group for women with one prior CD. The strength of this study was its ability to identify a conceptual cohort of women with one prior low transverse CD who attempted TOL or repeat CD. However, no details were provided on these deaths (e.g., whether infants with lethal anomalies were included), so it is not possible to determine whether these deaths were attributable to labor or cesarean.
A more recent population-based study from Scotland6 did exclude all perinatal deaths associated with lethal anomalies and medical conditions; however, they did not do a good job of classifying patients as TOL and ERCD. To ascertain the perinatal death rate attributable to delivery method, the authors excluded all deaths associated with congenital anomalies, antepartum stillbirth (intrauterine fetal death), multiple gestation, and noncephalic presentation. Additionally, they excluded all primary CDs. They divided all remaining deliveries into women with no prior CD who were nulliparous or multiparous, and women with prior CD who delivered by planned repeat CD or TOL. The TOL group was defined as any vaginal delivery or emergent CD regardless of intended delivery route.
There were 20 deaths in 15,515 TOLs for a rate of perinatal death of 12.9/10,000 (95 percent CI, 7.9 to 19.9) versus one in 9,014 repeat CDs for a rate of 1.1/10,000 (95 percent CI, 0.0 to 6.1), and 135 in 137,630 nulliparous women without prior CD for a rate of 9.8 (95 percent CI, 8.3 to 11.6), and 90 in 151,549 multiparous women without prior CD for a rate of 5.9/10,000 (95 percent CI, 4.8 to 7.3). This study is discussed in significant detail in this report because it has not been reviewed in the literature to date.
The authors emphasized that the infant death rate was 11 times higher in women choosing TOL than in those having a CD, corresponding to one additional infant death for every 849 patients. The rate of infant death in women choosing TOL was similar to primiparous women having a vaginal delivery. This would indicate that the woman choosing TOL is not assuming considerable additional risk for her infant in choosing TOL in the second pregnancy. However, the rate of infant death for repeat CD patients appears to be spuriously low. The cesarean group may be low due to misclassification because all emergent CDs and vaginal deliveries were classified as TOL regardless of intended route of delivery. There were 20 perinatal deaths in the TOL group; eight were delivered vaginally and 12 were emergent CDs. If only three of these deaths were misclassified (e.g., women intending elective repeat who required emergent CD), there would not be a statistically significant difference between perinatal death rates in TOL and repeat CD groups. One study examined the rate of emergent CDs in each group.30 They report that two of nine (22 percent) emergent cesareans performed for fetal distress were performed for women who desired repeat cesarean. If this proportion were applied to Smith's emergent cesarean perinatal deaths, three of the 12 would have been expected to occur in the planned repeat cesarean group and 9 in the TOL group. This small change would eliminate the statistically significant difference that was observed. Another potential source of misclassification that would decrease the risk of planned CD compared with TOL is in the antepartum stillbirth data, all of which were excluded.
Even though the authors went to great lengths to consider confounding, there is still substantial detail missing in understanding the context in which these perinatal deaths occurred. For example, the authors were unable to determine the type of prior CD scar (classical, vertical, etc.). To exclude women who might have had classical incisions, they excluded all births that occurred before 40 weeks' gestation, with the thought that women with known prior classical incisions are generally delivered by cesarean before 40 weeks. In confining their sample to those women who delivered at 40 weeks or greater, they might have introduced an additional confounder in that risk of perinatal death increases with higher gestational age, especially 42 weeks and greater. In fact, when they looked at gestation less than 39 weeks versus greater than 39 weeks, they found only three deaths between 37 and 39 weeks, all of which had PGE2 induction of labor. One question that arises is in the group that was greater than 39 weeks' gestation: what proportion of the perinatal deaths were in infants who were 42 weeks' gestation or greater? One of the greatest concerns for women with prior CD is the risk of uterine rupture, and the resulting potential for maternal or fetal morbidity and mortality.
This study did not specifically examine the subset of perinatal deaths attributable to uterine rupture. Uterine rupture was combined with cord compression/prolapse, birth trauma, and asphyxia associated with disproportion in a category called “mechanical” causes. These events are all limited to vaginal delivery; therefore, it is not surprising that the authors found seven perinatal deaths attributed to “mechanical” causes in TOL and none in CD. Additionally, it is not clear how TOL versus planned repeat CD were classified (post-hoc or intention).
Another potential confounder is the use of induction and augmentation agents. The study reports deaths from 1992 to 1997, but does not describe how often induction agents were used, or in what doses, across Scotland during those years. Fifteen percent of their population with prior CD had PGE2 induction of labor. There was no association between PGE2 induction and increased risk of infant death. Although oxytocin was used, the authors were not able to examine whether oxytocin posed any increased risk. Communication with the authors revealed that oxytocin would be used for women with prior CD and premature rupture of membranes, but is not frequently used to augment women for failure to progress during labor.
Importantly, the population-based studies do not describe the likely outcomes of high-quality obstetric care. Even if one accepts that the increased infant death rate in the TOL group is real, the studies do not suggest an answer to the question, “Is there an increased risk of infant death in a properly managed TOL?”
Fifteen studies of induction agents reported infant mortality. Of these, 11 found no deaths in any group studied.22, 25, 27, 29, 30, 32, 34–36, 50, 51 In the other four, no consistent pattern emerged favoring spontaneous or induced labor.6, 28, 31, 52
In summary, there appears to be a trend toward increased risk of fetal death for TOL versus ERCD. Although these studies attempted to account for some confounders, their retrospective nature makes it impossible to determine whether the method of delivery is responsible for any increased risk. The validity of the recent publication from Scotland is uncertain because the infant death rate in the CD group appears to be spuriously low, deaths were not directly linked to uterine rupture, some antepartum deaths could have been misclassified, and the TOL group included women who really intended to have an ERCD.
Maternal death rates did not differ between TOL and ERCD.
The best evidence suggests that hysterectomy rates do not differ between TOL and ERCD.5
Rates of infection were increased in ERCD versus TOL (8.6–9.73 percent versus 6.6–6.79 percent).5, 24
Studies consistently reported significantly increased risk of infection for women who had a TOL but ultimately ended with a cesarean delivery (e.g. failed TOL).
There is conflicting evidence regarding whether induction of labor had any effect on infection rates.
There is insufficient evidence regarding the effect of selected route of delivery on APGAR scores.
No study has measured infant death directly attributable to a mother's choice of TOL or repeat CD.
Studies to date, consistently suggests that infant death may be increased by TOL versus ERCD. The degree of increased risk is uncertain (90/10,000 TOL versus 50/10,000 ERCD5 compared with 12.9/10,000 TOL versus 1.1/10,000 ERCD.6)
What is the incidence of uterine rupture, and are there methods for preventing major maternal and/or infant morbidity from uterine rupture?
Terms used to describe the severity of uterine ruptures are also used inconsistently. For example, the term “dehiscence” is frequently thought to signify an incidental finding of a cesarean scar defect either at cesarean or uterine exploration after vaginal delivery. However, among the 10 studies that use this term, three26, 30, 53 used the term to include symptomatic uterine rupture. The terms “complete” or “true,” which were used to modify “uterine rupture” in 13 studies,5, 6, 20–25, 27, 50, 54–56 had several inconsistent definitions, such as separation requiring operative intervention—e.g., emergent cesarean performed for maternal bleeding or FHR tracing abnormality associated with detecting a scar separation at cesarean; extrusion of fetus found at cesarean performed for failure to progress, scar with bleeding, hematoma formation, or extrusion of the fetus; scar rupture accompanied by intra-abdominal bleeding; or exclusively for separations associated with serious maternal or infant consequences such as death or hysterectomy.
A more subtle problem occurs when uterine rupture is defined as one requiring operative intervention. Typically, a symptomatic rupture is defined as one that is discovered when an cesarean is performed because of maternal bleeding, fetal heart rate disturbances, or other clinical signs. Because uterine rupture is a rare event, finding a uterine wall defect in the context of a FHR abnormality does not necessarily signify that the defect was the cause of the fetal tracing abnormality or further that the infant would have significant morbidity attributable directly to uterine rupture of a cesarean scar. Suppose, for example, that persistent bradycardia occurs in 1 percent of labors, and is 100 percent sensitive and 99 percent specific for a clinically significant rupture of a cesarean scar. If the risk of a symptomatic rupture is 1/100, then classifying all ruptures associated with bradycardia as “symptomatic” would inflate the apparent risk of “symptomatic rupture” by 100 percent (from 1 in 100 to 2 in 100). If the true risk of a symptomatic rupture is only 1/1000, the bradycardia would be due to the rupture in only 1 of 11 cases, and classifying all ruptures associated with bradycardia as symptomatic would inflate the apparent risk of symptomatic rupture by 1100 percent (from 1 in 1000 to 11 in 1000).
What we are most interested in quantifying and aiming to reduce is major maternal or infant morbidity attributable to uterine rupture of a cesarean scar.
This report uses the term “asymptomatic uterine rupture of a cesarean scar”to indicate the opening of a prior cesarean incision with no signs or symptoms; “symptomatic uterine rupture of a cesarean scar” is used for uterine separation diagnosed at laparotomy performed because of FHR disturbances, maternal bleeding, or other signs of potential maternal or neonatal consequences; major maternal or infant morbidity from a uterine rupture of a cesarean scar cesarean scar separation leading to significant neonatal or maternal mortality or morbidity (e.g., neonatal neurologic injury, neonatal asphyxia, or maternal hysterectomy).
Asymptomatic uterine rupture of a cesarean scar, also referred to as uterine dehiscence, is an asymptomatic separation of the uterine scar that is an incidental finding at cesarean or from manual exploration of the uterus following a vaginal delivery. Asymptomatic uterine rupture might not necessitate operative intervention. Five of eight prospective cohort studies reported routinely performing uterine exploration after VBAC (Evidence Table 7).21, 23, 24, 26, 27 In these five studies, rates of nonsignificant, asymptomatic uterine rupture ranged from 0/1,00026 to 18.9/1,000,23 with a mean weighted average rate of 12.6/1,000 in women undergoing TOL. Three studies compared TOL with ERCD in women with prior CD and asymptomatic uterine rupture of a cesarean scar (Evidence Table 7).23, 24, 57 For these three studies, there was no statistically significant difference between the rates for asymptomatic uterine rupture in TOL and 16.4/1,000 (95 percent CI, 5.39 to 28.4) ERCD 12.9/1,000 (95 percent CI, 4.28 to 26.2) (Figure 6
Three4, 5, 58 of seven4–6, 58–61 population-based retrospective cohort studies provide information about their method of classification for symptomatic uterine rupture. (Evidence Table 1). Two4, 58 used ICD-9 codes which have been demonstrated to be unreliable (see Appendix G).62 Nine fair to good observational studies provide the best evidence for the frequency of symptomatic uterine rupture of the cesarean scar.5, 20–24, 26, 27, 57 The Nova Scotia database5 had nurses and physicians extract data from charts based on an explicit definition of uterine rupture as a defect that involved the entire wall of the uterus, that was symptomatic, or that required operative intervention. They reported 10 symptomatic uterine ruptures in 3,249 TOLs (3/1,000) versus one in 2,889 cases of ERCD. Eight prospective cohort studies reported rates of symptomatic uterine rupture.20–24, 26, 27, 57 Rates of symptomatic uterine rupture ranged from 0/1,00057 in one of the smallest studies to 7.8/1,000 in the largest study.20 The pooled rate for all prospective studies was 3.16/1,000 (95 percent CI, 1.29 to 5.78). Two studies5, 57 provide comparative data for rates of symptomatic uterine rupture in TOL versus ERCD (Figure 7
One population-based study5, four prospective studies,20–22, 26 and one uterine rupture case series55 reported on uterine rupture-related hysterectomy with rates ranging from 0–33 percent. The total uterine rupture related hysterectomy rate among these studies was 26 in 159 cases of symptomatic uterine rupture (16 percent). Given a symptomatic uterine rupture rate of 3/1000, and 16 percent chance of hysterectomy given a symptomatic uterine rupture, our best estimate of the risk of uterine rupture-related hysterectomy for women choosing TOL is 4.8/10,000.
Uterine rupture was reported in 29 of 48 studies of labor induction; however, 15 of these did not report the definition used. Twelve studies reported no cases of symptomatic uterine rupture. Of those studies providing a clear definition of symptomatic uterine rupture and finding any cases of uterine rupture, the lowest rate among the induction groups was 0.35 percent (1 of 289) in a prospective cohort study of oxytocin,30 and the highest was 6.25 percent (1 of 16) in a randomized controlled trial of mifepristone.35 The rates of rupture among women undergoing spontaneous onset of labor in these studies ranged from a low of 0.15 percent in a prospective study of PGE2 gel36 to a high of 0.8 percent in a similar prospective cohort study of oxytocin.28
In studies comparing any method of labor induction with spontaneous labor (Figure 8
Comparing labors requiring oxytocin with spontaneous labor (Figure 9
All three studies32–34 of a prostaglandin versus spontaneous labor that reported uterine rupture rates used PGE2 gel (Figure 10
Only one study67 compared one induction method versus another. It compared misoprostol to PGE2 (gel or pessary) in a prospective cohort study that did not provide a definition of uterine rupture.67 This study found a higher rate of rupture with misoprostol, but the difference was not significant. The largest study of prostaglandin was excluded from analysis due to poor definition of uterine rupture.4 Although the precision and accuracy of the results are reduced, the magnitude of the effect showing an increase in the rate of uterine rupture suggests that a real association between PG induction of labor and uterine rupture probably exists.
Many have wondered whether there are any factors that can prevent poor neonatal outcome when there are signs of potential rupture. Two fair-quality case series55, 56 have studied cases of uterine rupture of the cesarean scar to determine whether any predictive premonitory signs exist. Leung et al. were the first to perform an exploratory analysis to study risk factors for poor neonatal and maternal outcome; particularly FHR and uterine contraction patterns.55 They identified 106 cases of symptomatic uterine rupture from 11,179 TOLs in women with prior CD at LA County-USC Women's Hospital, from which they were able to review the records of 99. The scar type was unknown in 99 percent of their population. They categorized cases of uterine rupture based on complete, partial, or no extrusion of the fetus. Combining death, asphyxia, and respiratory distress, they concluded that perinatal morbidity and mortality was significantly greater in cases where the fetus was extruded. However, they report that the six neonates requiring intubation were extubated and discharged from the neonatal intensive care unit (NICU) within 24 hours (range 1–24 hours) and were discharged from the hospital without adverse sequelae. If these six temporary outcomes (e.g., without significant adverse sequelae) are removed, major perinatal morbidity (asphyxia or death) occurred in 7/41 (17 percent) cases of partial or complete extrusion and 4/58 (6.9 percent) cases of nonextruded fetuses (p = 0.113). Of note, four of the fetal deaths occurred in patients who presented with fetal distress and underwent immediate CD, leaving two cases occurring in women undergoing supervised labor (one in the extruded group and one in the nonextruded group). Looking for premonitory signs of uterine rupture, they found that abnormalities of FHR tracing (prolonged deceleration only [defined as FHR less than 90 beats/min that exceeded 1 minute and without return to baseline], prolonged decelerations preceded by late decelerations, prolonged decelerations preceded by severe variables, mild late decelerations only, or fetal distress on admission necessitating CD) occurred in 91/99 cases (91.9 percent) and that all cases of fetal extrusion had prolonged decelerations. Prolonged decelerations occurred in 17/41 (41.5 percent) patients with extrusion and 15/58 (25.9 percent) without. In studying patients with prolonged deceleration further, they found that no patient who had prolonged deceleration only as their sign had significant clinical morbidity when delivery occurred within 17 minutes of the onset of deceleration. If the three cases of temporary neonatal intubation were removed, one case of neonatal asphyxia and no deaths in the prolonged bradycardia group would remain. Although the small numbers make the data unstable, it is intriguing that the one case of asphyxia occurred when there was 32 minutes between the onset of bradycardia and delivery, compared with 22 minutes and less in the group with intubation or no complications. Thus it is unknown what neonatal outcomes would arise between 22 and 32 minutes from bradycardia.
Leung et al. have done a superb job of exploring the details of their cases of uterine rupture; however, they are limited by the constraints of case series data. Data from a control group are important for understanding details about the association between fetal bradycardia and poor infant outcome. Decelerations are not rare; in fact, only 1.4 percent of all deliveries do not have FHR decelerations.69 Prolonged decelerations, especially given Leung's definition, are rare, occurring in 7.9–12.5 percent of patients receiving epidurals.70 Causes of prolonged decelerations include cervical examination; rapid decent in the second stage of labor; maternal hypotension due to positioning, epidural, or other; maternal hypoglycemia; reactive hypothermia such as with a cold amnioinfusion; prolonged cord compression (oligohydramnios); tetanic uterine contractions; maternal seizures, and cord prolapse, in addition to uterine rupture. Because fetal bradycardia is not specific to uterine rupture, the presence of a control group would allow some insight into associations with uterine rupture versus these other causes. Additionally, it is important to know details about the context of decision-making, in order to know what portion of time delays are preventable (e.g., substantial time between decision to go to cesarean and actual time for cesarean).
A second and more recent case series found no relation between time from FHR deceleration and infant outcome.56 All medical records in a single-institution hospital were examined to identify cases of “complete cesarean scar disruption,” defined as uterine scar separation that extended through visceral serosa. As above, the study was conducted in a tertiary care hospital with in-house anesthesia and obstetrics. The authors report on 23 cases of uterine rupture of a cesarean scar, six with partial or complete expulsion of the fetus. Fetal heart rate abnormalities—which included tachycardia and late, variable, or prolonged (not defined) decelerations—were the initial sign of uterine rupture in 87 percent of cases (four had pain, one vaginal bleeding, and one hematuria). Prolonged deceleration was the first sign of uterine rupture in 6/6 (100 percent) of the extruded patients versus 8/17 (47 percent) without extrusion. There was one perinatal death that occurred in the non-extruded group (late decelerations more than 25 minutes before delivery, failed vacuum extraction, then cesarean), and three cases of impaired motor development diagnosed as hypoxic-ischemic encephalopathy, occurring in the extruded group; delivery occurred 15,16, and 23 minutes from onset of prolonged deceleration. When they looked at metabolic acidosis (their primary outcome, defined as umbilical artery pH less than 7.0 with base deficit greater than 12mMol/L), they found a non-significant trend towards less time between first sign to delivery (18 versus 24 minutes) and decision to delivery (13 versus 17 minutes) in the group with metabolic acidosis compared with those without acidosis (p = 0.11). In this case, the greater time delays in the group without metabolic acidosis could reflect less concern by the physician and thus a slower overall movement, rather than programmatic delays.
In summary, the literature on uterine rupture suffers from inconsistent use of terms and ambiguous definitions. Additionally, because uterine rupture of the cesarean scar is often diagnosed at cesarean performed for fetal tracing abnormalities, there is diagnostic review bias. Studies conducted thus far to examine the relationship between duration of FHR disturbance particularly prolonged bradycardia and adverse perinatal outcome, have had conflicting results. It is important to further examine the relationship between fetal tracing disturbances (e.g., prolonged fetal bradycardia) and uterine rupture. This can only be done by comparing instances of a particular fetal tracing disturbance in women undergoing a TOL and noting how many times it is truly associated with uterine rupture (true positive) and how many times it is not (e.g., false positive).
The use of terms among studies is inconsistent.
Definitions of terms among studies are ambiguous.
There is not a significant difference in asymptomatic uterine rupture rates in TOL versus ERCD.
Symptomatic uterine rupture is significantly more common in TOL versus ERCD, with an increased risk of 2.7/1000
Based on the frequency and severity of symptomatic uterine rupture, the risk of perinatal death due to a rupture of a uterine scar is 1.5/10,000 and the risk of hysterectomy is 4.8/10,000. These rates of serious complications such as perinatal death, are probably more precise than overall risks from studies measuring death directly.
The definition of uterine rupture as an outcome is confounded by a definition that includes the potential predictor of FHR tracing abnormality.
Measurement of frequency of occurrence, predictors for what population is at greatest risk, and predictors for poor outcomes are difficult, because of the lack of standard case definition.
What is the health status and health-related quality of life for VBAC and repeat cesarean patients?
In general, there is limited research on the health status or health-related quality of life of patients in the weeks after any type of delivery. In studies of the general postpartum population, health status or health-related quality of life refers to general health, physical functioning, mental health, vitality, pain, social functioning, self-care activities, working, household psychosocial outcomes, and/or daily activities (including care of the infant).12, 71–74
No studies evaluated health status or health-related quality of life for women with a prior CD after a TOL, repeat CD, VBAC, or ERCD. There were no studies in the general birthing population that contained a subgroup analysis of women with prior CDs. Studies of the general postpartum population did not present data on subgroups of women with prior CD.72, 74 Similarly, it was not possible to extrapolate results from the RCT of breech presentation, which examined the effect of route of delivery on health status, because women with a baby in breech presentation might not be similar to women with cephalic presentation and prior CD.12 One review71 and one prospective cohort study75 separated health status and psychosocial results by planned, unplanned CDs and vaginal deliveries but neglected to describe the process, e.g., whether a TOL led up to the unplanned CD. Because of these limitations, the usefulness of these general postpartum population results as they relate to women with prior CDs is questionable. More research is needed.
There were no studies of health status or health-related quality of life for VBAC or repeat CD patients.
Regarding VBAC and repeat cesarean, what factors influence patient satisfaction/ dissatisfaction with their childbirth experience?
In this review, the term satisfaction refers to a feeling or a response to a birthing experience.76, 77 Women who were interviewed after birth described satisfaction as a happy feeling.78 Dissatisfaction was described as a negative feeling. Satisfaction is often multidimensional (e.g., satisfaction with information given, care and treatment, patient's involvement in decisionmaking, and control in process).79 In this study, women might be satisfied with one aspect of the birthing experience but dissatisfied with another. The context, birth process, and outcome affect the woman's sense of satisfaction.78 Understanding how women feel before, during, and after the birth experience has not been explored.76
Studies that have measured satisfaction in the general birthing population suffer from a potential bias. Clinicians often gather the satisfaction data directly from the patients .80 Also, the timing of the measurement might introduce recall bias. In five of 10 studies of one review, the satisfaction results were collected within days or weeks of delivery.80 Several investigators have hypothesized that a woman having an emergency CD might be less critical if she believed the CD was performed to protect her own health or that of her baby.80–82 The literature that focused on satisfaction for women attempting TOL and those choosing an ERCD was evaluated with these potential biases in mind.
These two studies reported satisfaction (feelings) of patients with differing delivery outcomes.83, 84 One study reported feelings for patients achieving VBAC84 while the other reported feelings of mothers (and fathers) who chose TOL but had another CD or who chose ERCD.83
| Vaginal delivery | Prior CD | |
|---|---|---|
| Total ineffective responses | 37 | 65 |
| Total adaptive responses | 42 | 12 |
Chi square [1, n = 156] = 22.70, p < .0005)
| Feelings of. . . | Percent of Patients with First CD (n = 105) | Percent of Patients with first CD and Prior VD (n = 32) | Percent of Patients with second (or more) CDs (n = 91) |
|---|---|---|---|
| Relief | 86 | 78 | 90 |
| Disappointment | 68 | 56 | 34 |
| Frustration | 41 | 56 | 35 |
| Joy and happiness | 93 | 67 | 90 |
| Failure | 25 | 31 | 18 |
| Difficulty relating to baby | 14 | 13 | 7 |
| Guilt | 20 | 22 | 11 |
| Anger | 20 | 28 | 20 |
| Concern about scar | 30 | 25 | 15 |
| Guilty about dissatisfaction with birth experience | 20 | 19 | 10 |
| Uncertain about what you could do when you got home | 33 | 59 | 21 |
CD=cesarean delivery; VD= vaginal delivery
| Feelings of. . . | Percent of Patients with Firstt CD Birth (n = 105) | Percent of Patients with First CD and Prior VD (n = 32) | Perfect of Patients with Second (or more) CD (n = 91) |
|---|---|---|---|
| Relief | 93 | 76 | 90 |
| Fear for mother and baby | 70 | 55 | 52 |
| Being left out | 46 | 38 | 32 |
| Joy and happiness | 91 | 59 | 94 |
| Anger | 16 | 10 | 11 |
| Guilt | 10 | 3 | 11 |
| Difficulty relating to the baby | 7 | 3 | 4 |
| Uncertain about what you could do when you got home | 35 | 21 | 15 |
CD=cesarean delivery; VD= vaginal delivery
For both fathers and mothers, the feelings expressed most often by patients were of relief (that labor was completed and mother and baby were healthy) and joy and happiness. The proportion expressing these feelings was reduced when it was a couple who had experienced a CD after a prior VD.
The couples that participated in this study were self-selected and probably not representative of the general obstetric population. For example, 59 percent of the couples responding to this survey had attended prenatal classes compared with 30 percent in the general population for that region. Also, the study would be more pertinent to this review if the results had identified the subgroup of repeat CD patients who initially tried TOL.
Studies of patient satisfaction largely consisted of patient's own provider obtaining information about satisfaction, introducing the possibility for measurement bias.
Only two cross-sectional studies used methods other than the patient's own provider to obtain satisfaction information.
No study measured satisfaction for the three types of delivery outcomes that could be experienced by women with prior CDs (VBAC, TOL followed by CD, or ERCD), which leaves room for much needed research.
How are economic outcomes related to VBAC, repeat CD, and their respective complications?
One component of the decision to attempt a TOL or perform an ERCD is the economic value of each approach. Comparisons among alternative approaches can be evaluated using a cost-effectiveness design or other economic evaluation. While economic considerations should not be the sole driver for such a decision (unless TOL and ERCD are deemed clinically equivalent), the relative value of each approach might influence the decision.
Chung et al.87 focused on the probability of vaginal delivery for TOL and the cost-effectiveness of TOL in women with prior CDs. The study followed the guidelines for such analyses, including use of quality-adjusted life years (QALYs).100 A QALY compares a certain state of health (e.g., life after a hysterectomy) to a perfect state of health. This analysis included a societal perspective, performed a long-term analysis, and included most adverse events associated with the two modes of delivery. The paper focused on sensitivity analyses for the rate of successful TOL (that is, achieving VBAC). If the TOL success rate is less than 65 percent, ERCD cost less and provided more QALYs than TOL. This means that ERCD is more cost-effective or more efficient. For TOL success rates between 65 percent and 74 percent, ERCD provided more QALYs at a cost of less than $50,000 per QALY (the upper limit of cost-effectiveness used in this article). For TOL success rates between 74 percent and 76 percent, ERCD provided more QALYs but at a prohibitive cost (greater than $50,000 per QALY). When the probability of vaginal delivery for TOL exceeded 76 percent, TOL was more effective and less costly. The results were also sensitive to the probability of infant mortality, costs for “moderate” morbidity for the infant, the probability of urinary incontinence, the discount rate, and the probability of cesarean rupture. The authors defined moderate morbidity for the infant, “...principal diagnoses of meconium aspiration, neonatal infection/sepsis screening, and respiratory distress/failure.” The authors recommend that more precise tools be developed to estimate the probability of a successful TOL and, if the probability of success were 74 percent or greater, that TOL would be the efficient (cost-effective) choice; if the probability of success were less than 74 percent, ERCD would be the efficient choice. Clearly, the success probability for TOL was a key variable in these analyses. Chung's analysis did not consider future pregnancies.
The study by Grobman et al.88 used a variety of literature sources and estimated a cost of $2.4 million (M) to prevent one major neonatal adverse outcome by performing ERCD instead of TOL. This means that 1,591 ERCDs would be performed resulting in 0.1 additional maternal deaths and 74 additional maternal morbid events to prevent one serious neonatal outcome. Extensive sensitivity analyses estimated that the cost to prevent one major neonatal outcome would exceed $1M for all scenarios considered. This estimate was based on a payer or health care system perspective and considered a range of adverse outcomes including maternal and neonatal deaths and other major adverse outcomes.
Among the remaining 10 studies, there is at least one fatal flaw in each that cast doubt on the conclusions drawn. Several shortcomings are consistent across the 10 reports: the lack of cost data (reliance on charge data), failure to consider all relevant outcomes (especially among adverse events), lack of a societal perspective, and failure to use a recommended effectiveness outcome as the QALY.
Based on the economic evaluation with the best quality score, when the probability of vaginal delivery is 76 percent or greater, TOL is more cost-effective and provides higher quality of life.
Based on the economic evaluation with the best quality score87 and assuming costs per QALY of $50,000 as cost-effective, the more cost-effective of TOL and ERCD depends on the probability of successful VBAC after TOL.
Further evaluation is needed of the sensitivity of the probability cut point of 76 percent to other potential predictor variables.
What individual factors influence route of delivery?
| Category | Factors (number of studies) | |
|---|---|---|
| Age (20) | ||
| Demographic | Race (1) | SES (0) |
| Past Obstetric | Gravidity (6) | Number of prior CD (22) |
| Parity (12) | prior CD Indications: | |
| Prior VD (26) | Recurrent versus Nonrecurrent (61) | |
| Order of Prior VD (10) | Recurrent versus Breech (44) | |
| Previous Cervical Dilation (7) | Recurrent versus Fetal Distress (41) | |
| Current Obstetric | Gestational age (15) | Bishop score (2) |
| Birth weight (37) | SL (26) | |
| Multiple gestations (3) | Induced labor (26) | |
| Breech/External Cephalic | Augmented labor (21) | |
| Version (3/3) | Oxytocin use (nonspecified) (25) | |
| Cervical dilation (8) | Epidural use (16) | |
| Cervical dilation rate (2) | Maternal height (5) | |
| Cervical effacement (5) | Maternal weight (4) | |
| Station (5) | Maternal weight gain (3) | |
| NonClinical | Insurance (1) | Physician (0) |
| Hospital (2) | ||
Bold factors are those that had adjusted ORs from fair-to-good-quality studies
There were no fair-to-good quality studies for the individual factors of maternal race or socio-economic factors.
While over 50 studies have investigated the influence of clinical history and past obstetric factors on the outcome of TOL after prior CD, only five were of fair-to-good quality. This relatively small percentage of quality studies did not provide any information for the individual factors of gravidity, parity, and previous cervical dilation.
| Factor | Author (year) | Adjusted OR for VBAC | 95 percent CI p-value |
|---|---|---|---|
| Prior VD | McNally 1999107 | 27.78 | 3.85–200 |
| Order of prior VD | |||
| Before prior CD | Flamm 199736 | 1.53 | 1.12–2.10 |
| Weinstein 199642 | 1.8 | 1.1–3.1 | |
| After prior CD | Flamm 199736 | 3.39 | 2.25–5.11 |
| Macones 200138 | 7.69 | 3.23–20 | |
| After vs. Before prior CD | Caughey 1998112 | 3.48 | 1.9–6.1 |
| Before & After prior CD | Flamm 199736 | 9.11 | 2.18–38.04 |
| Number of prior CD | Pickhardt 199239 | 0.43 | p<0.05 |
| Prior CD Indication | |||
| Nonrecurrent vs. Recurrent | Flamm 199736 | 1.93 | 1.58–2.35 |
| Recur vs. Nonrecurrent | Weinstein 199642 | 0.8 | 0.3–2.0 |
| Breech vs. Recurrent | Weinstein 199642 | 1.9 | 1.0–3.6 |
| Fetal Distress vs. Recurrent | Weinstein 199642 | 1.05 | 0.4–2.6 |
Bold=significant; NR=not reported; NS=not significant
When considering the issue of prior CD, the two most investigated factors include the number of prior CDs and prior CD indication. Of the 22 studies looking at the number of prior CDs, only one was rated as being fair in quality.39 Consistent with the overall literature, Pickhardt39 demonstrated that the probability of VBAC significantly decreased as the number of prior CDs increased (adjusted OR 0.43; p < 0.05). By controlling for a great number of potential confounders in his analysis, Pickhardt established this factor as a true independent predictor of TOL outcome. Also consistent with the overall VBAC literature were the findings of the two36, 42 of 61 studies given a fair rating regarding prior CD indication. While Flamm36 demonstrated that those with a nonrecurrent indication compared with those with a recurrent prior CD indication (CPD or failure to progress), had a significantly higher VBAC rate (adjusted OR 1.93; 95 percent CI, 1.58 to 2.35), Weinstein42 showed similar, yet nonsignificant findings. Weinstein also found that although nonsignificant, those with a prior CD indication of breech presentation or fetal distress had a greater chance of VBAC compared with those with a recurrent indication (adjusted OR 1.9; 95 percent CI, 1.0 to 3.6 and adjusted OR 1.05; 95 percent CI, 0.4 to 2.6, respectively). As reported by previous studies, those with a prior CD indication of breech presentation had the highest relative likelihood of VBAC.
We found no fair or good studies addressing the factors of multiple gestations, cervical dilation rate, SL, induced labor, oxytocin use, maternal height, maternal weight, and maternal weight gain.
Three case series provide the only data regarding the association between external cephalic version (ECV) and VBAC.104, 105, 108 Rates for VBAC after ECV attempts ranged from 65.8 to 100 percent. By comparing ECV attempts in those with prior CD to those without prior CD, Flamm105 showed that those with prior CD were significantly more likely to be successfully verted (82 percent and 61 percent, respectively, p = 0.02). Although the overall VBAC rate in these three studies ranged from 50 to 54.5 percent, de Meeus104 showed that of those who had a successful version, the VBAC rate was actually higher (76 percent). Another finding of interest came from the Schacter108 study, which found that those delivering within a week of ECV had a significantly lower VBAC rate compared with those who delivered more than a week after ECV (0 percent [0/4] and 86 percent [6/7], respectively).
| Factor | Author (year) | Adjusted OR for VBAC | 95% C p-value |
|---|---|---|---|
| Gestational Age | Pickhardt 199239 | 0.81 | p < 0.05 |
| Zelop 2001110 | 0.67 (>40wks GA, spontaneous) | 0.56–0.83 | |
| Zelop 2001110 | 0.67 (>40wks GA, induced) | 0.45–0.91 | |
| Birth weight | Weinstein 199642 | 0.95 (>4000g) | 0.17–5 |
| Zelop 2001111 | 0.59 (>4000g) | 0.45–0.77 | |
| Cervical Dilation | Flamm 199736 | 2.16 (>4cm) | 1.66–2.82 |
| Macones 200138 | 1.87 | 1.14–3.23 | |
| Pickhardt 199239 | 1.62 | p < 0.05 | |
| Stronge 1996109 | NR | NS | |
| Effacement | Flamm 199736 | 2.72 (>75%) – referent <25 percent | 2.00–3.71 |
| Flamm 199736 | 1.79 (25–75%) – referent <25 percent | 1.31–2.44 | |
| McNally 1999107 | 5.0 (100%) | 1.28–19.23 | |
| Station | Stronge 1996109 | 12.3 | 4.6–33.3 |
| Bishop score | Weinstein 199642 | 6.0 (score >4) | 3.5–10.4 |
| Augmentation | Macones 200138 | 0.47 | 0.25–0.88 |
| Stronge 1996109 | NR | NS | |
| Epidural use | McNally 1999107 | 0.26 | 0.06–1.12 |
Bold=significant; NR=not reported; NS=not significant
The effects of various medications on TOL outcome have been one of the more heavily investigated areas of VBAC literature. No fair-to-good-quality studies provided information regarding labor induction or oxytocin use (in general); however, of 21 studies that provided information regarding the factor of labor augmentation, there were two fair-quality studies.38, 109 Although Macones38 demonstrated that those with labor augmentation were significantly less likely to have VBAC compared with those without augmentation (adjusted OR, 0.47; 95 percent CI, 0.25 to 0.88), Stronge109 found no significant association between labor augmentation and TOL outcome. Once again, one could speculate that this difference in results could be due to a lack of power in Stronge's study to find an association or perhaps due to a differential level of confounding adjustment. Of the 16 studies to investigate the influence of epidural use on the outcome of TOL, only one was of fair quality. Although nonsignificant, McNally107 demonstrated that those with the use of an epidural tended to have a lower likelihood of VBAC compared with those who did not use an epidural.
Although medical decisions are often based on clinical factors alone, it is important to remember that nonclinical factors might also play an important role in VBAC. For example, McMahon5 found that those who attended prenatal classes were significantly less likely to fail a TOL compared with those who did not attend (crude OR, 0.8; 95 percent CI, 0.6 to 0.9). In addition to this, Fraser106 conducted a fair-quality RCT comparing the effect of either a verbal-based (individualized discussion program) or a document-based (pamphlet) prenatal program for those attempting a TOL after prior CD. Although statistically nonsignificant, the results showed that those in the verbal treatment arm had a higher rate of VBAC compared with those in the document treatment arm (53 percent and 49 percent, respectively; RR, 1.1; 95 percent CI, 1.0 to 1.2). This review investigated the influence of three nonclinical factors (i.e., insurance, physician characteristics, and hospital characteristics) on the outcome of a TOL after prior CD.
While a number of studies in the VBAC literature provided information regarding the nonclinical factors of insurance status, physician characteristics, and hospital characteristics, none of them were of fair-to-good quality. The majority failed to adjust for confounding (e.g., Socol113, McMahon5); those that did provide adjusted ORs (e.g., Goldman,114 King,115 Stafford116) did so using database information that limited them to the comparison between those with VBAC and those with CD, which included those with either an ERCD or a failed TOL.
The vast majority of studies looking at individual factors that influence the route of delivery were of poor quality due to inadequate control for confounding factors.
The factors that were significantly associated with an increased likelihood of vaginal delivery (i.e., successful TOL) were: maternal age less than 40 years,36 PRIOR VD (particularly vaginal delivery after cesarean),36, 38, 42, 107 a nonrecurrent indication for the prior CD,36 and favorable cervical factors.36, 38, 39, 42, 107, 109
The factors that were significantly associated with a decreased likelihood of vaginal delivery (i.e., failed TOL) were: an increasing number of prior CDs,39 gestational age greater than 40 weeks39, 111 birth weight greater than 4000 g,111 and augmentation of labor.38
What factors influence a patient's decision making regarding VBAC or ERCD?
Several factors might influence a patient's preference for TOL, including education about VBAC, the patient's ethnicity, and social motives. Preference refers to choice about delivery method (TOL or ERCD).
Two recent systematic reviews80, 117 that addressed a women's choice for delivery reported that the included studies were descriptive and had many methodologic limitations: small sample sizes, selection bias, recall bias and preferences assessed by potentially biased observers. In particular, one review noted that in seven of 10 studies, the women's own providers recorded the patient's preferences for delivery.80 This direct involvement by women's providers in recording results might have influenced women's responses. Also, only three of the 10 studies reported if the women received education on birthing options, so whether the women made informed decisions was unclear. There were also conceptual issues to consider. Only seven of 10 studies reported whether the women requesting ERCD had an obstetric contraindication for TOL. Some women might not really have had a choice to make.
The findings of these two reviews80, 117 provided a backdrop for the current review. Before considering patient preference results, the studies were evaluated for the methodologic limitations identified in these reviews.
The methods to collect patient preference data varied across the included studies. In four of the 11 studies, the women completed questionnaires.57, 84, 106, 118 In two studies independent researchers interviewed the patients about their reasons for delivery.120, 124 In one retrospective cohort study, certified abstractors reviewed the charts, followed by a second reviewer, an obstetric nurse.121
Only the RCT met all criteria and was rated good quality for all results.106 We rated the remaining studies fair because they did not clearly state their inclusion or exclusion criteria,122–124 they had fair followup (60 to 80 percent),118 were unclear about followup,57 or had unreported followup rates.24, 84, 128 Other reasons for a fair rating included no description of how the measures were tested for validity or reliability,24, 118, 120 or a lack of clarity about who interviewed patients.119 When the inclusion/exclusion criteria were not reported or were vague, the number of women eligible for TOL was unknown. Attempted TOL rates and VBAC rates for three studies were unknown.118, 123, 124
Before patient preferences were assessed, the proportion of women who actually had a choice was determined for each study. The proportion of eligible women (minimal requirement: low-transverse scar, singleton fetus, and no other contraindications) choosing to attempt a TOL ranged from 22.6 to 90 percent in the six fair-to-good-quality studies that were clear about the inclusion/exclusion criteria.24, 57, 106, 119, 121, 128 As might be expected, the two studies conducted in the early 1980s24, 57 had much lower attempt rates (22.6 to 31.5 percent) compared with the other four studies, which were conducted between 1989 and 2001 (attempt rates 42 to 90 percent).106, 119, 121, 128
In total, 1,083 of 2733 eligible women in six studies chose TOL (sample weighted average of 39.6 percent).24, 57, 106, 119, 121, 128 The VBAC rate for eligible women choosing TOL ranged from 56.5 to 84.5 percent. In total, 778 of the 1,083 eligible women had a VBAC (sample weighted average of 71.8 percent).
The heterogeneity of the inclusion criteria (when they were assessed) might have contributed to variation in the proportion choosing a TOL. In three studies the women were pregnant and had a history of a prior CD when preference was assessed.24, 119, 122 In three studies the women were assessed within days of delivery.84, 106, 118 In one study the assessment was within 1 month of delivery,124 and in one study the women were assessed several months after delivery.57 Finally, in one study the women were interviewed both when they were pregnant and postpartum.120
Several factors (race, prior VD, social motives, safety, future childbearing plans) appeared to influence choice of delivery. The proportion of nonwhite patients ranged from 2.4 to 47 percent in the four fair-quality studies that reported race.118, 120–122 Only one prospective cohort study of good quality examined the effect of race on preference.120 In this study 23/43 (53.5 percent) nonwhite patients attempted a TOL and 42/50 (84 percent) of white patients attempted a TOL. Forty-seven percent of the nonwhite patients were black, 28 percent were Latino, and 21 percent were Asian. All women in this study were middle-class and working class women. Although the white patients were more educated than the nonwhite patients, all other socioeconomic status indicators were similar. Several results in this study suggested that the minority patients had less opportunities to gain medical information about delivery options than white patients. Fewer minority patients attended childbirth courses (43 percent) during their first pregnancy when compared with white patients (81 percent) (p < .0001). Compared with white patients, minority patients were less likely to have been told by their former providers after their prior CD that VBAC was possible (p < .003). Even though minority patients received less medical information and encouragement for a TOL, more patients (39 percent) identified the provider as an important influence in their decision, compared with 19 percent of white patients (p < .02).
In addition to informational differences between the races, underlying cultural ideologies might account for the different approaches to delivery.120 From structured interviews, these investigators reported that ethnic minority women viewed labor as a painful necessary evil that does not relate to one's intrinsic worth. Forty-six percent of minority patients did not want to experience labor again compared with 22 percent of white patients. If a woman could become a mother through a less painful, less risky manner, e.g., with an ERCD, no one look downed on them. By contrast, these same investigators described the view of labor by white patients as a challenge to be overcome to gain full status as mothers. White women viewed vaginal birth as a “once-in-a-lifetime experience not to be missed.”
Two of 11 studies examined prior VD as a predictor for a TOL preference.24, 123 In both studies, patients who had delivered at least one baby vaginally were more likely to choose TOL. A greater proportion of the women choosing TOL had a history of vaginal delivery either before or after their CD (18/53, 40.0 percent) when compared with women who chose ERCD (only 5/46, 10.9 percent had prior VDs) (p = 0.007).123 Possibly, women who have already succeeded with a vaginal delivery have a stronger self-efficacy or belief that by doing a TOL they will indeed deliver the baby vaginally. One cross-sectional study that examined state anxiety reported that women choosing TOL had lower state anxiety and felt better prepared than women choosing ERCD.122 Four of 11 studies cited fear of labor or fear of failure as a strong reasons for choosing ERCD.57, 118, 123, 124 These patients felt that a TOL would lead to a difficult labor, failure to deliver vaginally, and, in the end, another CD.57
Social motives (ability to care for children at home, convenience) appeared more often in these studies as the primary reason for selecting TOL or ERCD than careful weighing of health risks for mother or baby. Six of the seven studies that reported patients' reasons for choosing TOL cited “easier recovery” as a strong reason.84, 118, 120, 122–124 Women in these studies already had children at home who needed care, so a shorter delivery was very desirable. Five of the six studies reported that the women wanted to experience a vaginal birth.84, 118, 120, 122, 124 Structured interviews with women before delivery and 2 months after delivery showed that the women also chose TOL so their husbands could be more involved.128, 129 Finally, two of 10 studies cited convenience as a primary reason for ERCD.57, 118 A scheduled delivery allows mother and provider to set a date that coordinates well with work and allows time to plan for childcare.
Safety for the mother and/or baby was cited as an important reason in only four of the 11 studies reporting reasons for deliveries.84, 118, 122, 124 In a cross-sectional survey of women who had just delivered healthy babies either by ERCD or VBAC, 18/21 women who chose and delivered by VBAC felt that vaginal delivery was safest for the mother compared with 7/11 women who chose and delivered by ERCD.124 In this same group of mothers who chose and delivered by VBAC, 10/21 felt vaginal delivery was safest for the infant also, compared with 2/11 who chose and delivered by ERCD. Since this study only recruited women with healthy babies, the results are potentially biased in that the patients tended to believe the method was safe because the outcome was good. Another study using structured interviews showed that the women did not know actual probabilities or complication rates when they made their decisions.129 It was unclear if the provider had told them the probabilities and they did not recall them or place importance on them, or if the patients were never informed of the actual probabilities.
Only one good-quality RCT106 and two fair-quality prospective cohort studies24, 120 examined the effect of future childbearing plans on the birthing preference. In the RCT, 23 percent of women with a low motivation for a TOL desired to have a ligation sterilization compared with the 13 percent of women with a high motivation for TOL.106 In one prospective cohort study,128 22/56 (39.3 percent) women having an ERCD had their tubes tied after delivery, compared with 4/44 (9.1 percent) of women delivering vaginally. Similarly, more women having an ERCD, 245/547 (44.8 percent) requested a ligation sterilization, compared with 18/101 (17.8 percent) of women experiencing VBAC, and 14/61 (23.0 percent) choosing TOL but having a CD.24
The confidence a woman has to succeed at TOL might also be related to how knowledgeable she is about VBAC, particularly before she becomes pregnant or early in her pregnancy. Only three of the 11 studies with valid results described an education process for women with prior CD.106, 120, 121 The best-quality study, a good-quality RCT,106 reported that overall there was no difference in the proportion of eligible women attempting a TOL when given a pamphlet at 21 weeks' gestation versus an individualized VBAC education and support program started at 21 weeks' gestation. However, when the subgroup of patients with very low motivation for TOL was educated and given support, more patients, 28/86 (32.6 percent) chose TOL than the very low motivated patients who received pamphlets (18/93, 19.4 percent) (RR, 1.7; 95 percent CI, 1.0 to 2.8, p = 0.043). The investigators also commented that it was possible that the intervention was launched too late to influence the patient's choices. Indeed, 28 to 49 percent of patients in four other studies had decided to attempt a TOL before the pregnancy began.84, 118, 123, 124 Another 34 to 40 percent of patients decided to attempt a TOL before the midpoint of their pregnancy.118, 124 The results of these studies suggest that education should be started shortly after the first CD, perhaps at the first postnatal visit.123 In contrast, only 0 to 15 percent of the women in two studies had decided to have a ERCD before their pregnancy began, but 25 to 42 percent had selected it by the middle of the pregnancy.118, 124
The likelihood of VBAC counseling also appears related to the overall CD rate of the hospital the patient chooses for delivery. One fair-quality retrospective cohort study of 51 California hospitals reported that hospitals with higher overall CD rates had higher rates of ERCDs without documented evidence of counseling regarding TOL.121 In this study, 1,662 birth records were randomly selected from 11 “high CD” hospitals (average CD rate of 30 percent), from 32 “intermediate CD” hospitals (average CD rate of 21 percent), and from eight “low CD” hospitals (average CD rate of 15 percent). Of women eligible for TOL who chose ERCD, 21 percent of women at the “high CD” hospitals had no documented proof of counseling, compared with 15 percent of “intermediate CD” hospitals and 0.3 percent of “low CD” hospitals (p < 0.01 for the three proportions). Another 36 percent of women at “high CD” hospitals were counseled but refused TOL, compared with 29 percent at “intermediate CD” hospitals and 10 percent of women from “low CD” hospitals (p < 0.01 for three proportions). The study further reported that once a patient had been counseled and consented to a TOL, she had a similar chance of a vaginal delivery regardless of the underlying hospital CD rate.
The patient's exposure to VBAC education appears related not only to the hospital she chooses for delivery but also to her own specific physician. The specific wording the provider uses in discussing TOL with patients is difficult to document and might reflect the provider's underlying preferences. In one retrospective cohort study of the general birthing population (not focused on patients with prior CD) for 11 physicians, the variances for CD rates were not explained by patient obstetric risk factors, socio-economic status, service status, or physician's experience, suggesting that the physician's own practice style might influence route of delivery.130 In a cross-sectional study of 19 public hospitals in Italy, obstetricians would chose TOL if they worked at a large hospital (delivered more than 1,000 babies/year) (p < 0.01), and if they worked at a hospital with a CD rate of less than 25 percent (p < 0.001).131
The education and support for TOL a patient perceives from her physician might also be related to her ethnicity. In one fair prospective cohort study, 60 percent of nonwhite patients were aware of a VBAC option before the pregnancy, compared with 86 percent of white patients (p < 0.003).120 Seventy-two percent of white patients felt they received “some to much” information and encouragement by their provider on attempting a TOL, compared with 50 percent for nonwhite patients (p < 0. 005). Although white patients perceived that they received sufficient information, a lower proportion of white patients placed great value on their physician's information than nonwhite patients. Thirty-nine percent of nonwhite patients in one prospective cohort study felt the doctor was an important influence, compared with 19 percent of white patients (p < 0.02).120
Patient preferences for birth choice are unclear because of the heterogeneity of the 11 included studies.
Several factors appear related to choice for TOL (white race; prior VD; lower levels of anxiety during the pregnancy).
Lack of medical information along with cultural ideologies might account for minority women being less likely to attempt a TOL when compared with white women.
A woman's choice for delivery was often based on social motives (e.g., easier recovery, so she can care for baby and children at home).
Only four of 11 studies cited safety for mother or baby as important reasons for delivery choice.
It remains unclear if VBAC education increases the proportion of women who choose TOL. Future studies of education should include education before next pregnancy, perhaps at the postnatal visit of patients with first CD. Future work should also insure that all patients regardless of race receive the same information.
How do legislation, policy, guidelines, hospital characteristics, provider characteristics, insurance type, and access to care affect health outcomes for VBAC candidates?
King and Lahiri115 considered a variety of medical and socioeconomic predictors of rates of VBAC including two variables related to professional liability. These two variables were annual average paid loss (for years 1985-1989) of the hospital due to malpractice claims settlements divided by patient days and the mature-claims-made rate for OB/GYNs in the county of the hospital. A multiple logistic model to predict the probability of VBAC was developed. This model adjusted for a variety of patient demographic and socioeconomic characteristics and for hospital characteristics. The authors fit models with and without data from New York City to determine whether the influence of a characteristic on the results was due largely to New York City. Hospital-paid loss due to practice claims was statistically significant when New York City patients were excluded (OR, 0.96; 95 percent CI, 0.95 to 0.98) but not when New York City patients were included (OR, 1.01; 95 percent CI, 0.99 to 1.03). The physician's premium was statistically significant with the inclusion of hospitals in New York City (OR, 0.98; 95 percent CI, 0.97 to 0.99 for risk of a $5,000 increase in annual premiums) but not when New York City hospitals were excluded (OR, 1.01; 95 percent CI, 1.00 to 1.08). No summary statistics are provided to facilitate interpretation of these ORs and inclusion of interaction terms for New York City would have been more useful. Whether these ORs are statistically significant, the magnitude of the OR is small, indicating relatively little impact on rates of VBAC. While the professional liability variables are statistically significant, since the odds ratios are close to 1.0 they may not be very meaningful.
These two studies provide little evidence of the impact of legal or legislative components on rates of VBAC. For the paper by King and Lahiri,115 the effect of hospital paid loss due to malpractice claims settlements and physician's malpractice premiums were relatively small (OR very close to 1.0). Changes observed in VBAC rates in Studnicki et al.132 occurred only in some risk strata. There are not studies regarding the impact of the current malpractice crisis on availability of obstetric providers and impact on a patient's options. Thus additional research needs to be conducted to determine the influence of legal and legislative factors on changing provider behavior relative to type of delivery.
Bickell et al.134 selected a random sample of 45 hospitals in New York to receive a program of peer review and audits of 100 cases of labor and delivery with feedback These hospitals were compared with the remaining 120 hospitals in the state to determine differences in VBAC and repeat CD rates. While there was a significant difference in the overall CD rate, there were no significant differences in rates of VBAC or repeat CD, when comparing the year before audits began (1988) with the year after the audits and feedback were completed (1993) There were no differences in baseline characteristics reported and no adjustment was made for potential confounders.
There was one retrospective cohort study rated fair. Santerre,136 using data from a group of 55 hospitals in Massachusetts, performed a regression analysis on VBAC rates over 9 years (1985-1993) during which time the ACOG guidelines were published (in 1988). Using a model that adjusted for potential confounding variables including some baseline risk factors (e.g., low birth weight, race, and source of payment), the model predicted a “permanent” 5.6 percent increase in VBAC rate attributable to the guidelines.
Lomas et al. 135 also compared average monthly change in rates of repeat CD in Ontario for 6 years before and two years after publication of guidelines recommending reductions in the rates of CD. The guidelines were a Canadian national consensus statement similar to the National Institutes of Health 1980 consensus conference in the US. The rates of repeat CD decreased at a higher rate after the guidelines than before. As these authors did not fully describe the other variables included in their regression model, this study was rated fair.
The study133 that provides the best evidence suggests that use of opinion leaders provides a greater likelihood of changing practice compared with audit and feedback. A recent conference summary142 echoed this view when it concluded that involvement of opinion leaders is an important step in achieving local buy-in for guidelines. Another study134 of peer review and audit failed to demonstrate a significant change in the rates of either VBAC or RCD. The other two studies135, 136 suggested that publications of national guidelines do impact practice although perhaps not to the degree expected.
Gregory et al.164 compared VBAC rates across hospital settings in California in a study that was rated good. Rates of VBAC (adjusted for baseline and medical characteristics of mother and fetus) were 14 percent in private nonteaching hospitals, 57 percent in public hospitals, 60 percent in private teaching hospitals, and 41 percent in health maintenance organizations (HMOs). When compared with private, nonteaching hospitals, the repeat CD rates in other types of hospitals was statistically significantly different (p < 0.001). The adjusted repeat CD rates were 85.7 percent in private, non-teaching hospitals (the reference group), 43.0 percent in public hospitals, 40.0 percent in private teaching hospitals and 59.0 percent in HMOs.
McMahon et al.5 compared rates of TOL and VBAC with type of hospital in Nova Scotia. Compared with tertiary care centers, the ORs for TOL rate were 0.5 (95 percent CI: 0.5 to 0.6) for regional hospitals and 0.4 (0.3 to 0.5) for community hospitals. The ORs for successful TOL were 0.7 (0.6 to 0.8 and 0.5 to 0.9, respectively) for both regional and community hospitals, compared with the tertiary care centers.
Stafford116 reported on relationships between several hospital characteristics and rates of VBAC. The study was rated good and represented all relevant discharges in California in 1986. Across hospital ownership types (compared with proprietary hospitals), the adjusted ORs for VBAC were (1.4; 95 percent CI, 1.2 to 1.6) for private nonprofit hospitals, 3.9 (3.3 to 4.6) for Kaiser Permanente hospitals with Kaiser payment, 2.6 (1.4 to 4.6) for Kaiser Permanente hospitals without Kaiser payment, 2.5 (2.1 to 2.9) for county hospitals with indigent payment, 2.7 (2.1 to 3.5) for county hospitals without indigent payment, and 3.7 (3.0 to 4.6) for the University of California hospitals. Compared to nonteaching hospitals, the adjusted ORs for VBAC were 0.7 (0.6 to 0.8), 0.9 (0.8 to 1.0), and 1.7 (1.5 to 1.9) for nonmedical-school-affiliated teaching hospitals, medical-school-affiliated hospitals, and Council of Teaching Hospitals member hospitals, respectively. Compared with a hospital without an NICU), the adjusted OR for VBAC for a hospital with an NICU was 0.9 (0.8 to 1.0). Across four categories of annual numbers of births, rates of VBAC increased with increasing numbers of annual births.
King and Lahiri115 assessed the impact of various hospital factors on the VBAC rates in New York hospitals in a study rated good. Compared with voluntary hospital ownership, church hospitals had a higher OR (1.13; 95 percent CI, 1.01 to 1.26) of VBAC compared with ERCD. The odds ratio was not significantly different from 1 (1.07; 95 percent CI, 0.95 to 1.21) if New York City hospitals were excluded. Government hospitals had a lower OR (0.77; 95 percent CI, 0.63 to 0.94) and this association did not change if New York City hospitals were excluded. Odds ratios increased with increasing levels of care from I (reference) to II (1.30, 95% CI: 1.18 to 1.44) to III (1.55; 95 percent CI, 1.34 to 1.81). The OR for teaching hospitals was 1.11 (0.99 to 1.24) compared with nonteaching hospitals although not significantly greater unless New York City hospitals were excluded (OR 1.36; 85 percent CI, 1.21 to 1.54).
Santerre136 evaluated various predictors for rates of VBAC in a panel of 55 hospitals in Massachusetts in a study rated fair. The authors were specifically interested in ACOG guidelines but they also controlled for other factors, including hospital characteristics. Their model estimated lower VBAC rates at hospitals with a higher proportion of low birth weight babies, hospitals with a higher percentage of Hispanic babies, and nonteaching hospitals. Volume of births, presence of neonatal ICU, ownership status, and urban location did not predict VBAC rate in their model.
Shiono et al.163 surveyed a random sample of US hospitals in a study rated fair. They reported rates of TOL adjusted for size of the delivery service (the stratification variable). Adjusted TOL rates were 12.5 percent and 6.5 percent in hospitals with and without NICUs, respectively. Rates for TOLs were 14.6 percent and 6.6 percent in hospitals with and without OB residency, respectively. Rates of TOLs and VBAC increased with increasing size of delivery service, but rates of successful TOLs were highest in hospitals with the smallest (less than 500) and largest (5,000 or more) number of annual deliveries.
The three descriptive studies29, 157, 162 of hospital characteristics were all rated fair. These evaluated VBAC in small rural hospitals. Raynor29 reported on the VBAC rate in a small rural hospital in North Carolina. The rate of TOL in 67 eligible patients was 76 percent and the rate of VBAC among these was 61 percent. Two uterine ruptures were reported in this study but neither was related to labor. Schimmel et al.162 reported on a nurse-midwife service in a rural county in California. Among 37 patients, the VBAC rate was 87 percent and no uterine ruptures were reported. While these studies are small, they provide some evidence of the success of VBAC in rural settings. The third descriptive study was conducted by Walton et al.157 at an isolated US military hospital in Japan. Of 62 patients, 79 percent agreed to a TOL but 14 failed to meet guidelines for VBAC. Of the remaining 32, 88 percent achieved a VBAC. No uterine ruptures were reported. These reports, while limited, suggest that VBAC might be safely attempted in small rural hospitals. However, the effects of an adverse outcome of a TOL in a small rural setting have yet to be defined.
The comparative studies suggest there are some differences among types of hospital ownership with respect to rates of VBAC. However, categorization of hospital types varied across studies makes comparisons across studies difficult. Gregory et al.61 reported higher rates of VBAC in public hospitals and private, non-teaching hospitals, and lower rates in private, non-teaching hospitals. Stafford116 found statistically significantly higher rates of VBAC in Kaiser-affiliated hospitals, county hospitals, and University of California hospitals, compared with proprietary and private, nonprofit hospitals. King115 found that, compared with voluntary ownership, rates of VBAC were statistically significantly higher in church-affiliated hospitals and lower in government-affiliated hospitals. McMahon et al.5 found statistically significantly lower ORs for VBAC in regional and community hospitals, compared with tertiary medical centers. Santerre136 found no statistically significant association of type of hospital ownership with VBAC rates. Thus, additional research is required to clarify this potential association.
With respect to hospitals with teaching programs, Gregory et al.61 found private teaching hospitals had statistically significantly higher rates of VBAC than private non-teaching hospitals. King and Lahiri115 estimated an statistically non-significant OR of 1.11 comparing VBAC and ERCD in teaching versus non-teaching hospitals. Stafford116 found the highest OR for VBAC versus ERCD at hospitals that were members of the Council of Teaching Hospitals but ORs for other teaching hospitals (whether or not they were affiliated with medical schools) were lower than for non-teaching hospitals. Santerre136 found a statistically significantly lower VBAC rate among non-teaching hospitals than teaching hospitals. Shiono et al.163 estimated that hospitals with OB residency programs had statistically significantly different rates VBAC rates about twice as high as those that did not. Thus, as with ownership above, some studies suggest that teaching hospitals have higher rates of VBAC than non-teaching hospitals, but the association does not hold across all categorizations of teaching versus nonteaching.
With respect to the association of an NICU with rates of VBAC, Shiono et al.163 estimated VBAC rates were about twice as high in hospitals with an NICU compared with hospitals without an NICU. Stafford116 found an OR of 0.9 comparing hospitals with an NICU with those without (for VBAC versus ERCD). Santerre136 found no significant association of the presence of an NICU with VBAC rate. Thus if there is an association of the presence of an NICU with VBAC rate, this association is not consistent across studies.
Across several hospital characteristics, there are no consistent associations with rate of VBAC. This might reflect lack of consistent definitions of categories across studies (e.g., types of hospital ownership), changes in these categorizations over time, a variation in the potential confounding variables that were controlled for in each study, or other factors.
As discussed in the patient preferences section, the decision between a TOL and ERCD is generally made prior to arrival at the hospital for delivery. Thus some hospital characteristics are likely to be confounded with other health care system characteristics (or patient or clinical status characteristics). In particular, providers affiliated with a particular type of hospital might exert much more influence on the decision for TOL or ERCD than the hospital itself. To the extent that a specific type of provider is associated with a particular type of hospital, there is a potential for confounding of provider type with hospital type. It is important to know the extent to which hospital characteristics influence the decision on mode of delivery, compared with other health care system characteristics, so that future interventions can be effectively targeted.
Stafford170 reported on a cohort of women who delivered in 1986 in California in a study rated good. Unadjusted rates of VBAC were 8.1 percent (95 percent CI, 7.6 percent to 8.6 percent) for private insurers, 8.3 percent (7.3 percent to 9.4 percent) for non-Kaiser HMOs, 9.4 percent (8.6 percent to 10.1 percent) for Medi-Cal (California Medicaid), 18.1 percent (16.3 percent to 19.9 percent) for self-pay, 19.9 percent (18.3 percent to 21.5 percent) for Kaiser Permanente, 24.8 percent (20.4 percent to 29.3 percent) for indigent services, and 17.1 percent (10.5 percent to 19.7 percent) for other payers. Stafford reported that the unadjusted rates were similar to rates stratified on three potential confounders and rates adjusted by logistic regression model but only reported unadjusted rates. Stafford116 reported adjusted ORs for the above cohort in another study rated good. The adjusted ORs for VBAC compared with ERCD (with private insurance as the reference) were 1.0 (95 percent CI, 0.8 to 1.1) for non-Kaiser HMO, 0.8 (0.8 to 0.9) for Medi-Cal, 1.7 (1.5 to 1.9) for self-pay, 3.9 (3.3 to 4.6) for Kaiser-Permanente with Kaiser payment, 2.6 (1.4 to 4.6) for Kaiser Permanente without Kaiser payment, 1.9 (1.0 to 3.6) for indigent services, and 1.3 (1.1 to 1.5) for other payers. All were significantly different from the reference except for nonKaiser HMO.
King and Lahiri115 compared VBAC rates and adjusted ORs (adjusted for baseline risk and potential confounders) for VBAC across four insurance types. There was little variation among VBAC rates (21 percent for Medicaid to 25 percent for HMOs) and only the OR between HMOs and private insurance was different from 1 (1.15, 95% CI: 1.02, 1.30). The authors provided results for the state of New York that both included and excluded data from New York City. If data from New York City were omitted, the previous OR would not be different from 1 (OR 1.03; 95% CI, 0.90 to 1.17) but the OR comparing self-pay with private insurance (1.28; 95% CI, 1.01 to 1.81) would differ significantly from 1 (this OR was not different with data from New York City included). These ORs are all close to 1.0 whether or not they are statistically significant, suggesting a weak relationship of insurance type with VBAC rate.
A multivariable regression model by Santerre136 showed no effect of payment source (private payer or public payer) on rates of VBAC. Thus, insurance type had no impact on VBAC rates after adjusting for other factors. Similarly, Gregory et al.164 found no difference in VBAC rates for a dichotomous payment source variable (private insurance: yes or no) in a multivariable regression model.
The association between types of insurance (or payer) and VBAC rates are inconsistent across studies. While data from 1986 in California showed substantially higher rates of VBAC with Kaiser Permanente coverage and, to a lesser extent, indigent services and self-pay, similar associations have not been seen in other studies. Thus, this result may have been unique with respect to state, year, and payor.
In summary, because many factors including patient characteristics, access to obstetric providers, practice variation among providers, training of providers, ability to perform a cesarean expeditiously, and hospital characteristics may all influence the likelihood of a patient to choose TOL and the safety of each choice, current studies have not been able to identify the conditions that increase risk of TOL or ERCD. While the various characteristics of health care systems have been discussed separately above, studies need to look across these characteristics to provide a complete picture and avoid potential confounding variables. For example, an analysis of type of provider might determine a lower rate of VBAC among midwives than among obstetricians. However, midwives might be more likely to provide obstetric care to women without insurance and women of lower education levels and socio-economic status, and might be more likely to work in clinical settings without around-the-clock availability of surgical and anesthetic services and might be subject to different legal restrictions. Given the large number of potential confounders, careful adjustment for these potential confounders needs to be performed. This will require large and detailed data sets with information on patients (both mother and newborn), hospital, and provider.
Studies of legislation, policy, guidelines, hospital characteristics, provider characteristics, insurance type or access to care focus exclusively on VBAC rates rather than safety.
There are no studies regarding the impact of the current malpractice crisis on availability of obstetric providers and impact on a patient's options.
Studies of provider characteristics failed to control for important confounders such as patient selection bias.
Studies of hospital characteristics consistently report higher VBAC rates for teaching hospitals, but they conflict on whether having a NICU affects rates.
The association between insurance status and VBAC rates is inconsistent among studies
Current studies have not controlled for confounding for factors such as patient selection bias, as such, they have not identified conditions or practice management styles that increase risk of TOL or ERCD.
This report found that there were no high quality data providing definitive answers for decisionmaking about future childbirth following cesarean delivery, one of the most commonly performed surgical procedures in the U.S. (affecting up to 640,000 women each year).
The following summarizes the type of study design, the quality of the evidence from studies, and the suitability of the study design to answer the particular question for each key question.
| Key Question | Study Type* | Quality of Evidence | Suitability of Study Design† |
|---|---|---|---|
| Question 1 | |||
| What is the frequency of VD in those who undergo a TOL (SL, I, and A) after prior LTC or unknown scar? | II-2 | Fair-Good: Several large prospective and retrospective studies; mostly consistent findings. | Greatest |
| Question 2 | |||
| How do risk assessment tools identify who will have a VD after a TOL? | |||
| Predictive tools | II-2 | Fair-Good: Large cohort studies suggest tools can provide additional data predicting likelihood of (VD). | Greatest |
| Imaging modalities | I | Good: RCT demonstrated that imaging was ineffective to predict VD. | Greatest |
| Question 3 | |||
| What are relative harms associated with TOL(SL,I and A) and repeat cesarean? | II-2 | Fair-Poor: Many large cohort studies inconsistently defined outcomes. | Moderate |
| Maternal Death | Fair: Studies consistently found no maternal death risk increase from TOL versus ERCD. | Least | |
| Hysterectomy | Fair-Poor: Many studies failed to report indication for hysterectomy. | Moderate | |
| Transfusion | Fair: Two studies consistently found slightly increased risk for transfusion in TOL although not significant in one. | Moderate | |
| Infection | Poor: Definitions inconsistent. | Moderate | |
| Incontinence/Pelvic Floor | No studies. | Moderate | |
| Infant Death | Poor: Most studies found increased risk of perinatal death for TOL versus ERCD, yet magnitude varied greatly. | Least | |
| Neurologic impairment | Poor: Few studies of poor quality. | Least | |
| Respiratory impairment | No studies. | Moderate | |
| Question 4 | |||
| What is the incidence of uterine rupture of cesarean scar, and are there methods for preventing poor clinical outcomes? | |||
| Incidence | II-2 | Fair-Poor: Several large cohort studies inconsistent in terminology; many with consistent findings of increased risk of symptomatic UR in TOL vs ERCD. | Moderate |
| Methods for preventing poor outcomes | II-3 | Poor: Few studies, variation in case definition. Fetal bradycardia frequently associated with UR; inclusion of fetal tracing findings in definition of UR makes assessing true value difficult. | Least |
| Question 5 | |||
| What are the health status and health-related quality of life for VBAC and repeat cesarean patients? | None | No studies of women with prior CD. | NA |
| Question 6 | |||
| Regarding VBAC and ERCD,what influences patient satisfaction/ dissatisfaction with the birth experience? | III | Fair: Two cross-sectional studies with varied findings. | Least |
| Question 7 | |||
| How are economic outcomes related to VBAC, repeat CD, and their respective complications? | Econ | Fair-Good: One good economic model suggests VBAC cost-effective, provides higher quality of life when chance of VD is 76 percent or greater. | Greatest |
| Question 8 | |||
| What individual factors influence route of delivery? | II-2 | Fair-Poor: Several retrospective cohort studies conducted; all vary in items considered, each with limited adjustment for confounders. | Moderate |
| Question 9 | |||
| What factors influence a patient's decision making regarding VBAC or ERCD? | I, II, III | Fair: One good RCT and eight fair quality cohort or cross-sectional studies found women who preferred TOL more likely to be White, value process of labor, value social motives such as ease of recovery. | Moderate |
| Question 10 | |||
| How do legislation, policy, guidelines, provider characteristics, insurance type, and access to care affect health outcomes for VBAC candidates? | |||
| Legislation | II-3 | Poor: Few studies only examined impact on VBAC rates, not safety. None examined malpractice rate crisis' impact on access or safety. | Moderate |
| Guidelines | I, II | Fair-Good: Several studies consistently found the provision of guidelines especially with recommendations of opinion leaders increased VBAC rates; no studies on safety. | Moderate |
| Provider Characteristics | II | Poor: Several studies, none of which adjusted for differences in baseline risk or potential confounders. | Moderate |
| Hospital | II | Fair: Consistently found teaching hospitals had higher VBAC rates; no comparisons for safety. | Moderate |
| Insurance | II | Fair: Several studies with conflicting findings. | Moderate |
Study design categories—I: randomized, controlled trials; II-1: controlled trials without randomization; II-2: cohort or case-control; II-3: multiple time series; III: opinions, descriptive epidemiology. U.S. Preventive Services Task Force (1996).
Suitability of study design categories—Greatest: For comparison studies: Concurrent comparison groups and prospective measurement of exposure and outcome; For rates: population-based or multicenter prospective cohort studies. Moderate: All retrospective designs or multiple pre or post measurements but no concurrent comparison group; Least: Single pre and post measurements, no concurrent comparison group or exposure, outcome measured in a single group at the same point in time. Community Preventive Services Task Force (2000).
What is the frequency of vaginal delivery in women who undergo a TOL (spontaneous onset, induced or augmented) after prior low transverse cesarean or unknown scar?
Rates of vaginal delivery for women attempting TOL ranged from 60 to 82 percent. The largest population-based study reported a rate of 60.4 percent. These data may be the best reflection for vaginal delivery rates for the general population who attempt a TOL with low transverse scar across a diversity of settings of care and practice management. The combined vaginal delivery rate for all prospective cohort studies, largely conducted in university and tertiary care settings, was 75.9 percent. Further studies that investigate the true prevalence of vaginal delivery, accounting for practice variation, are needed.
There was a 10 percent reduction in the likelihood of vaginal delivery when oxytocin was used for ether induction or augmentation. There was a similar trend in reduced likelihood of vaginal delivery with prostaglandins. Most studies did not report rates for patients requiring medical augmentation or induction of labor separately from patients undergoing spontaneous labor. Furthermore, studies that did report separate rates, were not able to account for the contribution of reason for augmentation or induction, nor the impact of practice variation. Leaving insufficient data to determine the effect of medical induction and augmentation of labor.
How accurate are risk assessment tools for identifying patients who will have a vaginal delivery after trial of labor?
In considering whether to attempt a TOL or ERCD, patients, clinicians, payors, and policy-makers are confronted with the dilemma of weighing the likelihood of probabilities for vaginal delivery and health outcomes for each option.
Two validated scoring systems were identified.36, 40 These two scoring systems shared the design of incorporating various predictive factors available at a patient's admission, similar study patient exclusion criteria (e.g., classical or low vertical incision, multiple gestations, and malpresentation), and a roughly similar range of predicted vaginal delivery probabilities of 45 to 95 percent. In addition to these similarities, the two scoring systems also shared several limitations. First, both scoring systems were based on preselected populations of patients who were willing to attempt a TOL. Because of this design, both studies are affected by verification or workup bias, where the results are relatively distorted by the fact that not everyone who is eligible for a TOL is included in the study (e.g., the patient who is eligible for a TOL, but decides to have a ERCD is not incorporated into the study and not used for the creation of the scoring system). Another common limitation is that these scoring systems were created and validated for use at the time of admission, thus invalidating the application of the scoring systems at any other point during the pregnancy. For example, Flamm stated that because cervical dilation and effacement often change dramatically between the last prenatal examination and the time of admission, the use of his scoring system before the onset of labor would yield an incorrect prediction. The last common limitation stems from the included predicting variables themselves such as accuracy of a patient's past obstetric history (e.g., indication of a prior CD) if the medical record is not available, and the variable and subjective in nature of cervical dilation and effacement. The lack of accurate past obstetric data or the variability of various clinical findings between providers could potentially affect the precision of the predicted results.
However, beyond these similarities lie several differences that make the Flamm scoring system a relatively better predictive tool. First of all, Flamm's scoring system was developed prospectively and with a considerably larger sample size, compared with the Troyer scoring system (2,502 and 264, respectively). Flamm's scoring system can also be said to be more precise and accurate, in that the point values assigned to each of the included variables were based on the Beta coefficients of the logistic regression model. This system, which was not employed by Troyer, takes into account the relative predictive weights for each variable, while controlling for any possible confounding distortion. The use of a 10-point scoring system by Flamm also increases the accuracy and precision of his system by allowing for a more exact prediction of the probability of success, relative to Troyer's four-point scoring system. The value of a scoring system depends on its ability to accurately stratify patients into high and low-risk groups with low false positive or negative rates. In the case of TOL, an ideal tool would stratify all women eligible for a trial of labor into those with high and low likelihoods of vaginal delivery, with minimal false positives. The tool should minimize the number of patients predicted to be at high chance for vaginal delivery that actually have to have a cesarean after a lengthy trial of labor (false positives), because it is this group that has the highest risk to sustain complications of TOL such as uterine rupture. Flamm's test was able to provide additional information to slightly under one-half of the population tested, with a relatively low false positive rate of 2.6 percent. In order to know whether this tool is effective, it needs to be tested in different populations with differing baseline VBAC rates, and ideally tested in all eligible women rather than just those who already chose TOL.
Of the seven imaging studies identified, only one received a good quality rating.47 Although this RCT was similar to the other studies, in that it lacked any statistical adjustment for confounding, its randomization of subjects presumably allowed for control of confounding through study design. The finding that 60 percent (33/55) of those considered to have an inadequate pelvis by postpartum XRP had a vaginal delivery, compared with the 30 percent (27/89) of those considered to have an adequate pelvis by postpartum XRP, provides support for the conclusion that XRP is a poor predictor of TOL outcome and might unnecessarily increase CD rates.
What are the relative harms associated with a TOL (spontaneous onset, induced, augmented) and repeat cesarean?
There is no direct evidence comparing the risks and benefits of TOL relative to ERCD in similar patients. Several fair and good quality cohort studies provide indirect evidence about the relative benefits and harms associated with each route. Their findings are itemized below:
Maternal death rates did not differ between TOL and ERCD.
The best evidence suggests that hysterectomy rates do not differ between TOL and ERCD.5
Rates of infection were increased in ERCD versus TOL (8.6 to 9.73 percent versus 6.6 to 6.79 percent).5, 24
Studies that performed subgroup analyses for TOL with and without vaginal delivery consistently reported that rates of infection were significantly higher in women who had a TOL but ultimately had a cesarean delivery.
There is conflicting evidence regarding whether induction of labor had any effect on infection rates.
There is insufficient evidence regarding the effect of TOL and ERCD on APGAR score and respiratory morbidity.
No study measured infant death directly attributable to a mother's choice of TOL or repeat CD.
Two large population-based studies report increased risk of perinatal death associated with TOL, but they differ in the magnitude of risk.(90/10,000 TOL versus 50/10,000 ERCD5 compared with 12.9/10,000 TOL versus 1.1/10,000 ERCD.6)
Methodologic deficiencies in the literature are striking. Comparisons across studies were hampered by lack of standards for reporting severity of disease or condition, and inconsistencies in definitions of outcomes. Studies often did not pay close attention to comparability of groups, specifically, the ERCD group was often not ensured to be otherwise eligible for TOL. Other factors such as parity, type and number of previous cesarean, were often not considered.
Studies did not pay close attention to and account for the importance of co-interventions such as use of oxytocin and other medical agents for augmentation or induction of labor.
Most importantly, variations in reporting of important clinical outcomes such as hysterectomy, infection, maternal mortality, and perinatal mortality made it difficult to determine true probability of outcomes, potential preventive measures, or outcomes that were directly attributable to route of delivery or labor management. Lack of precision made it difficult to determine whether the rates truly represented risk of clinically significant outcomes or significant misclassification or confounding.
There were no studies of the long-term consequences of TOL versus ERCD such as incontinence, pelvic support disorders, or infant sequelae from neurologic or respiratory disorders.
What is the incidence of uterine rupture, and are there methods for preventing major morbidity and mortality due to uterine rupture?
Studies varied in their use of terms to describe the spectrum (e.g., asymptomatic, symptomatic, clinically significant) of uterine rupture of the cesarean scar. Our best attempt to separate the groups in a meaningful way found that there was no difference in rates of asymptomatic uterine rupture (dehiscence) between TOL and ERCD. There was a significant increase in the occurrence of symptomatic uterine ruptures in TOL. Specifically, for every 10,000 women attempting TOL there would be 27 additional symptomatic uterine ruptures. Based on the frequency and severity of symptomatic rupture, for every 10,000 women undergoing a trial of labor, there would be 1.5 uterine rupture related perinatal deaths and 4.8 rupture related hysterectomies.
Lack of precise definitions also prevents the ability to determine the value of certain premonitory signs. Because the definition of uterine rupture frequently includes ruptures discovered when cesarean is performed for fetal heart tracing disturbances, it is not possible to determine the accuracy of fetal tracing as a premonitory sign.
What are the health status and health-related quality of life for VBAC and repeat cesarean patients?
No studies provide information on health status or health-related quality of life, related to TOL versus ERCD.
Regarding VBAC and repeat cesarean, what factors influence patient satisfaction/ dissatisfaction with their childbirth experience?
It is important not only to consider the health outcomes for TOL and VBAC, but also whether patients are satisfied with their childbirth experience. Only two fair cross-sectional studies provided results on satisfaction for women attempting VBAC or ERCD. Other studies allowed the patient's provider to measure satisfaction, introducing the possibility of measurement bias.
Discussion of economic evaluations. The use of cost per QALY from a societal perspective as an economic outcome to compare health care delivery options is recommended by current guidelines.100 While there is no single threshold value for cost per QALY in the US, the upper limit of cost effectiveness of $50,000 per QALY used by Chung et al. is a reasonable limit for the US health care system.87 This limit can reflect one extra QALY at a cost of $50,000 or 50 extra QALYs at a cost of $1,000 per QALY. A value of $50,000 per QALY is slightly less than the cost per QALY for treatment guided by routine coronary angiography compared with initial medical therapy without angiography, or use of driver-side and passenger-side airbags compared with driver-side air bags alone.174
The use of QALYs as an economic outcome for methods of delivery means that both the mother and the newborn contribute QALYs to the analysis. It seems appropriate that both maternal and newborn QALYs should be counted, as both are outcomes influenced by the decision on mode of delivery. Economists typically do not differentiate QALYs on the basis of the age of the person receiving the QALY. That is, a QALY is counted the same for a senior age 80 as for a child age 5. Thus, a comparison between a childhood vaccination program and hip replacement surgery is facilitated by using cost per QALY.
Additional analyses using the model of Chung et al.87 would be useful. The authors could have performed two-way sensitivity analyses with each of the other sensitive variables listed above and TOL success probability to determine how sensitive these results are to two variables at once. For example, if an increase of 0.5 percent in the probability of cesarean rupture were to shift the decision point from 74 to 80 percent, then both of these two factors would need to be predicted to determine which delivery option was more efficient. That is, the results might be sensitive to more than one variable at a time. One problem with the recommendations of this study based on TOL success rate is that the recommendations ignored the imprecision of the estimated TOL success rate. If the TOL probability of success were 72 percent or 76 percent with a prediction error of +/- 4 percent (e.g., a CI for the prediction of 68 percent to 76 percent for a TOL success rate of 72 percent), the prediction interval would include the decision cut point of 74 percent. This means that the prediction does not select an efficient option in this case. A Monte Carlo simulation analysis that would allow introduction of random variation into the model of Chung et al. could help to evaluate the effect of uncertainty in the prediction parameter. For example, instead of using a predicted probability on TOL success, one could use the expected probability and the standard error around the probability to generate a sample of individuals, determine the experience of these individuals, and estimate the resulting cost per QALY. Another concern is the inclusion of fecal and urinary incontinence during the first year after birth in the model of Chung et al. As summarized elsewhere in this report, the evidence for a higher rate of these adverse events in TOL than ERCD is inconclusive. The authors should have included no additional cases of incontinence in the sensitivity analyses.
The valuation of different costs in these economic evaluations needs review. There are a number of costs associated with TOL and ERCD that are very difficult to measure. These events include, but are not limited to, cerebral palsy, loss of fertility after a hysterectomy, or death of the mother or of the newborn. These events have substantial societal costs that might be problematic to measure. To the extent these events are not properly valued in the above analyses, the analyses are potentially biased. The use of a broad range of sensitivity values might address this concern to some extent. With respect to major neonatal adverse events such as cerebral palsy, the costs include more than direct medical costs. The societal costs (e.g., long-term care, special education, lost productivity, and legal costs) of a major neonatal adverse event might be substantially higher than the direct medical costs. For example, the productivity lost for a newborn with a cognitive deficit could be substantial from a societal perspective. However, these societal costs were not included in the model of Grobman et al.88 Cerebral palsy after uterine rupture had the highest cost in this model (base case about $180,000) but occurred with very low probability. Maternal and neonatal deaths were not explicitly valued except in sensitivity analyses and then with a relatively small value ($100,000), because of the payer or provider perspective. While it is likely that these probabilities change with each subsequent pregnancy (e.g., a successful TOL indicates a higher probability of success for future TOLs).107 Another problem with costs is the true cost of the perinatal period (including times associated with labor and delivery for a TOL and with surgical processes for RCD). Chung et al. used charges for these costs; charges might not reflect actual time spent in labor and delivery or in surgery. More detailed studies that evaluate these times for series of patients would improve these models. These details are as important as LOS (see next section on health care resources below) for an accurate estimate of total costs.
The model of Chung et al.87 also considers only one pregnancy. The model of Grobman et al.88 did include more than one pregnancy after an initial CD. In this latter model, probabilities for each subsequent pregnancy appear to be the same as for the index pregnancy. Some women might be expected to have additional pregnancies and each pregnancy and the modes of delivery in the previous pregnancies are likely to modify the probabilities for subsequent pregnancies. For example, a repeat CD might increase the risk of other adverse events if a TOL is considered for the next pregnancy. Similarly, a successful VBAC means that a woman is more likely to have a TOL end in VBAC for subsequent pregnancies. While the data for subsequent pregnancies might be somewhat limited, the impact on future pregnancies is important.
In summary, the model of Chung et al.87 provided the best evidence of the relative value of TOL and ERCD, and suggested that the cost-effectiveness of TOL versus ERCD depends strongly on the probability of successful VBAC after a TOL. If this probability is “high,” VBAC is more cost-effective, while if this probability is “low,” ERCD is more cost-effective. Additional research is needed before precise values of high and low in the above can be assigned. Also there is likely a range of probabilities between the high and low values in which the cost-effectiveness might be indeterminate. The discussion above describes some additional analyses using the model of Chung et al. that might address some of these issues raised. However, other concerns, especially achieving a prediction tool of the desired precision, might be problematic. A second model by Grobman et al.88 provided only fair evidence, from a payer perspective, of the medical costs of TOL versus ERCD. Thus, Grobman et al. do not provide conclusive evidence of the value of VBAC over ERCD.
All studies were rated poor, mainly for lack of adjustment for potential confounding variables.
What individual factors influence route of delivery?
This review identified 96 studies that met the requirements for inclusion. However, upon further review, 83 of these studies were considered of poor quality and were subsequently removed from the analysis. The most common reason that studies were rated poor was due to lack of adjustment for important confounders. While many studies commented on the extensive list of factors that influence the outcome of TOL, very few studies actually considered those factors when conducting their analyses. Instead of stratifying their analysis or running multivariate models (e.g., logistic regression), studies often provided only bivariate analyses (i.e., Chi-square, Fisher exact, or t-tests). By neglecting to control for confounding, the measures of association provided by these studies might be distortions of the true association and hence should be interpreted with caution.
Overall there was an increased likelihood of vaginal delivery for women who had a prior vaginal delivery (particularly VD after cesarean), maternal age less than 40 years, a nonrecurrent indication for one's prior CD, and favorable cervical assessment. There was a decreased likelihood of vaginal delivery for women with an increased number of prior CDs, gestational age greater than 40 weeks, birth weight greater than 4000 grams, and augmentation of labor. Although all of these significant findings come from good to fair quality studies, it is important to remember that some of these factors do in fact vary between individual health care providers. For example, the cervical examination performed by one provider may differ from the exam of another or in another instance; the decision to augment a labor and how aggressively this approach should be applied may also be dramatically different between providers. In any case, these inter-provider variations may have not only affected the obtained results and perceived associations, and also has possible implications in the use of such knowledge in the clinical realm.
What factors influence a patient's decisionmaking regarding VBAC or ERCD?
A woman's choice for delivery was often based on social motives (e.g., easier recovery so she can care for her baby and children at home). Only four of 11 studies cited safety of the mother or bay as important reasons for delivery choice. It remains unclear if VBAC education increases the proportion of women who choose TOL. Future studies should include education, ideally before next pregnancy.
How do legislation, policy, guidelines, provider characteristics, insurance type, and access to care affect health outcomes for VBAC candidates?
One of the things a decisionmaker would want to know in deciding between TOL and ERCD is what conditions of care including practice management, training of the provider, and hospital characteristics increase the risks of each choice. There were no high quality data for this issue, in fact, studies of these factors exclusively examined VBAC rates rather than the safety of each choice.
No study provided direct evidence for the impact of rising malpractice rates on VBAC or ERCD. Two studies were identified that provided any data regarding legal and/or legislative effects. One study in Florida found a significant difference in VBAC rates before and after enactment of statewide legislation emphasizing dissemination and peer-review enforcement of guidelines. Analysis failed to consider underlying time trend in VBAC rates independent of legislation. Another study in New York found small changes (ORs between 0.95 and 1.0) in probability of VBAC for either hospital-paid loss due to malpractice claims or $5,000 increase in annual physician insurance premium increase. No other studies of the effects of increasing insurance premiums were identified.
A randomized trial133 demonstrated that opinion leaders are able to modify provider behavior to a greater extent than audit and peer review.
A second randomized trial134 failed to show a significant change in response to audit and peer review.
Two retrospective cohort studies135, 136 used data over time to show increases in VBAC rates in response to national VBAC guidelines.
Provider characteristics such as training to perform a cesarean, clinical volume, and management characteristics may affect outcomes of TOL and ERCD. Though these may be important factors, no studies that examined these factors, controlled for important confounders such as patient selection bias. Thus, there is no evidence as which if any of these factors may increase risk.
Most studies of the effect of teaching hospitals found that teaching hospitals had higher VBAC rates.
Studies disagreed whether the presence of a NICU in the hospital affected VBAC rates
In small rural hospitals, three studies of small case series found VBAC success rates of 67 to 88 percent with no serious adverse events. More extensive experience might modify this result.
There were conflicting data regarding the impact of types of health insurance on VBAC rates.
It is clear from this report, that the literature about TOL and ERCD is significantly flawed.
One of the highest priorities for future research should be the development of standardized reporting measures of disease severity and outcomes of delivery. For example, standardized reporting of disease/condition severity especially for conditions with devastating consequences such as uterine rupture, and precise definitions for important health outcomes, such as delineation between outcome and predictor such as fetal tracing findings and clinically significant uterine rupture, to enable identification of important for premonitory predictors.
Studies also need to be consistent in the definition of their conceptual cohort. In comparing TOL to ERCD, it is important to ensure that the ERCD group would have been eligible for a TOL.
Future studies of tools to predict likelihood of vaginal delivery need to be tested in populations with varying baseline risk and also add considerations for the consequences of prediction such as the likelihood of clinically significant uterine rupture from a false positive test.
Patients make decisions by a complex process weighing social ramifications and values in parallel with probabilities of health risks. Therefore, future studies should focus on accurately measuring this important dimension of childbirth decisionmaking.
Patients make decisions based on short and long-term consequences of their choices. Therefore, further research needs to focus on long-term health outcomes such as pelvic floor dysfunction, incontinence, or the long-term repercussions of neonatal conditions such as neurologic and respiratory conditions.
In order to consider long-term consequences and quality of life, studies need to use appropriate long-term methods such as survival analysis and studies that use QALYs need to be able to delineate maternal and neonatal consequences separately and in present data in a meaningful way.
Factor such as malpractice coverage, and insurance variation, limit patients’ ability to choose. No data was available for this very real determinant. Future studies are needed to examine the impact of factors such as the malpractice crisis and malpractice reform on choices available and outcomes from TOL and ERCD.
Future studies of vaginal delivery rates in TOL, should evaluate the impact of labor management strategies such as induction of labor on likelihood of success.
Studies examining the factors that may explain why vaginal delivery rates differ in some study populations are needed.
Studies with the objective of creating a predictive tool should attempt to use a prospective study design, avoid workup or verification bias (i.e., try to incorporate all of those who are eligible for a TOL into the study, instead of only those who decide on that route of delivery), and specify the reproducibility and generalizability of the predictive tools by validating it in another distinct population.
Although the avoidance of workup or verification bias might be difficult if not impossible to do, one can minimize this bias by maximizing the percentage of those eligible for a TOL that actually attempt a TOL.
By weighting the contribution of each variable and adjusting for confounding distortion, the use of a point system based on Beta coefficients and logistic regression modeling might provide more accurate and precise estimates of the probability of vaginal delivery.
To date, the two best scoring systems are by Flamm and Troyer. Each of these scoring systems could benefit from further validation studies (e.g., using a non-HMO study population with the Flamm scoring system, and using a prospectively designed validation study with the Troyer scoring system).
Future research should focus on conducting methodologically rigorous studies to provide direct evidence regarding the relative benefits and harms of trial of labor and ERCD. If randomized trials are not done, good-quality studies of TOL versus ERCD must pay attention to the following:
Population - Studies should be conducted in populations of women who are similar in every respect except choice of delivery route (comparability of groups).
Specificity of Intervention - Studies should pay close attention to and account for the importance of co-interventions such as use of oxytocin and other medical agents for augmentation or induction of labor.
Precise and Standard Outcome Measures Variations in reporting of important clinical outcomes were striking. Studies should consider the following factors in developing outcome measures:
Etiology - Outcomes such as hysterectomy, infection, maternal mortality, perinatal mortality must pay specific attention to explicitly identifying the etiology. Lack of precision in this regard allows for both under and over- reporting of cases due to misclassification. Examples include whether hysterectomy was performed due to maternal hemorrhage secondary to clinically significant uterine rupture versus hemorrhage due to abruption, uterine rupture through the uterine fundus in a woman with a low transverse incision either due to trauma or other non-incisional causes, and perinatal death due to lethal anomaly versus intolerance or management of labor.
Standard Terminology - In order to accurately measure outcomes, there must be a consistent terminology. Lack of this, prevents accurate and meaningful comparisons of risks for each delivery choice. Outcomes such as infection, hemorrhage, and uterine rupture were not consistently defined.
Separating prevention/prediction strategies from outcomes- As long as potentially important predictors of events such as prolonged fetal bradycardia as a predictor for clinically significant uterine rupture are included in the definition of uterine rupture, their true value as a predictor rather than a confounder will remain unknown.
Future studies need to use standard terminology for uterine rupture. Motivated by this need, we convened a conference call of national experts including representatives from the American College of Obstetricians and Gynecologists, American Academy of Family Physicians, Centers for Disease Control and Prevention, National Institutes of Health, and investigators from major VBAC studies to begin terminology discussions. The group proposed terminology based on anatomic findings. The term complete uterine rupture of a cesarean scar would be used to indicate a separation of all layers of the uterine wall including serosa. Incomplete rupture of a cesarean scar would be used to indicate a defect that did not extend through the entire thickness of the uterine wall (e.g. serosa intact). This latter term would include what are often referred to as uterine windows. Details are provided in Appendix G.
Studies should be explicit in reporting uterine rupture related health outcomes. Inconsistencies in reporting health outcomes such as perinatal death, maternal death, and hysterectomy attributable to uterine rupture, limits our ability to fully appreciate the significance of this condition.
Every effort should be made in future research studies to separate important predictors from the definition of uterine rupture. Failure to do so limits the ability to determine the value of factors such as fetal bradycardia as a predictor of risk.
Fetal bradycardia should be further explored as an important predictor of uterine rupture by use of a control group and reporting all instances of fetal bradycardia that occur in patients undergoing a TOL and the frequency of finding uterine rupture for this signal.
Attention to development of a tool focused on maternal health that includes a woman's ability to care for her infant.
Measurement of maternal and infant health status that measures these outcomes longitudinally over time.
Documentation of delivery process (e.g., TOL followed by repeat CD, VBAC, or ERCD) as it relates to health status.
Measurement and comparison of satisfaction as it relates to all delivery processes (TOL followed by repeat CD, VBAC, repeat CD).
Ascertainment of the level of information provided to the patient and the level of involvement in decisionmaking. A future trial could test the effect on patient satisfaction and/or other psychosocial outcomes of the use of various approaches to providing information and involving the women in decisions. Intervention patients in these trials might receive packets that include videos, pamphlets, access to a computerized decision aid, etc., covering the risks, benefits, and realities of recovery from either TOL or ERCD. Intervention patients would also be given many opportunities to become involved in the decisionmaking.
Ascertainment of true cost data. Data on costs (rather than charges) is sparse in the literature relating to these two alternatives. The costs of labor and delivery and of the surgical processes are poorly understood. Detailed time-in-motion studies would help to estimate these costs. The costs of specific health outcomes (as adverse events) are also poorly understood. This is especially true for outcomes that might have long-term societal costs such as special education and lost productivity for severe adverse neonatal outcomes, and lost productivity for maternal deaths. Economic evaluations need to estimate these costs in a better way and to include these long-term costs in models. Once costs are available, economic evaluations need to assume a societal perspective, use QALYs as a summary outcome measure, allow for two or more pregnancies after an initial CD, and include all adverse outcomes and associated long-term costs of these outcomes.
First of all, there is a need for studies to consider certain factors such as maternal race, spontaneous and induced labor, oxytocin use, and nonclinical factors (i.e., the nonitalicized factors in the above table). Previous studies of these factors have demonstrated their influence on the outcome of TOL; however, the lack of adjustment for potential confounders makes the interpretation of these associations less valid.
Second, there is the question of which study design best addresses this issue. Although database studies easily allow for large sample sizes (and hence the power to detect differences), they are often limited by the lack of individual patient data and thus the ability to control for confounding. While retrospective cohorts usually allow for the adjustment of confounders using individual patient data, they are limited by the availability and validity of previously collected data. Overall, it appears that the prospective cohort design allows the best opportunity to address the issue of predictive factors. Although expensive and time-consuming, this design allows one to collect the information desired, in a manner that improves the validity of the results.
Third and perhaps most important, there is an overwhelming lack of adjustment for confounding in the literature. Evaluation of the fair-to-good-quality studies showed that certain factors had a significant influence over the outcome of a TOL; these factors include but are not limited to: prior VD, order of prior VD (especially vaginal delivery after prior CD), cervical dilation, cervical effacement, and Bishop's score. This finding only strengthens the importance of considering these other factors when conducting research and making clinical decisions.
Develop an instrument to measure a women's preferences for birth. The instrument should include preferences related to both risk and social motives.
It remains unclear if VBAC education increases the proportion of women who choose TOL. Future studies of education should include education before next pregnancy, perhaps at the postnatal visit of patients with first CD.
Future research on units of health care resources should address more than LOS. Other important units of resources include time spent in labor and delivery and time spent in steps in the surgical process. Resources associated with serious adverse events also need to be estimated (e.g., special education after severe neonatal outcomes).
Research involving units of health care resources (e.g., LOS) should either compare TOL and ERCD at similar baseline risk or perform careful adjustment for baseline risk factors and other confounding variables. Otherwise comparisons of these resources suffer potential biases.
If more detailed economic evaluations are conducted (i.e., that go beyond the total patient charge), the units of health care resources should be identified as part of that study. Further, the trade-offs between all the other economic outcomes (beyond LOS) will require full economic analyses to compare difference units of resources appropriately.
Across legal or legislative factors, guidelines, provider characteristics, hospital characteristics, and types of insurance or payments, there are several general future research needs. Research needs specific to one of these are presented after the general needs.
Studies must either focus on a relatively homogeneous low-risk patient to compare across providers or to adjust analyses carefully for baseline risk and other potential confounding variables, to make sure comparisons among levels of characteristics are valid.
Studies also need to include as many potential predictors and potential confounders as possible. While this review has separated these health care system characteristics for ease of discussion, proper evaluation should include all of these. That is, a hospital characteristic might be a potential confounder for insurance type.
Complete evaluation of all of these health care system characteristics in a single set of analyses will require consortium level research. That is, only if large, complete data sets are assembled from multiple sources (including hospitals, insurers, and physicians) will research to address all of these diverse characteristics be possible.
For future research on the impact of legal and legislative characteristics on the choice of mode of delivery, studies need to be long term, collect adequate data on potential confounders, and estimate any underlying time trend independent of the intervention.
Guidelines, especially as championed by an opinion leader, have been demonstrated to effectively modify provider behavior (e.g., to increase rates of VBAC). Other approaches (e.g., peer review and audit) have not demonstrated a clear impact on changing VABC rates. Further research into alternative systems of rewards (e.g., bonus payments for a successful VBAC in patients who meet guidelines) and or punishments (e.g., including VBAC rate as a quality index) might also warrant additional research.
Studies looking at provider characteristics need to adjust for baseline differences in risk and other potential confounding variables.
Also, for provider (and hospital) characteristics, the analysis must match the sampling design. Specifically, patients are attended by physicians and deliver at specific hospitals. The clustered nature of this relationship (patient nested and clinician nested within one or two hospitals) needs to be reflected in the statistical analyses employed.
With respect to hospital characteristics, future studies need to make definitions of different characteristics as clear as possible. This is especially important, as some hospital characteristics are potentially confounded with one another. For example, hospitals that have high levels of care, have NICUs, are teaching hospitals, and have large numbers of deliveries might be the same small set of hospitals. That is, particular hospital characteristics might occur as groups and not as independent factors.
A relationship between insurance type and rates of VBAC has not been demonstrated. However, to the extent that VBAC rate is becoming a quality measure, additional research on this particular association might not be warranted. If rate of VBAC becomes a widely used quality measure, there will likely be no association with type of insurance.
Malpractice insurance premiums may also influence the decision on mode of delivery for women with prior CD. Increasing rates of malpractice insurance might lead some providers either to not provide any delivery services or to choose a mode of delivery perceived to be less risky for mother and/or child. Careful evaluations of rates of VBAC and ERCD across time (before and after changes in premiums) and across geographic regions (one or more in which changes in premiums were large and one or more in which changes in premiums were small) would allow appropriate comparisons to be made. That is, the changes in rates in the geographic region(s) in which the premiums were high could be compared with rates in the region(s) in which premiums were low. Inclusion of potential confounders including patient-level risk factors would need to be included in any such study.
Principal Investigator
Jeanne-Marie Guise, MD, MPH
Assistant Professor of Obstetrics and Gynecology and of Medical Informatics and Outcomes Research
Oregon Health & Science University
EPC Director
Mark Helfand, MD, MPH
Associate Professor of Medicine and Medical Informatics & Outcomes Research
Oregon Health & Science University
Co-investigator
Michelle Berlin, MD, MPH
Associate Professor of Obstetrics and Gynecology and Medical Informatics and Outcomes Research
Oregon Health & Science University
Co-investigator
Karen Eden, PhD
Assistant Professor of Medical Informatics & Outcomes Research
Oregon Health & Science University
Co-investigator
Dale Kraemer, PhD
Assistant Professor of Medical Informatics & Outcomes Research
Oregon Health and Science University
Co-investigator
Marian McDonagh, PharmD
Clinical Research Pharmacist
Center for Health Research
Kaiser Permanente
Co-Investigator
Jason Hashima, BS
Division of Medical Informatics & Outcomes Research
Oregon Health & Science University
EPC Administrator
Kathryn Pyle Krages, AMLS, MA
Division of Medical Informatics & Outcomes Research
Oregon Health & Science University
Research Coordinator
Peggy Nygren, MA
Division of Medical Informatics & Outcomes Research
Oregon Health & Science University
Co-Coordinator
Patricia Osterweil, BS
Division of Medical Informatics & Outcomes Research
Oregon Health & Science University
Librarian
Patty Davies, MS
OHSU Library
Oregon Health & Science University
AHRQ Task Order Officer
Rosaly Correa-de-Araujo, MD, MSc, PhD
Center for Practice and Technology Assessment
Agency for Healthcare Research and Quality
Rockville, Maryland
American Academy of Family Physicians (AAFP)
Eric Wall, MD, MPH
Clinical Associate Professor of Family Medicine, OHSU
Vice President and Regional Director, Lifewise and Blue Cross/Blue Shield of Alaska Medical Director
Portland, Oregon
American College of Obstetricians and Gynecologists (ACOG)
Jone Sampson, MD
Assistant Professor of Obstetrics and Gynecology/Genetics
Oregon Health & Science University
Portland, Oregon
Resident Training Perspective
Paul Kirk, MD
Professor of Obstetrics and Gynecology
Oregon Health & Science University
Portland, Oregon
Insurance Perspective
David Labby, MD
Associate Medical Director for CareOregon and Assistant Professor of Medicine and Family Medicine
Oregon Health & Science University
Portland, Oregon
Midwifery Perspective
Polly Malby, NP, CNM
Assistant Professor of Family Nursing
Department of Family Nursing
Oregon Health & Science University
Portland, Oregon
Rural Medicine Perspective
Michelle Petrofes, MD
Physician and Partner
Dunes Family Health Care
Reedsport, Oregon
Patient Perspective
Diana Blaser
Vancouver, Washington
Patient Perspective
Alison Wetchler
Vancouver, Washington
William Phillips, MD
Clinical Professor of Family Medicine
University of Washington
Seattle, Washington
Deborah Wing, MD
Women's and Children's Hospital
University of Southern California
Los Angeles, California
Nancy Sullivan, CNM
Assistant Professor
Oregon Health & Science University
Portland, Oregon
Martin T. November, MD, MBA
Instructor of Obstetrics, Gynecology and Reproductive Biology
Harvard Medical School
Boston, Massachusetts
William A. Grobman, MD
Assistant Professor of Maternal-Fetal Medicine
Northwestern University
Chicago, Illinois
Sally Morton, PhD
RAND Chair in Statistics
RAND
Santa Monica, California
Evan Myers, MD
Assistant Professor of Obstetrics and Gynecology
Duke University Medical Center
Durham, North Carolina
Joint Commission on Accreditation of Healthcare Organizations (JCAHO) Representative:
Jerod M. Loeb, PhD
Vice President for Research & Performance Measurement
Oakbrook Terrace, Illinois
American College of Obstetricians and Gynecologists (ACOG) Representatives:
Benjamin Sachs, MD
Professor of Obstetrics, Gynecology and Reproductive Biology
Harvard Medical School
Department of Maternal and Child Health
Beth Israel Hospital
Boston, Massachusetts
Stanley Zinberg, MD
Vice President of Clinical Practice
ACOG
Washington, DC
American College of Nurse-Midwives Representative:
Ann Trudell, CNM
Lecturer-Nurse-Midwife
University of California, Los Angeles
Los Angeles, California
American Academy of Family Physicians (AAFP) Representative:
Richard Roberts, MD, JD
Belleville Family Medical Clinic
Belleville, Wisconsin
Society for Healthcare Consumer Advocacy Representatives:
Laura McHenry
Director, Patient Relations
Potomac Hospital
Woodbridge, Virginia
Jerri Scarzella
Director, Customer Relations
Holy Cross Hospital
Silver Spring, Maryland
American Academy of Pediatrics (AAP) Representatives:
William Kanto, MD
Augusta, Georgia
Anne Stark, MD
Up-To-Date
Wellesley, Massachusetts
David Atkins, MD, MPH
Chief Medical Officer
Center for Practice and Technology Assessment
Agency for Healthcare Research and Quality
Rockville, Maryland
If there was a discrepancy between data in text and tables of the studies we reviewed, we followed the following protocol:
If the correct data could be derived from other data within the study, we used these data.
If the data could not be determined from within the study, a search of an ‘erratum’ in the literature was done to see if updated data were published. If this was determined, the investigator used the updated information and included the study. The investigator noted this in the evidence table of the specific topic.
If the study data could not be determined using other study data or no ‘erratum’ information was available, the study was excluded. In summary of subtopics, investigators noted how many and which studies were excluded for this reason.
(In some cases, where no data was available for an entire subtopic, investigators contacted authors to determine correct study data. See individual subtopic methods for details on this procedure.)
Our research team decided to include only studies that were conducted in developed countries. We used the definition of “developed country” taken from the CIA World Factbook 2001, Appendix B (Washington, DC: Central Intelligence Agency). According to this source, 35 countries are considered developed countries:
Andorra
Australia
Austria
Belgium
Bermuda
Canada
Denmark
Faroe Islands
Finland
France
Germany
Greece
Holy See
Iceland
Ireland
Israel
Italy
Japan
Liechtenstein
Luxembourg
Malta
Mexico
Monaco
Netherlands
New Zealand
Norway
Portugal
San Marino
South Africa
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp.[mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
2 or 3 or 4 or 5
exp cesarean section/ or “cesarean”.mp.
6 and 7
1 or 8
limit 9 to human
limit 10 to english
10 not 11
limit 12 to abstracts
11 or 13
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
2 or 3 or 4 or 5
exp cesarean section/ or “cesarean”.mp.
6 and 7
1 or 8
limit 9 to human
limit 10 to english language
10 not 11
limit 12 to abstracts
11 or 13
Risk factors/ or “risk factors”.mp.
exp ethnic groups/ or “ethnic groups”.mp.
exp demography/ or “demographics”.mp.
Midwifery/ or “midwife”.mp.
“NATUROPATH”.mp.
Family practice/ or “family practice”.mp.
Health maintenance organizations/ or “hmo”.mp.
exp prepaid health plans/ or “prepaid health plans”.mp.
Pregnancy outcome/
exp “Outcome assessment (health care)”/
Physicians, family/ or “family physician”.mp.
exp insurance/ or exp insurance, health/
Hospitals, rural/ or Rural health/ or Rural health services/ or Rural population/ or “rural”.mp.
Medical indigency/ or “medical indigency ”.mp.
Urban health/ or Urban population/ or “metropolitan”.mp.
exp hospitals, teaching/ or “teaching hospital”.mp.
Hospitals, community/ or “community hospital”.mp.
exp hospitals, public/ or “public hospital”.mp.
exp hospitals, private/ or “private hospital”.mp.
obstetric factor$.ti.
exp infant, low birth weight/ or “low birth weight”.mp.
Fetal weight/ or “fetal weight”.mp.
exp pregnancy, multiple/ or “multiple gestation”.mp.
exp labor presentation/ or “labor presentation”.mp.
Parity/ or “parity”.mp
15 or 16 or 17 or 18 or 19 or 20 or 21 or 22 or 23 or 24 or 25
26 or 27 or 28 or 29 or 30 or 31 or 32 or 33 or 34 or 35 or 36 or 37 or 38 or 39
40 or 41
14 and 42
Databases: MEDLINE (1980-April 2002), EMBASE (1980-April 2002),
HealthSTAR (1980-April 2002)
exp labor, induced/ or “labor induction”.mp.
(labor and augment$).tw
1 or 2
limit 3 to human
limit 4 to english language
4 not 5
limit 6 to abstracts
5 or 7
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
2 or 3 or 4 or 5
exp cesarean section/ or “cesarean”.mp.
6 and 7
1 or 8
limit 9 to human
limit 10 to english language
10 not 11
limit 12 to abstracts
11 or 13
exp risk assessment/ or “risk assessment”.mp.
exp probability/ or “probability”.mp.
Predictive value of tests/
previous vaginal delivery.mp.
Gestational age/ or “gestational age”.mp.
“SPONTANEOUS LABOR”.mp.
Birth weight/ or “birth weight”.mp.
Fetal weight/ or “fetal weight”.mp.
exp labor presentation/ or Oxytocin/ or “cervical dilation”.mp.
exp treatment outcome/ or Pregnancy outcome/ or “outcome”.mp.
Cesarean section, repeat/ or “repeat cesarean”.mp.
15 or 16 or 17 or 18 or 19 or 20 or 21 or 22 or 23 or 24 or 25
14 and 26
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
exp cesarean section/ or “cesarean”.mp.
1 or 2 or 3 or 4 or 5 or 6
exp health status/ or “health status”.mp.
exp health status indicators/ or “health status indicators”.mp.
exp quality of life/ or “quality of life”.mp.
Patient satisfaction/ or “patient satisfaction”.mp.
8 or 9 or 10 or 11
7 and 12
limit 13 to human
limit 14 to english language
14 not 15
limit 16 to abstracts
15 or 17
exp MALPRACTICE/ or malpractice.mp.
exp Jurisprudence/ or litigation.mp.
lj.fs.
19 or 20 or 21
7 and 22
limit 23 to (human and english language)
18 or 24
exp Depression, Postpartum/ or postpartum depression.mp.
7 and 26
27 not 25
limit 28 to (human and english language)
25 or 29
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
VBAC.mp.
1 or 2
ec.fs.
exp “costs and cost analysis"/
exp economics/
exp Insurance/
4 or 5 or 6 or 7
3 and 8
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
11 or 12 or 13 or 14
exp cesarean section/ or “cesarean”.mp.
15 and 16
10 or 17
limit 18 to human
limit 19 to english language
19 not 20
limit 21 to abstracts
20 or 22
8 and 23
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
VBAC.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, cas registry/ec number word, mesh subject heading]
exp Labor/
3 or 4 or 5 or 6
exp cesarean section/ or “cesarean”.mp.
7 and 8
1 or 2 or 9
exp Health Services Accessibility/
(access to healthcare or access to health care).mp.
exp HOSPITALS, RURAL/ or exp RURAL HEALTH SERVICES/
exp HOSPITALS, URBAN/ or exp URBAN HEALTH SERVICES/
Physicians, Family/ or family physicians.mp.
general practitioners.mp.
Midwifery/ or midwives.mp.
Length of Stay/
exp Clinical Competence/ or clinical competence.mp.
exp Utilization Review/
19 and 20
exp *clinical competence/
21 or 22
exp Physician's Practice Patterns/ or physician's practice patterns.mp.
13 or 14 or 15 or 16 or 17 or 18 or 19 or 20 or 21 or 22 or 23 or 24
11 or 12 or 25
10 and 26
limit 27 to (human and english language)
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
VBAC.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
3 or 4 or 5 or 6
exp cesarean section/ or “cesarean”.mp.
7 and 8
1 or 2 or 9
exp MEDICAID/ or medicaid.mp.
10 and 11
limit 12 to (human and english language)
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
VBAC.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
3 or 4 or 5 or 6
exp cesarean section/ or “cesarean”.mp.
7 and 8
1 or 2 or 9
exp LEGISLATION/ or legislation.mp.
lj.fs. or law$1.mp.
11 or 12
10 and 13
Databases: MEDLINE (1980-April 2002), HealthSTAR (1980-April 2002)
Vaginal birth after cesarean/ or “vaginal birth after cesarean”.mp.
VBAC.mp.
(trial of labor or trial of labour or trial of scar$).mp.
Delivery/ or Episiotomy/ or Extraction, obstetrical/ or Home childbirth/ or Labor, induced/ or Natural childbirth/ or Version, fetal/
(vaginal birth or vaginal delivery or uterine rupture).mp. [mp=title, abstract, registry number word, mesh subject heading]
exp Labor/
3 or 4 or 5 or 6
exp cesarean section/ or “cesarean”.mp.
7 and 8
1 or 2 or 9
exp Practice Guidelines/ or practice guidelines.mp.
10 and 11
limit 12 to english language
Studies that were initially included and at the data abstraction level were excluded (see Bibliography for full reference.)
| Author, Year | Study Design | Reason |
|---|---|---|
| VBAC Success/ Maternal & Infant Outcomes | ||
| Abitbol, 1993 | Prospective Cohort | All women with history of cesarean / study follow-up or time period ambiguous |
| Aydemir, 1993 | Unable to separate scarred uterus group and CD data by group | |
| Hamilton, 2001 | Case-Control | Comparison and control groups not comparable on CD rates |
| Holland, 1992 | Retrospective Cohort | Insufficient description of population/data |
| Lynch, 1996 | Case-Series | Data not presented in an understandable/usable way |
| Miller, 1994 | Retrospective Cohort | Duplicate Data to Leung, 1993 |
| Poma, 2000 | Before-After Policy change | Data difficult to understand/abstract due to study design |
| Rozenberg, 1996 | Prospective Cohort | Sensitivity/ specificity data not able to be analyzed |
| Schneider, 1988 | Prospective Cohort | Noncomparable groups, vertical incisions |
| Predictive Tools and Individual Factors | ||
| Del Valle, 1994 | TBA | Incorrect comparison/no TOL group information |
| Goldman, 1990 | Case-control | Incorrect comparison/no TOL group information |
| King, 1994 | Database | Incorrect comparison/no TOL group information |
| Stafford, 1991 | Database | Incorrect comparison/no TOL group information |
| Wagner, 1999 | Retrospective Cohort | Error in data |
| Induction of Labor | ||
| Grubb, 1996 | RCT | Data on risk/benefit of induction in TOL not discernable |
| Kaplan, 1993 | Retrospective Cohort | Data on risk/benefit of induction in TOL not discernable |
| Learman 1996 | Retrospective Cohort | Data on risk/benefit of induction in TOL not discernable |
| Maslow, 2000 | Retrospective Cohort | Data on risk/benefit of induction in TOL not discernable |
| Peleg, 1999 | RCT | Data on risk/benefit of induction in TOL not discernable |
| Troyer, 1992 | Retrospective Cohort | Data on risk/benefit of induction in TOL not discernable |
| Turner, 1997 | Retrospective Cohort | Data on risk/benefit of induction in TOL not discernable |
| Cost, Healthcare Resources, and Provider Characteristics | |
|---|---|
| Author, Year | Reason |
| Abitol (1993) | No relevant data |
| ACOG (1996) | review |
| ACOG (1997) | No relevant data |
| Adams (2000) | General population |
| Afriat (1990) | Review |
| Ales (1990) | Wrong population |
| American Health Consultants (1996) | Review |
| Amini (1994) | General population |
| Anderson (1985) CMAJ | General population |
| Anderson (1999) | Wrong population |
| Anonymous (DS&B, 1998) | National data from insurer; limited cost and number of cases |
| Balaban (1994) | General population |
| Barclay (1989) | General population |
| Barros (1991) | Developing country |
| Bennetts (1982) | General population |
| Benson (2001) | No relevant data |
| Bertollini (1992) | General population |
| Bique (1999) | Wrong population |
| Blakemore (1990) | General population |
| Blegen (1995) | General population; no relevant data |
| Bonham (1983) | General population |
| Braveman (1996) | No data |
| Britton (1998) | General population |
| Brooten (1994) | General population |
| Bryan (1990) | Wrong population |
| Buist (1999) | General population |
| Burns (1993) | No relevant data |
| Burns (1994) | No relevant data |
| Butler (1993) | General population |
| Carey (1991) | General population |
| Carpenter (1987) | General population |
| Caughey (1998) | No relevant data |
| Cavero (1991) | General population |
| Chambliss (1992) | No relevant data |
| Chaska (1988) | General population |
| Chervenak (1996) | Editorial; no relevant data |
| Chez (2001) | No relevant data |
| Chua (1991) | Developing country (Sinagapore) or General population |
| Clark (1991) | General population |
| Clarke (1995) | No relevant data |
| Clarke (1996) | No relevant data |
| Clemenson (1993) | Review |
| Coco (1998) | Review |
| Combs (1992) | Wrong population |
| Committtee on Obstetric Practice (1996) | No relevant data |
| Comreid (1996) | Wrong population |
| Coody (1993) | Wrong population |
| Coonrod (2000) | General population |
| Cowan (1994) | No relevant data |
| Creedy (2000) | General population |
| Crump (1988) | General population |
| Curtin (1999) | No relevant data |
| Daniels (1989) | Review |
| Davies (1996) | No relevant data |
| Dawson (1997) | Editorial |
| de Meeus (1998) | No relevant data |
| de Regt (1986) | Wrong time |
| DeJoy (1999) | Letter |
| Demott (1990) | General population |
| DeMott (1999) | Letter |
| Dhall (1987) | Developing country |
| Dublin (2001) | No relevant data |
| Duff (1988) | No relevant data |
| Eakes (1990) | Wrong population |
| Eakins (1989) | No relevant data |
| Eddy (1990) | Review |
| Eidelman (1998) | General population |
| Eisenberg (1979) | Wrong time |
| Elliott (1997) | No relevant data |
| Emerson (2001) | Wrong population |
| Enthoven (1989) | General population |
| Evans (1984) | Data pre-1980 |
| Fadda (2001) | Wrong population |
| Farmer (1996) | Wrong population; no relevant data |
| Feldman (1985) | Wrong population |
| Finkler (1982) | Review |
| Finkler (1991) | General population |
| Finkler (1993) | General population |
| Firth (1988) | No relevant data |
| Flamm (1985) Clin Obst & G, 28, 735 | No relevant data |
| Flamm (1990) | No relevant data |
| Flamm (1997) | Review; no relevant data |
| Flanagan (1987) | Wrong population |
| Fraser (1987) | General population |
| Frigoletto | Wrong population |
| Gafni (1997) | Wrong population |
| Garite (1986) | Wrong population |
| Gates (1995) | No relevant data |
| Gifford (1995) | Wrong population |
| Gillette (1996) | Letter; no relevant data |
| Glasser (1988) | General |
| Gleicher (1984) JAMA 3273 | General population |
| Gleicher (1986) | Editorial; no relevant data |
| Goeree (1995) | Wrong population; no relevant data |
| Goetzl (2001) | No relevant data |
| Gold (1987) | General population |
| Goldfarb (1987) | General population |
| Goldfarb (1991) | General population |
| Gonzalves (1993) | Wrong population |
| Gordon (1999) | Wrong population, no relevant data |
| Gould (1989) | Wrong population |
| Grazier (1987) | General population |
| Green (1995) | Editorial |
| Gregory ( 1994) | No relevant data |
| Gregory ( 1999) | Wrong population; no relevant data |
| Greis (1981) | General population |
| Greulich (1994) | General population |
| Grullon (1997) | Wrong popultion |
| Grzybowski (1991) | General population; no relevant data |
| Guirguis (1991) | Developing country |
| Hage (1992) | Wrong population |
| Haire (1991) | General population |
| Halpern (1999) | Letter |
| Haney (1999) | General population |
| Hanley (1996) | No relevant data; VBAC outcomes (N=376) |
| Haq (1988) | Review |
| Hart (1996) | Wrong population |
| Harwood (2001) | Wrong population |
| Heddleston (1991) | No relevant data |
| Hemminki (1991) | General population |
| Henry (1995) | No relevant data |
| Hibbard (1989) | General population |
| Hickson (1987) | No relevant data |
| Hillman (1990) | General population |
| Hornbrook (1981) | Wrong time |
| Hourvitz (1996) | Wrong population |
| Hsiao (1988) | No relevant data |
| Hueston (1993) | Wrong population |
| Hueston (1994) | General population |
| Hueston (1995) J Fam Pract, 40, 345 | General population |
| Hueston (1995A) | General population |
| Hurst (1984) | General population |
| Institute of Clinical Systems Investigation (1996) | No relevant data |
| Janowitz (1982) | Developing country |
| Janowitz (1984) | Developing country |
| Jones (1991) | No relevant data |
| Joseph (1991) | No relevant data |
| Kaplan (1996) | Wrong population |
| Kazandian (1996) | No relevant data |
| Keeler (1993) | Review |
| Kennedy (1997) | Review |
| Kennell (1991) | General population |
| Kilpatrick (1995) | Wrong population |
| Kirk (1990) | No relevant data |
| Kizer (1988) | Letter |
| Kline (1993) | No relevant data |
| Koska (1989) | General population |
| Kotagal (1999) | Wrong population |
| Kozak (1989) | General population |
| Kramer (1997) | General population; no relevant data |
| Krieger (1993) | Editorial |
| Krikke (1989) | Wrong population |
| Lagrew (1998) | General population |
| Lavin (1982) | Data pre-1980 |
| Leung (1993) | No relevant data |
| Leung (1998) | General population |
| Leyland (1993) | Letter |
| Lieberman (1998) | No relevant data |
| Lopez-Zeno (1992) | Wrong population |
| Lydon-Rochelle (2000) | Wrong population |
| Magann (1991) | Wrong population |
| Mansfield (1995) | General population |
| Mardon (1997) | General population |
| Marieskind (1989) | Review |
| Marta (1994) | Review |
| Martin (1997) | Wrong population (low-segment vertical) or review |
| Mauldin (1996) | General population |
| McClain (1990) | No relevant data |
| McCloskey (1992) | Wrong population |
| McCord (2001) | Developing country |
| McIntosh (1984) | General population |
| McIntosh (1991) | Review |
| Meehan (1989) | No relevant data ? |
| Menacker (2001) | No relevant data |
| Merrill (1999) | General population; no relevant data |
| Metropolitan Life Insurance Co, (1994) | No relevant data |
| Miller (1980) | No relevant data |
| Miller (1989) | Review |
| Miller (1994) Ob Gyn 255 | No relevant data |
| MMWR 4/23/1993 | General population |
| MMWR 8/16/96 | General population |
| Moore (1986) | Wrong population |
| Mousa (2000) | Wrong population |
| Mozurkewich (2000) | No relevant data |
| Mundle (1996) | General population; no relevant data |
| Myers (1986) | Wrong population |
| Myers (1990) SA, NEJM | Letter |
| Myers (1993) | General population |
| Naef (1995) | No relevant data |
| Nesbitt (1991) | Wrong population |
| Newton (1989) | Wrong time |
| Norman (1995) | Editorial |
| Notzon (1990) | No relelvant data |
| November (2001) | Review |
| Oberman (1989) | General population |
| Obst (2001) | General population |
| Oleske (1991) | General population |
| Oleske (2000) | No relevant data |
| Panlilio (1992) | General population |
| Parrish (1993) | General population |
| Parrish (1994) JAMA 443 | Wrong population |
| Paul (2000) | Developing country |
| Pauly (2001) | No relevant data |
| Petitti (1985) | Review |
| Petrou (2001) | General population |
| Phillips (1982) | Wrong time |
| Placek (1983) | Wrong time |
| Placek (1988) | General population |
| Poma (1999) | No relevant data |
| Porreco (1989) | Editorial |
| Porreco et al (1989) | Editorial |
| Pridjian (1991) | General population |
| Rabinerson (2001) | Letter; no relevant data |
| Radin (1993) | Wrong population |
| Regan Report on Nursing Law (1993) v34 No.2 | Wrong population |
| Reid (1989) | General population |
| Resnick (1987) | General population |
| Reynolds (1997) | General population |
| Rhodes (1994) | Wrong population |
| Roberts (1994) | No relevant data |
| Roberts (1997) | Meta-analysis; no citations for included articles |
| Robertson (1990) | General population |
| Rochat (1988) | General population |
| Rock (1988) | Wrong population |
| Rogers (2000) | Wrong population |
| Rooks (1989) | General population |
| Rose (1999A and B) | Editorial |
| Rose (1999A) AFP 474 | Editorial |
| Rosen (1990) | Review |
| Rosen (1991) | Review |
| Rubin (1981) | Wrong time |
| Ruderman (1993) | General population |
| Rudick (1984) | No relevant data |
| Sachs (1999) | Editorial; no relevant data |
| Sachs (1999) | Editorial |
| Sachs (1999A) | Editorial |
| Sachs (1999B) | Letter |
| Sack (1980) | Wrong population |
| Sakala (1993) | General population |
| Sanchez-Ramos (1992) | Wrong population |
| Sanchez-Ramos (1995) | General population |
| Sandmire (1994) | No relevant data |
| Sandmire (1996) | No relevant data |
| Satcher (1999) | Letter |
| Satin (1991) | General population |
| Satin (1994) | General population |
| Schipp (2000) | No relevant data |
| Schipp (2001) | No relevant data |
| Schnitker (1999) | Review |
| Scott (1991) | No relevant data |
| Scott (1997) | Review |
| Seminar in Nursing Law | Wrong population |
| Sennett (1983) | Wrong population |
| Shy (1980) | Wrong time |
| Siddiqui (1999) | General population |
| Sims (1984) | General population |
| Sirio (1999) | Letter |
| Skupinski (1996) | Wrong population |
| Spelliscy (1995) | Wrong population |
| Stafford (1990) JAMA 683 | Review |
| Stafford (1993) | No relevant data |
| Stainaker (1997) | No relevant data |
| Statistical Bulletin (1988) | General population |
| Statistical Bulletin (1989) | Wrong time |
| Statistical Bulletin (1992) | General population |
| Stuart (2001) | General population |
| Taffel (1983) | General population |
| Taffel (1987) | No relevant data |
| Taffel (1991) | General population |
| Taylor (1997) | Wrong population |
| Torres (1989) | Wrong population |
| Tussing (1992) | Wrong population |
| Udom (1998) | General population; no relevant data |
| van Amerongen (1989) | No relevant data |
| Vimercati (2000) | No relevant data |
| Wall (1995) | Editorial |
| Wen (1998) | General population |
| Wennberg (1982) | No relevant data |
| Whitsel (2000) | No relevant data |
| Williams (1983) RL, AJPH | Wrong time |
| Wilner (1981) | Wrong time |
| Wright (1984) | Wrong time |
| Yanover | pre 1980 |
| Young (1997) | Editorial |
| Zahniser (1992) | No relevant data |
| Zelop (2001) | No relevant data |
| Zhou (1991) | Developing country (China) |
Our team used the criteria listed below to rate studies.* Details on use of these criteria follow. See individual topic method and/or results sections for discussion on those components considered fatal flaws for particular topics.
Random assignment
Allocation concealed
Groups similar at baseline
Eligibility criteria specified
Outcome assessors blinded
Care provider blinded
Patient unaware of treatment
Intention-to-treat analysis
Maintenance of comparable groups
Reporting of attrition, crossovers, adherence, and contamination
Differential loss to followup or overall high loss to followup
Comparable groups assembled/ Database representative for study (e.g., comparing women who all would qualify for TOL rather than TOL versus medically indicated repeat cesarean)
Maintenance of comparable groups
Clear definition of comparison groups/sufficient description of distribution of prognostic factors
Measures equal, reliable, valid/ explicit definition of outcomes (objective, consistently applied e.g., uterine rupture)
Outcome assessment blind to exposure status
Loss/dropout rate
Follow-up long enough for outcomes to occur
Consider/adjust for potential important confounders (obstetric/medical conditions)
Case definition explicit
State of the cases reliably assessed and validated
Accurate ascertainment of cases
Nonbiased selection of cases/controls (controls randomly selected)
Cases and controls comparable with respect to potential confounding factors
Procedures applied equally
Appropriate attention to confounders
Appropriate statistical analysis used (matched, unmatched, overmatching)
Representative sample selected from a relevant population
Inclusion criteria explicit
Individuals entered the survey at a similar point in their disease progression
Followup long enough for important events to occur
Outcomes assessed using objective criteria/ blinding used
If comparison of sub-series, sufficient description of the series and distribution of prognostic factors
The Methods Work Group for the US Preventive Services Task Force (USPSTF) developed a set of criteria by which the quality of individual studies could be evaluated in terms of both internal validity and external validity. The USPSTF accepted the criteria, and the associated definitions of quality categories, that relate to internal validity at its September 1999 quarterly meeting. Details on this criteria and grading study quality has also been documented.*
This document describes the criteria relating to internal validity and the procedures followed to make these judgments.
All topic teams will use initial “filters” to select studies for review that deal most directly with the question at issue and that are applicable to the population at issue. Thus, studies of any design that use outdated technology or that use technology that is not feasible for primary care practice may be filtered out before the abstraction stage, depending on the topic and the decisions of the topic team. The teams will justify such exclusion decisions if there could be reasonable disagreement about this step. The criteria below are meant for those studies that pass this initial filter.
Presented below are a set of minimal criteria for each study design and then a general definition of three categories—good, fair, and poor—based on those criteria. These specifications are not meant to be rigid rules but rather are intended to be general guidelines, and individual exceptions, when explicitly explained and justified, can be made. In general, a good study is one that meets all criteria well. A fair study is one that does not meet (or it is not clear that it meets) at least one criterion but has no known “fatal flaw.” Poor studies have at least one fatal flaw.
Criteria:
Initial assembly of comparable groups
-for RCTs: adequate randomization, including first concealment and whether potential confounders were distributed equally among groups
-for cohort studies: consideration of potential confounders with either restriction or measurement for adjustment in the analysis; consideration of inception cohorts
Maintenance of comparable groups (includes attrition, cross-overs, adherence, contamination)
Important differential loss to follow-up or overall high loss to follow-up
Measurements: equal, reliable, and valid (includes masking of outcome assessment)
Clear definition of interventions
Important outcomes considered
Analysis: adjustment for potential confounders for cohort studies, or intention to treat analysis for RCTs.
Good: Meets all criteria: Comparable groups are assembled initially and maintained throughout the study (follow-up at least 80 percent); reliable and valid measurement instruments are used and applied equally to the groups; interventions are spelled out clearly; important outcomes are considered; and appropriate attention to confounders in analysis. In addition, for RCTs, intention to treat analysis is used.
Fair: Studies will be graded fair if any or all of the following problems occur, without the fatal flaws noted in the “poor” category below: Generally comparable groups are assembled initially but some question remains whether some (although not major) differences occurred in follow-up; measurement instruments are acceptable (although not the best) and generally applied equally; some but not all important outcomes are considered; and some but not all potential confounders are accounted for. Intention to treat analysis is done for RCTS.
Poor: Studies will be graded poor if any of the following fatal flaws exists: Groups assembled initially are not close to being comparable or maintained throughout the study; unreliable or invalid measurement instruments are used or not applied at all equally among groups (including not masking outcome assessment); and key confounders are given little or no attention. For RCTs, intention to treat analysis is lacking.
Criteria:
Accurate ascertainment of cases
Nonbiased selection of cases/controls with exclusion criteria applied equally to both
Response rate
Diagnostic testing procedures applied equally to each group
Measurement of exposure accurate and applied equally to each group
Appropriate attention to potential confounding variable
Good:Appropriate ascertainment of cases and nonbiased selection of case and control participants; exclusion criteria applied equally to cases and controls; response rate equal to or greater than 80 percent; diagnostic procedures and measurements accurate and applied equally to cases and controls; and appropriate attention to confounding variables.
Fair: Recent, relevant, without major apparent selection or diagnostic work-up bias but with response rate less than 80 percent or attention to some but not all important confounding variables.
Poor: Major selection or diagnostic work-up biases, response rates less than 50 percent, or inattention to confounding variables.
Criteria:
Comprehensiveness of sources considered/search strategy used
Standard appraisal of included studies
Validity of conclusions
Regency and relevance are especially important for systematic reviews
Good: Recent, relevant review with comprehensive sources and search strategies; explicit and relevant selection criteria; standard appraisal of included studies; and valid conclusions.
Fair: Recent, relevant review that is not clearly biased but lacks comprehensive and search strategies.
Poor: Outdates, irrelevant, or biased review without systematic search for studies, explicit selection criteria, or standard appraisal of studies.
Three studies (Lydon-Rochelle, 2001; Rageth, 1999; Stone, 2000), used ICD-9 codes to measure uterine rupture rates, a method that has been shown to be inaccurate (Anonymous, 2000). Hospital discharge data has important limitations. For example, one state-wide study of ICD-9 codes from hospital discharge data compared the codes for uterine rupture to detailed medical records including surgical reports and discharge summaries in Massachusetts (Anonymous, 2000). In a seven-year period 1,244 suspected uterine ruptures were identified from ICD-9 codes. After detailed record review 480 (39.8 percent) of these were confirmed as true uterine ruptures rather than incidental extension of uterine incision at surgery or uterine windows without disruption. The positive predictive value was 50.7percent for the ICD-9 codes 665.0 (rupture of uterus before the onset of labor) and 665.1 (rupture of uterus during labor or not otherwise specified) and 28.6 percent for code 674.1 (disruption of cesarean wound including dehiscence or disruption of uterine wound). If they had restricted cases of uterine rupture to those identified by codes 665.0 and 665.1, as was done in the two retrospective studies above (Lydon-Rochelle, 2001; Stone, 2000), they would have missed one third of cases classified as having uterine rupture by chart review. Thus, ICD-9 codes are not an accurate means to identify cesarean disruption. Seven of 15 prospective cohort studies were rated poor.
References
Anonymous. Use of hospital discharge data to monitor uterine rupture--Massachusetts, 1990-1997; US Department of Health & Human Services. MMWR - Morbidity & Mortality Weekly Report 2000;49(12):245–8.
Lydon-Rochelle M, Holt VL, Easterling TR, et al. Risk of uterine rupture during labor among women with a prior cesarean delivery. New England Journal of Medicine 2001;345(1):3–8.
Rageth JC, Juzi C, Grossenbacher H. Delivery after previous cesarean: a risk evaluation. Swiss Working Group of Obstetric and Gynecologic Institutions. Obstetrics & Gynecology 1999;93(3):332–7.
Stone C, Halliday J, Lumley J, et al. Vaginal births after Caesarean (VBAC): a population study. Paediatric & Perinatal Epidemiology 2000;14(4):340–8.
| Author/Year/Quality | Random assignment | Allocation concealed | Groups similar at baseline/Maintenance of comparable groups | Eligibility criteria specified | Blinded: Outcome Assessors/Care Provider/Patient | Cointerventions/Intention-to-treat analysis | Report of attrition, crossovers, adherence, & contamination | Differential loss to followup or overall high loss to followup | Quality Score |
|---|---|---|---|---|---|---|---|---|---|
| Random Control Trials | |||||||||
| Lelaidier 1994 | Yes - randomized in pharmacy, “balanced rand list” | Yes - tablets all the same disp out of pharm | Yes, although diff in rates of postdates, IUGR between Mef and pl unsure if SS | Yes | Yes/Yes/Yes | Yes, f/u with oxytocin, specific details not available although authors looked at dose requirements/ | ? | NR | FAIR |
| Rayburn 1999 | Yes pharmaceutical company computer generated | Yes | Yes except never looked at parity/NR | Yes | ?/No/No | Yes oxytocin - similar between groups/No - non-compliance excluded prior to analysis | Yes oxytocin - similar between groups | No | FAIR |
| Xenakis 1995 | inadequate (days of the week) | no | yes/NR | yes | No/No/No | None/NR | NR | none | POOR |
| Wing 1998 | NR | NR | NR/NR | yes | No/No/No | None/NR | NR | none | POOR |
| Population-Based Database | |||||||||
| Author, Year | Comparable groups assembled/Database representative for study | Maintenance of comparable groups | Clear definition of comparison groups/sufficient description of distribution of prognostic factors | Measures equal, reliable, valid/eplicit definition of outcomes | Outcome assessment blind to exposure status | Loss/Drop-out rate | Follow-up long enough for outcomes to occur | Consider/Ad just for potential important confounders | Quality Score |
| McMahon 1996 | Yes | NA | Yes | Yes | No | NA | Yes | Yes | GOOD |
| Smith 2002 | Uncertain | NA | Uncertain | Yes | No | NA | Yes | Yes | FAIR |
| Bais 2001 | Uncertain | NA | No | Most | No | NA | Yes | No | POOR |
| Lyndon-Rochelle 2001 | Yes | NA | Yes | No | No | NA | Yes | Yes | POOR |
| Stone 2000 | Uncertain | NA | No | No for uterine rupture | No | NA | Yes | No | POOR |
| Gregory 1999 | Uncertain | NA | No | Yes | No | NA | Yes | No | POOR |
| Rageth 1999 | No | NA | No | No | No | NA | Yes | No | POOR |
| Holt 1997 | Uncertain | NA | No | Yes | No | NA | Yes | No | POOR |
| Beall 1984 | Yes | NA | Yes | No | No | NA | Yes | Not adjusted for age, parity, obsteric or medical complications | POOR |
| Prospective Cohort | |||||||||
| Duff 1988 | Yes | NA | Yes | Yes | No | NA | Yes | Y/N | GOOD |
| Flamm 1994 | Yes | NA | Yes, age, prior #CD, birth weight | Yes | No | NA | Yes | Yes | GOOD |
| Flamm 1988 | Yes | NA | NA | Yes | No | NA | Yes | looked at group specific rates for parity, prior CD reason | GOOD |
| Flamm 1987 | yes | NA | partial, reasons for induction not given | yes | No | NA | Yes | Yes | FAIR |
| Blanchette 2001 | nr | NA | No | yes | No | NA | yes | yes | FAIR |
| Cowan 1994 | NA, no comparison | NA | NA, no comparison | Yes | No | NA | Yes | Y/N | FAIR |
| Flamm 1990 | Yes/No | NA | NA | Yes, defined rupture | No | NA | Yes | uncertain | FAIR |
| Phelan 1987 | Yes | NA | No info for parity, age | Yes | No | NA | Yes | Yes/No | FAIR |
| Paul 1985 | Yes | NA | No | Yes | No | NA | Yes | No, scar type, age, parity | FAIR |
| Martin 1983 | Yes | NA | No | Yes except fever | No | NA | Yes | No | FAIR |
| RCT | Quality Components | ||||||||
| Study, Year | Random assignment | Allocation concealed | Groups similar at baseline/Maintenance of comparable groups | Eligibility criteria specified | Blinded: Outcome Assessors/Care Provider/Patient | Intention-to-treat analysis | Report of attrition, crossovers, adherence, & contamination | Differential loss to followup or overall high loss to followup | Quality Score |
| Thubisi, 1993 | Y | NA | Y/N | Y | N/N/N | Y | NA | NA | GOOD |
| Fraser, 1997 | Y | NA | Y/Y & N | Y | N/N/N | N | Y | Y/N | FAIR |
| COHORT | Quality Components | ||||||||
| Study, Year | Comparable Groups. Clear inclusion criteria. | Maint. of comparable groups | Clear definition of comparison groups | Measures reliable, valid | Unbiased assessment of data and analysis of results | Loss/Drop - out rate | Follow-up long enough for outcomes to occur | Adjust for potential confounders (obstetric conditions) | Quality Score |
| Flamm, 97 | Y | Y | Y/N | Y | N | NA | Y | Y | GOOD |
| Jakobi, 93 | Y | Y | N | Y | N | NA | Y | Y | FAIR |
| McNally, 99 | Y | Y | N | Y/N | N | NA | Y | Y | FAIR |
| Stronge, 1996 | Y | Y | N | Y/N | N | NA | Y | Y/N | FAIR |
| Troyer, 92 | Y | Y | N | Y/N | N | NA | Y | N | FAIR |
| Vinueza, 2000 | Y | Y | Y | Y/N | N | NA | Y | N | FAIR |
| Weinstein, 96 | Y | Y | N | Y/N | N | NA | Y | Y | FAIR |
| Zelop, 2001 (A) | Y | Y | Y/N | Y | N | NA | Y | Y | FAIR |
| Zelop, 2001 (B) | Y | Y | Y/N | Y | N | NA | Y | Y | FAIR |
| Abitbol, 91 | N | NA | N | Y | N | NA | Y | N | POOR |
| Lao, 87 | Y | Y | N | Y/N | N | NA | Y | N | POOR |
| Morgan, 88 | Y | Y | N | Y | N | NA | Y | N | POOR |
| Thurnau, 91 | Y | Y | N | Y | N | NA | Y | N | POOR |
| Wright, 85 | Y | Y | N | Y/N | N | NA | Y | N | POOR |
| Case-Control | Quality Components | ||||||||
| Author, Year | Case definition explicit | State of the cases reliably assessed and validated | Accurate ascertainment of cases | Cases/controls: Nonbiased selection & comparable confounding factors | Procedures applied equally | Measurement of exposure accurate and applied equally | Appropriate attention to confounders | Appropriate statistical analysis used (matched, unmatched, overmatching) | Quality Score- Review 1 |
| Macones, 2001 | Y | Y/N | Y | N/N | Y | Y/N | Y | Y | FAIR |
| Pickhardt, 92 | Y | Y/N | Y/N | N/N | Y | Y/N | Y | Y | FAIR |
| Case-Series | Quality Components | ||||||||
| Author, Year | Representative sample selected from a relevant population | Inclusion criteria explicit | Individuals entered the survey at a similar point in their disease progression | Follow-up long enough for important events to occur | Outcomes assessed using objective criteria/blinding used | If sub-series, sufficient description & distribution of prognostic factors | Quality Score | ||
| Flamm, 91 | Y | Y | Y/N | Y | Y | N | FAIR | ||
| de Meeus, 98 | Y | Y | Y/N | Y | Y | N | FAIR | ||
| Schatcher, 94 | Y | Y/N | Y/N | Y | Y | Y | GOOD | ||
| RCT | Quality Components | ||||||||
| Study, Year | Random assignment | Allocation concealed | Groups similar at baseline/Maintenance of comparable groups | Eligibility criteria specified | Blinded: Outcome Assessors/Care Provider/Patient | Intention-to-treat analysis | Report of attrition, crossovers, adherence, & contamination | Differential loss to followup or overall high loss to followup | Quality Score |
| Fraser, 1997 | Yes | Yes | No differences in baseline demographic. Similar proportions of women had previous labors and were requesting tubal ligation. | Used validated Birth Experience Rating Scale. | Blocked by hospital and by the women's motivation (either low or high) | Yes, used intent-to-treat | Yes | Lost 140/1275 (11.0%). | Good |
| COHORT | Quality Components | ||||||||
| Study, Year/Quality/Design | Comparable Groups. Clear inclusion criteria. | Maintenance of comparable groups | Clear definition of comparison groups | Measures reliable, valid | Unbiased assessment of data and analysis of results | Loss/Drop - out rate | Follow-up long enough for outcomes to occur | Adjust for potential confounders (obstetric conditions) | Quality Score |
| Kirk, 1990 | Incl/excl criteria NR. At Hospital B: 73% of patients who planned a TOL returned surveys compared with 47% of ERCD. | NR | Yes | Lost 97/257 (38%) | Yes | NA | Fair: Fair follow-up, validity of measures not described. | ||
| Kline, 1993 | Clear exclusion criteria. No differences in demographic | Yes | Women requesting elective CD. Women attempting TOL. | Validation unlikely but not reported. | Unclear who asked patients about delivery reasons but biased if patient's clinician did. | NR | Yes | No confounders or adjustments are presented. | Fair. Unclear who interviewed patients. Potentially biased results. |
| McClain, 1985; McClain, 1987; McClain, 1990 | Yes | Yes | Women who chose TOL and those who chose elective repeat CD. | Unclear if reasons validated. | Yes | NR | Follow-up not reported. | Yes. Adjusted for education when examining ethnicity. | Fair. Measures validation not reported. |
| Martin, 1983 | Yes | NR | Unclear who interview the women regarding their birth choice and reasons. | Accounted for all patients. | Follow-up NR | Accounted conditions (# of prior CDs, epidural use ) in outcomes. | Fair. Measures validation NR. | ||
| Meier, 1982 | Clear inclusion criteria. | Reported no demographics for groups. | NR | Yes | Lost 14/53 (26.4%) of TOL. | Yes | NA | Fair. Follow-up rate is for subgroup. Measures validation NR. | |
| Melnikow, 2001 | Yes, groups determined by underlying CD rates at hospitals. | Yes, used ICD-9CM coding. | Yes. Independent chart abstraction. | Lost 73/1662 (4.3%) | NA | NR | Fair. No mention of adjustments. | ||
| Quinlivan, 1996 | Not clear of some patients eligible for TOL. | No baseline demographics or risks presented. | Women with emergency and elective CD. | Probably clinically valid. | No, the clinician who performed the CD provided the data. | NR | NA | NA | Poor. |
| Cross-sectional | Quality Components | ||||||||
| Study, Year/Quality/Design | Comparable Groups. Clear inclusion criteria. | Maintenance of comparable groups | Clear definition of comparison groups | Measures reliable, valid | Unbiased assessment of data and analysis of results | Loss/Drop - out rate | Follow-up long enough for outcomes to occur | Adjust for potential confounders (obstetric conditions) | Quality Score |
| Lau, 1996 | Clear inclusion criteria. | Not clear | Yes | NA | Yes | NA | Good | ||
| Murphy, 1989 | Yes | Content validity. Pretesting. | Yes | Lost 3/53 (5.7%) | Y | NA. Discussed possible confounders | Good | ||
| Joseph, 1991 | Clear exclusion criteria. | Unclear. | Presented may groups of patients with crossovers. | Yes/No | No. | Accounted for all patients | Yes | Presented only descriptive statistics. | Fair. |
| Gamble, 2001 | NR by group. Inclusion/exclusion criteria NR. | Yes. Content validity. | Yes | Lost 3% at recruitment | NA | NA | Fair. No demographics by group. | ||
| Fawcett, 1994 | NA. Only one group. | Unclear | Unclear | Interrater reliability was 92%. | Yes. | NR | 12–48 hours after delivery. | NA | Fair. Follow-up rate NR. |
| Mould, 1996 | Clear inclusion criteria. No baseline demographic or risks presented. | Cross-sectional study | Women having an ERCD. Women having an emergency CD. | Validation unlikely but not reported. Yes/No | No, patient's clinician interviewed for preference. | Lost 15/102 (14.7%) | Yes | No | Poor |
| Abitbol, 1993 | Clear inclusion criteria. No baseline demographics. | Unclear. | Women requesting elective CD. Women attempting TOL. | Validation unlikely but not reported. | No | 0%? | Yes | No | Poor. Potentially biased results. |
| Dilks, 1997 | Yes | Yes | Unclear | Recruited 74/225. Lost (67.2%) | Yes | NA | Poor. Recruitment rate poor. | ||
| Author/year | Perspective Stated | Prog Benef. Described | Intervention Cost incl | Morbidity/SE Costs include | Averted Costs include | Induced Costs include | Costs/Ben Discounted | Sensitivity Analyses | C/E Ratio Stated | Quality Score |
|---|---|---|---|---|---|---|---|---|---|---|
| Chung (2001) | Good | Good | Good | Good | Good | Good | Good | Good | Good | GOOD |
| Grobman (2000) | Good | Good | Good | Good | Good | Good | Good | Good | Fair | FAIR |
| Finkler (1997) | Good | Poor | Good | Good | Good | Fair | NA | Poor | NA | POOR |
| Keeler (1996) | Good | Poor | Fair | Poor | Poor | Poor | NA | Poor | NA | POOR |
| Spellacy (1991) | Poor | Fair | Fair | Poor | Fair | Poor | NA | Poor | NA | POOR |
| Shy (1981) | Poor | Poor | Fair | Poor | Poor | Poor | NA | Poor | NA | POOR |
| Chuang (1999) | None | Fair | Fair | Fair | Poor | Poor | NA | Good | Poor | POOR |
| Clark (2000) | Poor | Poor | Fair | Poor | Fair | Fair | Poor | Poor | NA | POOR |
| Traynor (1998) | Good | Fair | Good | Fair | Poor | Fair | NA | None | NA | POOR |
| Shorten (1998) | Good | Fair | Good | Fair | Fair | Fair | NA | Good | NA | POOR |
| Hadley (1986) | Fair | Good | Fair | Fair | Poor | Fair | NA | Poor | Poor | POOR |
| Flamm (1985) | Poor | Fair | Fair | Poor | Poor | Poor | NA | Poor | Poor | POOR |
| DiMaio (2002) | Poor | Fair | Fair | Fair | Fair | Fair | NA | Poor | Poor | POOR |
| RCT | |||||||||
| Study, Year | Random assignment | Allocation concealed | Groups similar at baseline/Maintenance of com-parable groups | Eligibility criteria specified | Blinded: Outcome Assessors/Care Provider/Patient | Intention-to-treat analysis | Report of attrition, cross-overs, etc | Loss to follow-up | Quality Score |
| Guidelines | |||||||||
| Bickell (1996) | Good | NA | Good/NA | Good | NA | Fair | NA | NA | FAIR |
| Lomas (1991) | Good | NA | Good/NA | Good | NA | Good | NA | NA | GOOD |
| CASE CONTROL | |||||||||
| Author, Year | Case definition explicit | State of the cases reliably assessed and validated | Accurate ascertainment of cases | Non-biased selection of cases/controls | Cases and controls comparable with respect to potential confounding factors | Measurement of exposure accurate and applied equally/Procedures applied equally | App attention to confounders | App. Stat Analy | Quality Score |
| Physician Characteristics | |||||||||
| Goldman (1993) | Good | Fair | Fair | Good | Poor | Fair/NA | Good | Poor | POOR |
| Goldman (1990) | Good | Good | NA | NA | Good | Fair | Poor | Good | POOR |
| Hospital Characteristics | |||||||||
| Goldman (1993) | Good | Fair | Fair | Good | Poor | Fair/NA | Good | Poor | Poor |
| Goldman (1990) | Good | Good | NA | NA | Good | Fair | Poor | Good | POOR |
| Case-Series | |||||||||
| Author, Year | Representative sample selected from a relevant population | Inclusion criteria explicit | Individuals entered the survey at a similar point in their disease progression | Follow-up long enough for important events to occur | Outcomes assessed using objective criteria/blinding used | Sufficient description of the series (subseries) and distribution of prognostic factors | Other important issues | Quality Score | |
| Health Care Resources | |||||||||
| Iglesias (1991) | Good | Good | NA | NA | Good | NA | Poor (small n) | POOR | |
| Hospital Characteristics | |||||||||
| Iglesias (1991) | Good | Good | NA | NA | Good | NA | Poor (small n) | POOR | |
| Kumar (1996) | Good | Good | NA | NA | Good | NA | Poor (small n) | POOR | |
| Raynor (1993) | Good | Good | NA | NA | Good | NA | Fair (smaller n) | FAIR | |
| Schlimmel (1992) | Good | Good | NA | NA | Good | NA | Fair (smaller n) | FAIR | |
| Walton (1993) | Good | Good | NA | NA | Good | Good | Fair (smaller n) | FAIR | |
| Hangsleben (1989) | Fair | Fair | NA | NA | Good | Fair | Poor (did not report ERCD in sample) | POOR | |
| Cross-Sectional Studies | |||||||||
| Guidelines | |||||||||
| Coulter (1995) | NA | Good | NA | NA | Fair (self report) | Poor | Poor (small n) | Poor | POOR |
| Author, Year | Comparable Groups/Clear inclusion criteria | Maintenance of comparable groups | Clear definition of comparison groups | Measures reliable, valid | Un-biased assessment of data | Loss/Drop-out rate | Follow-up long enough for outcomes to occur | Adjust for confounders | Quality Score |
|---|---|---|---|---|---|---|---|---|---|
| Resources | |||||||||
| Flamm (1994) | Good | NA | Fair | Fair | NA | NA | NA | Poor | POOR |
| Mor-Yosef (1990) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Phelan (1987) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Placek (1988A) | Poor | NA | Good | Fair | NA | NA | NA | Poor | POOR |
| Placek (1988B) | Poor | NA | Good | Fair | NA | NA | NA | Poor | POOR |
| Roberts (1997) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Stovall (1987) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Taffel (1991) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Boucher (1984) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Cowan (1994) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Data Strat & Bench Marks (1998) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Eriksen (1989) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Flamm (1988) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Hadley (1986) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Hanley (1996) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Curtin (1997) | Poor | NA | Fair | Fair | Good | NA | NA | Poor | POOR |
| Hook (1997) | Fair | NA | Fair | Good | Good | NA | NA | Poor | POOR |
| anonymous (1998) Data Strategies & Benchmarks, Oct. 154 | Poor | NA | Poor | Good | Good | NA | NA | Poor | POOR |
| Author, Year | Comparable Groups/Clear inclusion criteria | Maintenance of comparable groups | Clear definition of comparison groups | Measures reliable, valid | Unbiased assessment of data | Loss/Drop - out rate | Follow-up long enough for outcomes to occur | Adjust for potential confounders (obstetric conditions) | Quality Score |
| Insurance Type | |||||||||
| Stafford (1990) | Good | NA | Good | Good | NA | NA | NA | Good | GOOD |
| Stafford (1991) | Good | NA | NA | Good | NA | NA | NA | Good | GOOD |
| King (1994) | Good | NA | Good | Good | NA | NA | NA | Good | GOOD |
| Gregory (1999) | Good | NA | Good | Good | NA | NA | NA | Fair | FAIR |
| Santerre (1996) | Fair | NA | Good | Good | NA | NA | NA | Good | FAIR |
| Oleske (1998) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Rageth (1999) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Wagner (1999) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Placek (1988A) | Poor | NA | Good | Fair | NA | NA | NA | Poor | POOR |
| Skelton (1997) | Good | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Curtin (1997) | Poor | NA | Fair | Fair | Good | NA | NA | Poor | POOR |
| Miller (1992) | Fair | NA | Fair | Good | Good | NA | NA | Poor | POOR |
| Physician Charactreristics | |||||||||
| Davis (1994) | Poor | NA | Fair | Good | NA | NA | NA | Poor | POOR |
| Barnsley (1990) | Poor | NA | Poor | Fair | NA | NA | NA | Poor | POOR |
| Coco (2000) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Deutchman (1995) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Hueston (1995) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Miller (1995) | NA | NA | NA | Good | NA | NA | NA | Poor | POOR |
| Sinusas (2000) | Poor | NA | NA | Good | NA | NA | NA | Poor | POOR |
| Stone (1996) | NA | NA | NA | Fair | NA | NA | NA | Poor | POOR |
| Berkowitz (1989) | Poor | NA | Adequate | Good | NA | NA | NA | Poor | POOR |
| Harrington (1997) | Fair | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Hueston (1994) | NA | NA | NA | Fair | Good | NA | NA | Poor | POOR |
| Hospital Characteristics | |||||||||
| Gregory (1999) | Good | NA | Good | Good | NA | NA | NA | Good | GOOD |
| Santerre (1996) | Fair | NA | Good | Good | NA | NA | NA | Good | FAIR |
| McMahon (1996) | Good | NA | Good | Good | NA | NA | NA | Good | GOOD |
| King (1994) | Good | NA | Good | Good | NA | NA | NA | Good | GOOD |
| Stafford (1991) | Good | NA | NA | Good | NA | NA | NA | Good | GOOD |
| Barnsley (1990) | Poor | NA | Poor | Fair | NA | NA | NA | Poor | POOR |
| Shiono (1987) | Fair | NA | NA | Good | NA | NA | NA | Fair | FAIR |
| Whitsel (2000) | Good | NA | NA | Good | NA | NA | NA | Poor | POOR |
| Gregory (1999) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Mor-Yosef (1990) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Skelton (1997) | Good | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Paterson (1991) | Good | NA | Good | Good | Good | NA | NA | Poor | POOR |
| Curtin (1997) | Poor | NA | Fair | Fair | Good | NA | NA | Poor | POOR |
| Sieck (1997) | Poor | NA | Good | Fair | Good | Poor | NA | Poor | POOR |
| Placek (1988A) | Poor | NA | Good | Fair | NA | NA | NA | Poor | POOR |
| Legal Factors | |||||||||
| King (1994) | Good | NA | Good | Good | NA | NA | NA | Good | GOOD |
| Studnicki (1997) | Good | NA | Good | Good | NA | NA | NA | Good | GOOD |
| Guidelines | |||||||||
| Santerre (1996) | Fair | NA | Good | Good | NA | NA | NA | Good | FAIR |
| Lomas (1989) | Fair | NA | Good | Good | NA | NA | NA | Fair | FAIR |
| Myers (1993) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Sanchez-Ramos (1990) | Poor | NA | Good | Good | NA | NA | NA | Poor | POOR |
| Myers (1988) | Poor | NA | Adequate | Good | NA | NA | Adequate | Poor | Poor |
| Porreco (1985) | Poor | NA | Adequate | Good | NA | NA | Adequate | Poor | POOR |
Call Participants:
Stanley Zinberg, MD, MS, FACOG
Vice President for Practice Activities
American College of Obstetricians and Gynecologists
Washington, DC
Watson Bowes, MD
Professor Emeritus of Obstetrics and Gynecology
University of North Carolina at Chapel Hill
Chapel Hill, North Carolina
Benjamin Sachs, MB, BS, DPH, FACOG
Obstetrician-Gynecologist-in-Chief
Beth Israel Deaconess Medical Center
Boston, Massachusetts
Evan Myers, MD, MPH
Assistant Professor of Obstetrics and Gynecology
Duke University Medical Center
Durham, North Carolina
Eric Wall, MD, MPH
Clinical Associate Professor of Family Medicine
Oregon Health & Science University
Vice President and Regional Director, Lifewise and Blue Cross/Blue Shield of Alaska Medical Director
Portland, Oregon
Fay Menacker, DrPH, RN, CPNP
Division of Vital Statistics
National Center for Health Statistics
Hyattsville, Maryland
Jun “Jim” Zhang, PhD, MD
Division of Epidemiology, Statistics and Prevention Research
National Institute of Child Health and Human Development
National Institutes of Health
Bethesda, Maryland
David Atkins, MD, MPH
Chief Medical Officer
Center for Practice and Technology Assessment
Agency for Healthcare Research and Quality
Bethesda, Maryland
Mark Helfand, MD, MPH
Director, Oregon Evidence-based Practice Center
Associate Professor of Medicine and Medical Informatics & Outcomes Research,
Oregon Health & Science University
Jeanne-Marie Guise MD, MPH
Assistant Professor of Obstetrics and Gynecology and of Medical Informatics and Outcomes Research
Oregon Health & Science University
Portland, Oregon
A conference call was held on September 5, 2002 to discuss terminology for uterine rupture. Specifically, some peer reviewers of the VBAC evidence report were concerned with terminology used in the draft report. If the members of the call could reach consensus on appropriate terminology, the final evidence report would be revised to reflect this consensus, as possible.
The draft evidence report found inconsistencies and ambiguities in terminology used for uterine rupture. Call participants were directed to a table of terminologies used for uterine rupture among several studies in the evidence report. We discussed the challenges in studying the epidemiology of the condition due to these inconsistencies. We also discussed the inability to identify predictors for morbidity due to uterine rupture when they were embedded in the definition of uterine rupture. Motivated by these issues, we presented the terminology used in the draft report to start discussion about more precise terminology.
One alternative terminology proposed was complete rupture, incomplete rupture, or window. Members of the call were pleased with the fact that incomplete and complete would provide a clear anatomic description. The majority felt that there was not a need to distinguish between incomplete rupture and window. There was some concern that these terms did not provide a description for the severity of the condition. Although the severity of the condition is important, indicating the origin or cause of uterine rupture is needed to establish contributing factors. One suggestion was to use the following terms:
Symptomatic Uterine Rupture Not Related to a Cesarean Scar
Symptomatic Uterine Rupture Related to a Cesarean Scar
Asymptomatic Uterine Rupture Not Related to a Cesarean Scar
Through discussion it was suggested that the descriptors, clinically significant or consequential, would be more appropriate than a/symptomatic since they are easier to define. However, questions as to what “clinically significant” meant were raised. Some members of the call considered any uterine rupture as “clinically significant” since the patient would need an unexpected surgical procedure and may have delivered her baby via an unintended route. Also, some mentioned that any uterine rupture could also lead to significant morbidity if left untreated.
It was then suggested that outcomes should not be used to diagnosis/describe a uterine rupture. In order to accurately determine and record the frequency of uterine rupture, it must be kept in simple terms. Several members of the call agreed with this suggestion. There was some agreement on using the following terms:
Incomplete uterine rupture of a cesarean scar - separation that was not completely through all layers of the uterine wall (e.g., serosa intact)
Complete uterine rupture of a cesarean scar - entire thickness of the uterine wall including visceral serosa (with or without expulsion of part or complete extrusion of fetal-placental unit)
The evidence report is constrained by the data provided within the studies. The text was revised to replace cesarean disruption with uterine rupture of a cesarean scar. Because few studies presented data exclusively for complete or incomplete rupture, the authors were not able to present these data specifically in the report. The text has included the table of terminology used among studies (referred to in the call) and a discussion of the difficulties raised by inconsistent terminology to pave the way for future research with explicit outcomes.
Although full consensus was not reached on terminology, the call was the first step in bringing together experts in the field to discuss this issue. Future work can be done to arrive at a consensus and potentially shape the field by uniformity in reporting terminology.
| A | Augmentation |
| AHRQ | Agency for Healthcare Research and Quality |
| AI | Augmentation/Induction |
| BW | Birthweight |
| CD | Cesarean Delivery |
| CI | Confidence Interval |
| CPD | Cephalopelvic Disporportion |
| CPDI | Cephalopelvic Disproportion Index |
| ECV | External Cephalic Version |
| EFW | Estimated Fetal Weight |
| EPC | Evidence-based Practice Center |
| ERCD | Elective Repeat Cesarean Delivery |
| FHT | Fetal Heart Tracing |
| FP | Family Medicine |
| FPI | Fetal Pelvic Index |
| FTOL | Failed Trial of Labor |
| FTP | Failure to Process |
| g | Grams |
| GA | Gestational Age |
| hrs | Hours |
| I | Induction |
| IUGR | Intrauterine Growth Restriction |
| LOS | Length of Stay |
| LTCS | Lower segment Transverse Cesarean Section |
| MD | Medical Doctor |
| mos | Months |
| NA | Not Applicable |
| NPV | Negative Predictive Value |
| NS-NR | Non-Significant/ actual p-value not reported |
| OR | Odds Ratio |
| OR(a) | Adjusted Odds Ratio |
| PCD | Previous Cesarean Delivery |
| PIH | Pregnancy Induced Hypertension |
| PLTCS | Previous Low Traverse Cesarean Section |
| PPV | Positive Predictive Value |
| PROM | Premature Rupture of Membranes |
| RCT | Randomized Clinical Trial |
| RR | Relative Risk |
| SD | Standard Deviation |
| SL | Spontaneous Labor |
| TOL | Trial of Labor |
| UR | Uterine Rupture |
| VBAC | Vaginal Birth After Cesarean Delivery |
| VD | Vaginal Delivery |
| wks | Weeks |
| XRP | X-ray Pelvimetry |
| yrs | Years |