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Nicholson WK, Wilson LM, Witkop CT, et al. Therapeutic Management, Delivery, and Postpartum Risk Assessment and Screening in Gestational Diabetes. Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Mar. (Evidence Reports/Technology Assessments, No. 162.)

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Therapeutic Management, Delivery, and Postpartum Risk Assessment and Screening in Gestational Diabetes.

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2Methods

The ACOG has requested an evidence report to review and synthesize published literature regarding the intrapartum management and postpartum followup of women with gestational diabetes. Our EPC established a team and a work plan to develop the evidence report. The project consisted of recruiting technical experts, formulating and refining the specific questions, performing a comprehensive literature search, summarizing the state of the literature, constructing evidence tables, synthesizing the evidence, grading the strength of the evidence, and submitting the report for peer review.

Topic Development

The topic for this report was nominated in a public process. At the beginning of the project, we recruited a panel of external technical experts to provide input at key steps, including the selection and refinement of the questions to be examined. The panel included external experts who have strong expertise in gestational diabetes (see Appendix A a).

We worked with the technical experts and representatives of the AHRQ and ACOG to develop the key questions that are presented in the Conceptual Framework and Key Questions section of Chapter 1 (Introduction). The key questions focused on: (1) the risks and benefits of using oral diabetes medications and any type of insulin to treat gestational diabetes affecting the mother and neonate, (2) the risks and benefits of medically indicated cesarean delivery and the choice of timing of induction for the mother and neonate, (3) the risk factors associated with the short-term and long-term development of type 2 diabetes following a pregnancy with gestational diabetes, and (4) the performance characteristics (i.e., sensitivity, specificity, and reproducibility) of tests for diagnosing type 2 diabetes when conducted in postpartum gestational diabetes patients.

Search Strategy

Searching the literature involved identifying reference sources, formulating a search strategy for each source, and executing and documenting each search. We also searched for medical subject heading (MeSH) terms that were relevant to gestational diabetes. We used a systematic approach for searching the literature, with specific eligibility criteria, to minimize the risk of bias in selecting articles for inclusion in the review. The systematic approach was intended to help identify gaps in the published literature.

Our comprehensive search plan included electronic and hand searching. We ran searches of four databases, MEDLINE® (1950 through January 2007), EMBASE® (1974 through January 2007), The Cochrane Central Register of Controlled Trials (CENTRAL; Issue 1, 2007), and the Cumulative Index to Nursing & Allied Health Literature (CINAHL®; 1982 through January 2007), to identify primary literature on the association of intrapartum management and postpartum followup of women with gestational diabetes with various maternal and neonatal outcomes. Hand searching for possibly relevant citations took two forms. First, from our electronic search, we identified the 13 journals (see Appendix B a) that were most likely to publish articles on this topic (i.e., these journals had the highest number of abstracts and articles included in the review). We scanned the table of contents of each issue of these journals for relevant articles from August 2006 through January 2007. For the second form of hand searching, reviewers received eligible articles and flagged references of interest for the team to compare to the existing database.

Search strategies specific to each database were designed to enable the team to focus the available resources on articles that were the most likely to be relevant to the key questions. We initially developed a core strategy for MEDLINE®, accessed via PubMed®, based on an analysis of the MeSH terms and text words of key articles identified a priori. The PubMed® strategy formed the basis for the strategies developed for the other electronic databases (see Appendix C a).

The results of the searches were downloaded and imported into ProCite® version 5 (the Thompson Corporation, Stamford, CT). We used the duplication scan feature in ProCite® to delete citations already retrieved. From ProCite®, the articles were uploaded to SRS 4.0 (TrialStat! Corporation, Ottawa, Ontario, Canada), a Web-based software package developed for systematic review data management. This database was also used to store citations in portable document format (PDF) and to track the search results at the title review, abstract review, article inclusion/exclusion, and data abstraction levels. A list of excluded articles is presented in Appendix D a.

Study Selection

The study team scanned all titles. Two independent reviewers conducted title scans in a parallel fashion. For a title to be eliminated at this level, both reviewers had to indicate that it was obviously ineligible. If the two reviewers did not agree on the eligibility of an article, it was promoted to the next level (see Appendix E a, Title Review Form). The title review phase was designed to capture as many studies as possible that reported on the association of intrapartum management and postpartum followup of women with gestational diabetes with various maternal and neonatal outcomes. All titles that were identified as potentially addressing these issues were promoted to the abstract review phase.

Abstracts were reviewed independently by two investigators. Abstracts were excluded if both investigators agreed that the article met one or more of the following exclusion criteria: (1) not written in English; (2) did not include any human data; (3) contained no original data that was published in a peer-reviewed journal (i.e., was a meeting abstract, editorial, commentary, or letter); (4) did not evaluate women with gestational diabetes; (5) was a case report or case series; (6) did not base the diagnosis of gestational diabetes on either a 3-hr, 100-gm OGTT or a 2-hr, 75-gm OGTT; (7) did not evaluate an outcome relevant to the key questions (see Table 1); (8) did not include a medication of interest for Key Question 1; (9) did not have an appropriate comparison group for Key Questions 1 or 2; or (10) did not apply to a key question. We included publications that did not explicitly state the test used to diagnosis gestational diabetes if we were able to confirm through referenced publications or through personal communications with the author that the study used one of the accepted diagnostic tests. Differences of opinion regarding abstract eligibility were resolved through consensus adjudication. At this level of review, the reviewers were also asked to identify to which key question(s) the article might apply if it was eligible for review.

Table 1. List of outcomes reviewed.

Table 1

List of outcomes reviewed.

Because of the broad array of potentially eligible articles obtained at the abstract review phase, full articles initially selected for review underwent another independent parallel review by the investigators to determine whether the articles should be included in the full data abstraction. In addition to the exclusion criteria used for the abstract review, studies were excluded if less than 90 percent of the sample was diagnosed with gestational diabetes and there was no separate analysis for gestational diabetes patients. We limited the studies for Key Question 1 to all randomized controlled trials (RCTs) and observational studies that compared two types of treatment. For Key Question 1, we decided not to include observational studies that compared either an oral diabetes medication or insulin to diet, because most of these studies had a selection-by-indication bias (i.e., treatment was determined by the severity of the diabetes).

At this phase of the review, the investigators determined which of the key questions each article addressed (see Appendix E, Article Inclusion/Exclusion Form). If the articles were still deemed to have applicable information, they were included in the full data abstraction. Differences of opinion regarding article eligibility were resolved through consensus adjudication.

Data Abstraction

We used a systematic approach for extracting data to minimize the risk of bias in this process. By creating standardized forms for data extraction, we sought to maximize consistency in identifying all pertinent data available for synthesis.

Each article underwent double review by study investigators for full data abstraction and assessment of study quality. For all data abstracted from studies, we used a sequential review process. In this process, the primary reviewer completed all data abstraction forms. The second reviewer checked the first reviewer's data abstraction forms for completeness and accuracy. Reviewer pairs were formed to include personnel with both clinical and methodological expertise. A third reviewer re-reviewed a random sample of articles by the first two reviewers to ensure consistency in the classification of the articles. Reviewers were not masked to the articles' authors, institutions, or journal.21 In most instances, data were directly abstracted from the article. If possible, relevant data were also abstracted from figures. Differences of opinion were resolved through consensus adjudication. For assessments of study quality, each reviewer independently judged study quality and rated items on quality assessment forms (see Appendix E, Data Abstraction Review Forms).

For all included articles, reviewers abstracted information regarding the general study characteristics (e.g., exclusion criteria, study design, study period and followup, and country) and study participants (e.g., maternal age, race, weight/body mass index [BMI], parity/gravida, gestational age, method of gestational diabetes management, and the type, timing, and results of the OGTT). For articles that applied to Key Questions 1 and 2, we abstracted information on the type of intervention, the outcomes measures and the method of ascertainment, and the results of each outcome, including the measures of variability. For articles that applied to Key Question 3, we abstracted information on the diagnosis of type 2 diabetes, the length of followup, the covariates considered and included in the models, and the measure of association and variability. For articles that applied to Key Question 4, we abstracted information on the reference test, the comparison test, the length of followup, and the results of the tests.

All information from the article review process was entered into the SRS 4.0 database by the individual completing the review. Reviewers entered comments into the system whenever applicable. The SRS 4.0 database was used to maintain and clean the data, as well as to create detailed evidence tables and summary tables (see Appendix F and Summary Tables).

Study Quality Assessment

The study aspects considered in our quality assessment varied according to the question being addressed and the type of study design. As part of our dual, independent review of study quality, we judged articles on several aspects of each study type's internal validity. Quality assessment of trials for Key Questions 1 and 2 was based on the Jadad criteria22 and included: (1) appropriateness of the randomization scheme, (2) appropriateness of the blinding, and (3) description of withdrawals and drop-outs. For each trial, we awarded a score from 5 (high quality) to 0 (low quality). Quality assessment of observational studies for Key Questions 1, 2, and 3 involved selecting elements from the Standards for Reporting of Observational Studies (STROBE) checklist of the reporting of observational studies;23 it included items about reporting on the hypotheses, inclusion/exclusion criteria, study population, power and sample size calculations, definition of outcomes, loss to followup, and missing data. Quality assessment of the diagnostic test studies for Key Question 4 was designed by selecting elements from the Standards for Reporting of Diagnostic Accuracy (STARD) Initiative24 and included items about reporting of the sampling design, loss to followup, information about diagnostic accuracy, verification of positive and negative tests, independent interpretation of tests, reproducibility, and subgroup analyses.

Data Synthesis

For each key question, we created a set of detailed evidence tables containing all the information extracted from the eligible studies. The investigators reviewed the tables and eliminated items that were rarely reported.

We conducted meta-analyses when there were sufficient data (three or more studies) and the studies were homogeneous with respect to key variables (population characteristics, study duration, intervention/exposure/comparison tests, and length of followup). When the data were not sufficient to combine the studies in a meta-analysis, we prepared a qualitative summary of the results.

In the meta-analysis, we recorded the mean difference in infant birth weight between groups, along with its measure of dispersion. We calculated a pooled estimate (weighted mean difference) of infant birth weight from the eligible RCTs using a random effects model with the DerSimonian and Laird formula for calculating between-study variance.25 The random effects model was used because unmeasured heterogeneity was likely to exist among the trials.

We assessed heterogeneity among the trials considered for meta-analysis using a standard chi-squared test and a significance level of alpha ≤ 0.10. We also examined heterogeneity among studies with an I2 statistic, which describes the variability in effect estimates that is due to heterogeneity rather than random chance.26 A value greater than 50 percent may be considered to have substantial variability.

All statistical analyses were conducted using STATA (Intercooled, version 8.2, StataCorp, College Station, TX).

Data Entry and Quality Control

Initial data were abstracted by the investigators and entered directly into Web-based data collection forms using SRS® 4.0 (TrialStat! Corporation, Ottawa, Ontario, Canada). After a second reviewer reviewed the data, the adjudicated data were re-entered into the Web-based data collection forms by the second reviewer. Second reviewers were generally more experienced members of the research team, and one of their main priorities was to check the quality and consistency of the first reviewers' answers. In addition to the second reviewers checking the consistency and accuracy of the first reviewers, a lead investigator examined a random sample of the reviews to identify problems with the data abstraction. If problems were recognized in a reviewer's data abstraction, the problems were discussed at a meeting with the reviewers. In addition, research assistants used a system of random data checks to assure data abstraction accuracy.

Rating the Body of Evidence

At the completion of our review, we graded the quantity, quality, and consistency of the best available evidence addressing the key questions by adapting an evidence-grading scheme recommended by the GRADE Working Group.27 We assessed the strength of the study designs, with RCTs considered to be best, followed by non-randomized controlled trials and observational studies. To assess the quantity of evidence, we focused on the number of studies with the strongest design. We also assessed the quality and consistency of the best available evidence, including assessment of the limitations affecting individual study quality (using the individual study quality assessments), certainty regarding the directness of the observed effects in the studies, the precision and strength of the findings, and the availability (or lack) of data to answer the key question. We classified evidence bodies pertaining to the key questions into the following categories: (1) “high” grade, indicating confidence that further research is very unlikely to change our confidence in the estimated effect in the abstracted literature; (2) “moderate” grade, indicating that further research is likely to have an important impact on our confidence in the estimates of effects and may change the estimates in the abstracted literature; (3) “low” grade, indicating the further research is very likely to have an important impact on confidence in the estimates of effects and is likely to change the estimates in the abstracted literature; (4) “very low” grade, indicating any estimate of effect is very uncertain; and (5) “insufficient” grade, indicating the lack of enough evidence to make any estimate of effect.

Peer Review

A draft of the completed report was sent to the technical experts and peer reviewers, as well as to the representatives of AHRQ. In response to the comments of the technical experts, peer reviewers, and AHRQ, revisions were made to the evidence report, and a summary of the comments and their disposition was submitted to AHRQ.

Appendixes cited in this report are provided electronically at: http://www.ahrq.gov/clinic/tp/gdmparttp.htm

Footnotes

a

Appendixes cited in this report are provided electronically at: http://www.ahrq.gov/clinic/tp/gdmparttp.htm

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