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Haemophilia. Author manuscript; available in PMC 2012 Jan 1.
Published in final edited form as:
PMCID: PMC2990788


Margaret V. Ragni, M.D., M.P.H.,1,2 Charity G. Moore, Ph.D., M.S.P.H.,3 Kakra Soadwa, M.D., M.P.H.,1,* Michael A. Nalesnik, M.D.,4 Albert B. Zajko, M.D.,5 Andrea Cortese-Hassett, Ph.D.,4,6 Theresa L. Whiteside, Ph.D.,7 Suzanne Hart, Ph.D.,8,** Adriana Zeevi, Ph.D.,4 Jie Li, M.S.,3 Obaid S. Shaikh, M.D.,9 and The HHH Study Group



Hepatitis C virus (HCV) is the major cause of liver disease in hemophilia. Few data exist on the proportion with liver fibrosis in this group after long-term HCV and HIV co-infection.


We conducted a cross-sectional multi-center study to determine impact of HIV on the prevalence and risk factors for fibrosis in hemophilic men with chronic hepatitis C.


Biopsies were independently scored by Ishak, Metavir, and Knodell systems. Variables were tested for associations with fibrosis by logistic regression and receiver operating curves (ROC).


Of 220 biopsied HCV(+) men, 23.6% had Metavir ≥F3 fibrosis, with higher mean Metavir fibrosis scores among HIV/HCV co-infected than HCV mono-infected, 1.6 vs. 1.3 (p=0.044). Variables significantly associated with fibrosis included AST, ALT, APRI score (AST/ULN×100/platelet ×109/L), alpha-fetoprotein (all p<0.0001), platelets (p=0.0003), and ferritin (p=0.0008). In multiple logistic regression of serum markers, alpha-fetoprotein, APRI, and ALT were significantly associated with ≥ F3 fibrosis, AUROC=0.77 (95%CI 0.69, 0.86). Alpha-fetoprotein, APRI, and ferritin were significant in HIV(−), (AUROC 0.82 (95%CI 0.72, 0.92), and alpha-fetoprotein and platelets in HIV(+) (AUROC=0.77 (95%CI 0.65, 0.88). In a multivariable model of demographic and clinical variables, transformed (natural logarithm) of alpha-fetoprotein (p=0.0003), age (p=0.006), and HCV treatment (p=0.027) were significantly associated with fibrosis.


Nearly one-fourth of hemophilic men have Metavir ≥ 3 fibrosis. The odds for developing fibrosis are increased in those with elevated alpha-fetoprotein, increasing age, and past HCV treatment.

Keywords: Hepatitis C, Fibrosis, Hemophilia, Transfusion, Metavir, Receiver operating curve


Hepatitis C (HCV) is the most common cause of chronic liver disease and the leading cause of death in individuals with hemophilia. Of the 90% of hemophilic men exposed to HCV through clotting factor concentrates prior to AIDS [1], it has been estimated that 20% have cirrhosis [2], similar to other risk groups [3,4]. However, the extent of fibrosis among hemophilic men with long-term HIV infection is not known.. This is an important consideration, given the competing effects of the HIV virus itself, which accelerates liver disease progression [5] and upregulates cytokines promoting liver fibrosis [68]; and the effects of highly active antiretroviral therapy (HAART), which improves HIV survival [9], slows HCV progression [1012] and improves post-transplant survival in co-infected individuals [13]. Although liver biopsy is the gold standard for assessment of liver disease [14], few hemophilic men undergo this procedure, even by the less invasive transjugular route [5]. Thus, noninvasive markers of hepatic fibrosis [1622], e.g. AST, ALT, platelet count, and combinations, have been increasingly used to predict fibrosis [19]. Few studies, however, are powered to assess markers in HCV(+) hemophilic men with and without HIV infection. [23]. Moreover, little is known about the role of cytokine upregulation by HIV [68] or cytokine genotype [2426] in predicting fibrosis in co-infected individuals. We, therefore, designed a cross-sectional study to determine prevalence and risk factors for fibrosis.

Patients and methods


A total of 781 men with hemophilia A or B, ≥18 years of age, with a positive HCV antibody test, from 34 U.S. hemophilia treatment centers were enrolled on the HIV Impact on Hepatitis C in Hemophilia (HHH) Study. Study subjects were enrolled on this NHLBI-funded cross-sectional, multi-center study between April 2002 and December 2007, during routine comprehensive hemophilia center clinic visits. All subjects provided signed informed consent in accordance with the Declaration of Helsinki. The protocol and informed consent were approved by the Clinical Translational Research Center (CTRC) Advisory Committee and Institutional Review Board (IRB), at the University of Pittsburgh (headquarters), and all participating institutions. Approved consent forms from participating institutions were reviewed by the Coordinating Center (M.V.R.) to assure inclusion of health information protection (HIPAA) and safety procedures regarding liver biopsy. Duration of HCV infection was based on data documenting HCV infection occurs in those with hemophilia with the first blood product exposure [33], which occurs within the first year of life for most such patients. Dates of HIV seroconversion were based on previously published studies establishing 1982 as median year of seroconversion for hemophilia A and 1983 for hemophilia B [1].

Liver histology and quantification of fibrosis

Each patient was asked to undergo an optional liver biopsy at baseline, or to provide permission to review recent liver biopsy slides and blocks. Only 40 subjects underwent liver biopsy during study; 180 already had undergone liver biopsy and refused to undergo a repeat biopsy due to bleeding risk. The 220 biopsies, including 40 fresh tissue and 180 slides and blocks, were coded at each site, shipped to the University of Pittsburgh coordinating center, and independently reviewed by the study pathologist (M.A.N.) and scored by Knodell [27], Ishak [28], and Metavir [29] classification systems, with Ishak fibrosis 0 to 6, Metavir fibrosis F0 to F4, http://www.xcellpath.com/healthcare/other/other_staging_liver.htm. Of the biopsies, 66 (30.0%) were performed within 12 months; 24 (10.9%) within 24 months; 35 (15.9%) within 36 months; 25 (11.4%) within 48 months; 14 (6.4%) within 60 months; and the remainder, 56 (25.4%) between 60 and 180 months of enrollment. By approach, 119 (54.1%) of the biopsies were performed by the percutaneous route, 84 (38.2%) by the transjugular route, 16 (7.3%) intraoperatively, and one (0.4%) was obtained at autopsy.

Serum fibrosis markers

On the day of study enrollment, demographic, clinical information, and a one-time blood sample was obtained for ALT, AST, alpha-fetoprotein, ferritin, HCV antibody, HCV viral load, HCV genotype, HIV antibody, HIV viral load, CD4 count, platelet count, hemoglobin, and cytokines TGF-β, IL-6, IL-10, TNF-α, and IFN-γ. APRI score was calculated as AST/ULN x 100/platelet count 109/L.

Cytokine immunoassay, mRNA, and promoter genotype

Plasma cytokine immunoassay (TGF-β, IL-6, IL-10, TNF-α, and IFN-γ) was measured by enzyme-linked immunosorbent assay (Quantikine R&D Systems, Minneapolis, MN) [30, 31]. Cytokine mRNA (TGF-β, IL-6, IL-10, TNF-α, and IFN-γ) was measured on liver tissue by ribonuclease protection assay (Riboquant, Pharmingen, San Diego CA) with radiolabeled bands determined by densitometry [26]. Genomic DNA was extracted from peripheral venous blood samples using the QIAamp DNA Blood Midi KitR, followed by whole genome amplification using the REPLI-gR Mini/Midi Kit (Qiagen Inc, Valencia CA). The allelic polymorphisms of IL-6 (174 G/C) and IL-10 (1082G/A, 819C/T, 592C/A), and TGF-β (C/T codon 10, C/G codon 25) were identified by PCR with sequence specific primers (PCR-SSP) using a five-cytokine polymorphism kit (One Lambda Inc, Canoga Park CA) [32].

Statistical analysis

Subjects with and without a liver biopsy were compared on demographic, behavioral, and clinical variables to assess the generalizability of the findings. Wilcoxon rank sum test was used for continuous variables and chi-square, or Fisher’s exact, test was used for categorical variables. Using the same statistical tests, subjects with and without HIV infection were compared on the same variables to establish differences between the two groups that might be important to consider in multivariable analyses. Spearman rank correlation was used to determine the association between the biochemical markers (AST, ALT, platelet count, AST/ALT, APRI ferritin, alpha fetoprotein) and fibrosis score [29] for each classification system for all subjects and stratified by HIV status. The same analysis was used in a subset of subjects with cytokine measurements to determine the association between cytokine mRNA (TGF-β, IL-6, IL-10, TNF-α, and IFN-γ). Logistic regression and the area under the receiver operating curves (AUROC) were used to determine the diagnostic accuracy of the biochemical markers for Metavir F3-F4 fibrosis [29]. Although time between enrollment and biopsy was not significantly different between those with Metavir F3-F4 fibrosis and those without, two types of sensitivity analyses were conducted to assess its impact on biochemical marker association with Metavir F3-F4 fibrosis. In the first sensitivity analysis, we stratified by time between enrollment and biopsy date (<3, ≥ 3 years) to compare the regression coefficients and AUROCs. In the second sensitivity analysis, regression models were conducted in all subjects, controlling for time between enrollment and biopsy. No impact was noted (data not shown) in terms of inference for the associations of biochemical markers with Metavir F3-F4 fibrosis: therefore, analyses are presented from all subjects. Multiple logistic regression was used to determine demographic, clinical, behavioral, and laboratory variables significantly associated with fibrosis. Variables were considered for inclusion in the final model if they were significant as univariates at the 0.2 level and significant at the 0.05 level in multivariable models within each type of variable. Among subjects with HIV, the association between HAART and presence of fibrosis was tested by Fisher’s exact test for categoric variables. The median fibrosis score by HAART therapy was assessed by Wilcoxon rank sum test, comparing those treated vs. untreated. The same procedures were used to test the impact of HCV treatment on fibrosis among all biopsied subjects, irrespective of HIV status. All data analyses were performed using SAS 9.1.3 software package (SAS Institute, Cary NC), and receiver operating curves (ROC) were analyzed with Stata software (StataCorp LP, College Station TX).


Baseline characteristics and liver fibrosis scores

Of 781 HCV(+) hemophilic men enrolled in the study, 220 (28.2%) underwent liver biopsy (Table 1). Those who underwent biopsy were more likely to be older, Caucasian, HIV(+), to have a detectable HCV viral load, and to have received HCV antiviral therapy than those not biopsied. Of the subjects undergoing biopsy, 43.6% received interferon (IFN) and/or ribavirin (RBV) therapy, and, among HIV(+) biopsied subjects, 80.7% received highly active antiretroviral therapy (HAART). Co-infected subjects also had lower platelet counts (p<0.001) and higher AST (p=0.002) than mono-infected subjects. Of all biopsied subjects, 82 (38.2%) had Ishak grade > 3 fibrosis, higher among HIV(+), 46.2%, than HIV(−), 32.3%, p=0.035. A total of 52 (23.6%) had ≥ F3 Metavir fibrosis, and the Metavir score was higher in co-infected than HCV mono-infected subjects, 1.6 ± 1.2 (standard deviation) vs. 1.3 ± 1.2, p=0.044 (Table 2).

Table 1
Characteristics of HCV (+) Hemophilic Men Enrolled on Study
Table 2
Characteristics of HCV (+) Hemophilic Men Undergoing Liver Biopsy

Correlation between serum biomarkers and fibrosis scoring systems

Overall, AST, ALT, platelet count, APRI, ferritin, and alpha-fetoprotein were significantly associated with fibrosis by the Knodell, Ishak, and Metavir systems (Table 3). This was also true for the HIV(−) subgroup, while among HIV(+), only AST, ferritin, and alpha-fetoprotein were positively correlated with all three scoring systems. In all groups, alpha-fetoprotein was the variable most strongly associated with Metavir fibrosis (Table 3).

Table 3
Fibrosis in HCV (+) Hemophilic Men: Spearman Correlation Coefficients Between Biomarkers and Histologic Scoring Systems

Relationship between HAART therapy and fibrosis

Among HIV(+) subjects, a significantly greater proportion of those treated with HAART, 23 of 75 (30.7%), had Metavir ≥ F3 fibrosis than those not receiving HAART, 3 of 18, 16.7%, p=0.380. There was also no difference between median Metavir fibrosis score between subjects treated with HAART and untreated (data unshown) p=0.578.

Relationship between HCV infection, HCV treatment, and fibrosis

Duration of HCV was greater in those with Metavir F3-F4 fibrosis than F0-F2, 44.5 ± 11.2 vs. 38.8 ± 12.2 years, p=0.0014. Significantly more of those receiving HCV treatment (interferon ± ribavirin), 31 of 96 (32.3%), had Metavir ≥ F3 fibrosis than those not receiving HCV treatment, 21 of 123 (17.1%), p=0.009. Median Metavir fibrosis score was higher among HCV-treated subjects, median (25th, 75th percentile), 1.0 (1.0, 3.0) compared to untreated subjects, 1.0 (0.0, 2.0), p=0.004.

Logistic regression model and predictors of Metavir ≥F3 fibrosis

In univariate logistic regression, alpha-fetoprotein was most highly associated with Metavir ≥F3, overall, and for HIV(+) and HIV(−) groups, AUROC=0.76, 0.71, and 0.80, respectively, Table 4. In multiple logistic regression models, APRI, ALT, and alpha-fetoprotein were significantly associated with F3-F4 fibrosis, AUROC=0.77 (95% CI 0.69, 0.86, Figure 1a. Among HIV(+), platelets and alpha-fetoprotein were predictors of Metavir ≥F3 fibrosis, AUROC=0.77 (95% CI 0.65, 0.88), Figure 1b. Among HIV(−), APRI, ferritin, and alpha-fetoprotein were significant predictors of Metavir ≥F3 fibrosis, AUROC=0.82 (95% CI 0.72, 0.92), Figure 1c. Since APRI is a function of AST and platelet count, AUROC curves were assessed with just APRI, and considering AST and platelet count as separate variables. Overall, when APRI was excluded from the model, platelet count was significantly associated with fibrosis, but not AST (data not shown).

Figure 1Figure 1Figure 1
Metavir ≥ F3 Fibrosis in Hemophilic Men with Hepatitis C
Table 4
Fibrosis in HCV (+) Hemophilic Men: Spearman Correlation Coefficients Between Cytokines and Histologic Scoring Systems

Cytokine analysis

IL-6 mRNA was negatively associated with all three classification systems, overall and stratified by HIV status. IL-10, TNF-α, and IFN-γ mRNA showed a similar negative association, with all classification systems, in all individuals and in those who were HIV(−), Table 5. Neither cytokine ELISA nor cytokine promoter genoptyes was associated with fibrosis in any group (data not shown).

Table 5
Logistic Regression Coefficients for Metavir ≥ F3 Fibrosis in Hemophilic Men with HCV Infection*

Multivariable model

In multiple logistic regression, age at enrollment, HCV treatment, transformed (natural logarithm, ln) platelet count, and transformed (natural logarithm, ln) alpha-fetoprotein were positively associated with Metavir ≥ F3 fibrosis, Table 6. Despite the effect of HIV on severiy of fibrosis (above), HIV was not significantly associated with fibrosis, nor did it alter the association among the variables with fibrosis in the final model.

Table 6
Multivariable Model for Metavir ≥ F3 Fibrosis in Hemophilic Men with HCV Infection*


Few studies have documented the histologic impact of HIV infection on HCV infection in those with hemophilia, a unique population that differs from other risk groups in their early acquisition of HCV, now the leading cause of mortality in this group [1,5,10]. Knowledge of stage of fibrosis is critical to appropriate HCV management and treatment. Because of the potential bleeding risks associated with liver biopsy, there has been interest in identifying noninvasive biomarkers that predict fibrosis. Yet fibrosis models derived in non-hemophilic HCV-infected groups may not accurately predict fibrosis in those with hemophilia, due to differences in age at acquisition of HCV and HIV, duration of HCV [33] and HIV infection [1], CD4 count, and HAART therapy [10]. To address these issues, the impact of HIV infection on HCV was evaluated by comparing prevalence and factors associated with fibrosis in HIV/HCV co-infected and HCV mono-infected men. The findings of this observational study, which represents the largest multi-center study of histologic HCV infection in hemophilia, demonstrate that 41 years after the introduction of HCV into this population, 23.6% have biopsy-confirmed fibrosis, and, among HIV/HCV co-infected, the prevalence of fibrosis, 28.0%, is 1.4 fold higher than in HCV-mono-infected men, 20.5%, or pre-HIV [2] and post-HIV rates in hemophilic men [16, 34].

All variables except AST/ALT were strongly associated with fibrosis by all three systems. Alpha-fetoprotein was the strongest univariate marker associated with Metavir ≥F3 fibrosis. Platelet count and alpha-fetoprotein were significantly associated with fibrosis in the co-infected group, similar to previous findings [35]; and APRI, ferritin, and alpha-fetoprotein were significantly associated with fibrosis in the HIV(−) group, similar to published studies [22]. These biomarkers, however, were not as strongly associated with fibrosis in co-infected as mono-infected subjects, in contrast to previous studies [20, 21, 36]. Although the reason for this discrepancy is not known, it may reflect the effects of long duration HIV infection which increases HCV progression [5, 10], resulting in liver dysfunction and lower platelets in co-infected, but not mono-infected subjects. This may also account for differences between our study and past studies of shorter duration HIV infection.

The likelihood of having fibrosis (Metavir F3 fibrosis) was increased in those with elevated α-fetoprotein, increasing age, and past HCV treatment. The latter is a somewhat surprisisng finding: HCV treatment, if successfully completed, is associated with reduction in HCV viral load and reduced liver disease progression. Although there is no obvious explanation, this may be a limitation of the variables we assessed, “interferon ever” or “ribavirin ever”, but not the dates of treatment, dose, tolerance, compliance, or virologic outcome. This could also be a survivor effect, as those not treated for HCV could have died earlier, so those living treated longer may be more likely to live long enough to develop fibrosis. Alternatively, those receiving treatment did so late in the course of their HCV infection, as long duration HCV infection distinguishes hemophilic from non-hemophilic subjects, with potentially poorer outcomes, as noted in hemophilic transplant candidates [37, 38].

It would seem reasonable, based on these findings, to monitor HCV(+) hemophilia patients routinely with α-fetoprotein levels, and, if elevated or increasing, consider liver biopsy, antiviral treatment, careful assessment for end-stage liver disease, and early referral for transplant evaluation. These findings underscore the need for prospective studies to confirm these findings and determine whether early identification of these abnormalities is associated with clinical benefit.

The findings of this study also establish that fewer than one-third of HCV (+) hemophilic men overall receive HCV antiviral therapy; and, despite beneficial effects of HAART in slowing HCV liver disease [10], one-fifth of co-infected men may not receive HAART therapy. Emerging rates of pre-transplant mortality in co-infected transplant candidates [39], among whom 10% have hemophilia, further suggest not only the need for optimal treatment, but also early recognition of end-stage liver disease, including routine monitoring of all co-infected individuals with model for end-stage liver disease (MELD), a predictor of post-transplant mortality, based on bilirubin, creatinine, INR [13,39].

The mechanism of fibrosis progression among those with co-infection is not well understood. It has been proposed that HIV upregulates cytokines that cause fibrosis [68], yet, in contrast to previous studies [24,40], we found that cytokine mRNA was negatively associated with fibrosis.

We recognize several limitations of this study. First, only a small proportion of the group underwent liver biopsy; however, it is among the largest hemophilic groups to undergo biopsy. Secondly, many subjects had undergone biopsies prior to study and were unwilling to undergo another. Despite this, the results of the study remain unchanged even after adjusting for or stratifying by time between serum measurement and biopsy. Thirdly, the true rate of fibrosis may be underestimated, as those who died of AIDS or liver disease before the 2002 start of study may have had fibrosis [5], were not able to be included, while most of those co-infected included in the study received HAART, which slows HCV progression [10]. Fourthly, although the duration of HCV infection was based on data documenting that HCV infection in hemophilia occurs with the first blood product [33], typical for those with severe and moderately severe hemophilia, it may not be true for those with mild disease, who are treated for traumatic bleeds, typically after first year of life. Finally, a one-time cytokine level may be insufficient to evaluate HIV impact on liver fibrosis, and moreover, the negative association between cytokine mRNA and fibrosis suggests other mechanisms by which HIV increases HCV progression, which will require further study

The strengths of this study are its size, i.e. the largest histologic assessment of HCV infection in hemophilia, liver histopathology assessment by a single central pathologist expert in HCV fibrosis, and comparisons between HIV(+) and HIV(−). However, until the accuracy of biomarkers approaches that of liver biopsy, the latter will remain the gold standard for fibrosis detection.


M.V.R. and K.S. designed the research; M.A.N. and A.J.Z. performed study procedures; A.C.H., T.L.W., S.H., and A. Z. performed laboratory assays; M.V.R., K.S., C.G.M., and J.L. analyzed the results and made figures; and M.V.R. wrote the paper with contributions from K.S., C.G.M., and O.S.S.

The Impact of HIV on Hepatitis C in Hemophilia (HHH) Study was supported by a grant from the National Institutes of Health, NHLBI R01 68429 (MVR), and by a grant from the National Institute of Health CTRC/CTSI: NIH/NCRR/CTSA UL-1 RR024153. There were no competing financial interests by any authors. We thank Kristen Jaworski, B.S.N., R.N., Hemophilia Center of Western Pennsylvania for coordination of sample and data collection; Steven H. Belle, Ph.D., Graduate School of Public Health, University of Pittsburgh, for assistance in study design; George Michalopoulos, Ph.D., Chair, Department of Pathology, for advice in initial planning; and Ms. Terry Sefcik, Center for Healthcare Research, University of Pittsburgh, for data entry and data cleaning. We also thank the physician investigators and nurse coordinators, “The HHH Study Group,” without whom this project could not have been accomplished: Ellis Neufeld, MD, Joanna Hedstrom, RN, and Randi Stern, RN, Brigham & Women’s Harvard, Boston MA; Joan Gill, MD, and Megan Gavin, RN, Medical College of Wisconsin, Milwaukee WI; Lisa Boggio, MD, and Sandy Harris, RN, Northwestern University, Chicago IL; Doreen Brettler, MD, and Linnea Olson, RN, University of Massachusetts, Wooster MA; Gilbert White, MD, Alice Ma, MD, and Aime Grimsley, RN, University of North Carolina, Chapel NC; Keith Hoots, MD, Kathryn Moynihan, RN, and Megan Ullman, RN, University of Texas, Houston TX; Cynthia Rutherford, MD, and Patricia Dunnagan, RN, University of Texas Southwestern, Dallas TX; Robert Bona, MD, and Ann Bartolomeo, RN, University of Connecticut, Farmington CT; Diana Beardsley, MD, Judy C. Sutton, RN, and Susan Marino, RN, Yale University, New Haven CT; Alice Cohen, MD, and Ellen White, RN, Newark Beth Israel Medical Center, Newark NJ; Peter Kouides, MD, and Laura Braggins, RN, Rochester General Hospital, Rochester NY; Chris Walsh, MD, and Johanna McCarthy RN, Mt. Sinai Medical Center, New York NY; Zale Bernstein, MD, and Linda Belling, RN, Erie County Medical Center, Buffalo NY; James Steinberg, MD, and Francie Lasseter, RN, Emory University, Atlanta GA; Philip Kuriakose, MD, and Angela Lambing, RN, Henry Ford Hospital, Detroit MI; Roshni Kulkarni, MD, Ajovi Scott Emuakpor, MD, Laura Carlson, RN, and Carolyn Solomon, RN, Michigan State University, East Lansing MI; Ralph Gruppo, MD, and Ann P Green, MD, Children’s Hospital Medical Center, Cincinnati OH; Jeffrey Hord, MD, and Dawn Ali, Akron City Hospital, Akron OH; Amy Shapiro, MD, Karen Hieston, RN, Renee Murry, RN, and Sarah May, RN, Indiana Hemophilia Thrombosis Center, Indianapolis IN; Geoffrey Allen, MD, Alexis Thompson, MD, Nichele Willingham, RN, and Dena F. Haddad, RN, Childrens Memorial Hospital, Chicago IL; Leonard Valentino, MD, and Rosie Howard, RN, Rush Medical Center, Chicago IL; Prasad Mathew, MD, and Marcia Schwartz, RN, University of New Mexico, Albuquerque NM; Hassan Yaish, MD, Richard Lemons, MD, Shirley Bleak, RN, and Jennifer Green, RN, Primary Children’s Medical Center, Salt Lake City UT; Diane Nugent, MD, and Marianne McDaniel, RN, Children’s Hospital of Orange County, Orange CA; Michael Tarantino, MD, Yvonne Lucas, RN, and Mary Brooks, RN, Comprehensive Bleeding Disorders Center, Peoria IL; Cindy Leissinger, MD, Cecelia Schmidt, RN, Tulane Medical Center, New Orleans LA; Joseph Palascak, MD, Mary Galeano, RN, and Madeline Heffner, RN, University of Cincinnati, Cincinnati OH; Mark Reding, MD, Kerry Hansen, RN, and Joan Osip, RN, University of Minnesota, Minneapolis MN; Joachim Reimers, MD, and Judy Bagato, RN, St. Louis University, St. Louis MO; Patrick Fogarty, MD, Patrycja Olszynski, RN, and Susan Karp, RN, University of California, San Francisco CA; Donna DiMichele, MD, Suchitra Acharya MD, and Ilene Goldberg, RN, New York Weill Cornell Medical Center, New York NY; Barbara Konkle, MD, and Karen Panckeri, RN, University of Pennsylvania, Philadelphia PA; Jerry Powell, MD, and Karen Scott, University of California, Davis CA; Marilyn Manco-Johnson, MD, Sally Stabler MD, Carissa Smith, RN, Brenda Riske, RN, University of Colorado Health Sciences Center, Denver CO.

Support: National Institutes of Health Grant NHLBI R01 68429 (MVR), and CTRC/CTSI NIH/NCRR/CTSA UL-1 RR024153.


Conflict of interest disclosure: The authors declare no competing financial interests.


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