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Original Clinical Science—Liver

Prevalence and Predictors of Patient-Reported Long-term Mental and Physical Health After Donation in the Adult-to-Adult Living-Donor Liver Transplantation Cohort Study

Dew, Mary Amanda PhD1,2,3,4; Butt, Zeeshan PhD5,6,7; Liu, Qian MPH8; Simpson, Mary Ann PhD9,10; Zee, Jarcy PhD8; Ladner, Daniela P. MD5,6; Holtzman, Susan PhD11; Smith, Abigail R. PhD8; Pomfret, Elizabeth A. MD, PhD10; Merion, Robert M. MD8,12; Gillespie, Brenda W. PhD13; Sherker, Averell H. MD14; Fisher, Robert A. MD15; Olthoff, Kim M. MD16; Burton, James R. Jr. MD17; Terrault, Norah A. MD19; Fox, Alyson N. MD19; DiMartini, Andrea F. MD1,20

Author Information
doi: 10.1097/TP.0000000000001942

Living organ donation is a 1-time event with the potential for lifelong impact on donors’ medical and psychosocial status. Given growing emphasis in Western countries on increasing donations from living donors to offset the organ shortage,1 it is critical that the impact of donation on the donor be understood not only in the first several years postdonation but also in the later-term years. However, in contrast to a number of longitudinal investigations of long-term outcomes in kidney donors,2-5 follow-up of liver donors has only recently extended beyond the first 1 to 2 years postdonation.6 In particular, a growing number of studies have begun to document long-term risks for mortality and medical complications after liver donation,6 including large-scale prospective and longitudinal studies of national cohorts.7,8 Such information is essential for potential liver donors to be fully informed about risks, and for transplant programs to plan surveillance efforts to monitor postdonation medical issues in their donors.

A less recognized long-term outcome area pertinent to both informed consent and surveillance plans concerns liver donors' psychosocial outcomes. Patient-reported outcomes are well-recognized as critical elements to include when delineating the impact of medical procedures, including living donation.9-11 Yet studies documenting liver donors' long-term psychosocial status, including both their mental health and their perceptions of physical well-being and health-related quality of life (HRQOL), have lagged behind the literature on medical outcomes in several important respects. First, studies of these long-term psychosocial outcomes have been predominantly cross-sectional12-22 and, as such, have been unable to examine trends over time. Second, most reports do not examine clinically significant difficulties in the psychosocial domains assessed, and instead focus on either nonspecific, generic HRQOL assessments13,21,23 or unvalidated, single-item assessments with unknown performance characteristics.12,15-20 Third, the vast majority of reports examine small single-site cohorts,12,13,15-20,22 resulting in findings of unknown, potentially limited, generalizability.

In the present study, we used data from the 9-site Adult-to-Adult Living-Donor Liver Transplantation Cohort Study-2 (A2ALL-2), conducted in 2009 to 2014, to longitudinally chart the nature of clinically significant psychosocial difficulties in both donor-reported mental and physical health domains in the long-term years postdonation. We move beyond our previous examination of long-term psychosocial outcomes in our cohort, in which we considered generic HRQOL and general questions about emotional and physical reactions to donation cross-sectionally among 517 individuals assessed at up to 10 years postdonation.14 Namely, herein we examined the prevalence and nature of change over time of diagnosable mental health conditions and specific areas of physical health problems in the cohort. We also examined patterns of co-occurrence among the conditions, because they are likely to be comorbid rather than occurring in isolation.24-26 We considered whether the prevalence of any such problems differs from normative levels in healthy community samples, and we examined whether sociodemographic factors, donation-related clinical factors, and donors' perceptions of the donation experience were associated with risk for mental and physical health problems.

MATERIALS AND METHODS

Participants and Study Design

In the A2ALL-2 Consortium, we previously enrolled 517 liver donors in a cross-sectional investigation of their long-term postdonation psychosocial status.14 The Consortium was formed in 2009 with 1 Canadian and 8 US centers. At enrollment, eligible donors were aged 18 years or older, spoke English, and were 3 to 10 years postdonation (donation occurred between 2002 and 2009). Of eligible donors, 66% enrolled (71% of those located).14

In the current investigation, we followed this cohort for 2 years. They were assessed 3 times (at enrollment, and twice annually thereafter).

Procedure

The study was approved by the Institutional Review Boards and Privacy Boards of the University of Michigan Data Coordinating Center and each transplant center. Participants provided informed consent. Telephone interviews lasting 30 to 45 minutes were conducted at each time point by trained interviewers using computer-assisted interview methods to ensure that questions were asked in a standardized manner.14,27

Trained research staff at each center extracted clinical information (described below) from donors’ medical records.

Measures

Outcomes

We used validated, widely-used measures to assess current mental health (psychiatric disorders including major depression, nonpanic anxiety disorder [ie, generalized anxiety disorder], and alcohol use disorder; depression symptom severity; and general mental HRQOL) and current physical health (fatigue, pain severity, pain interference with daily activities, and general physical HRQOL) (Table 1).

T1-21
TABLE 1:
Measures used to assess study outcomes and potential predictors and correlates of outcomes

Potential Predictors and Correlates of Mental and Physical Health Outcomes

We assessed variables in 3 areas: sociodemographic characteristics, clinical factors from donors’ medical records, and donors’ perceptions related to the donation experience (Table 1).

Statistical Analysis

We compared individuals who continued versus dropped out during the study on initial assessment characteristics using χ2 tests and t tests. The sample’s distribution on each mental and physical health outcome variable was examined at each assessment. Change across time for each outcome was evaluated with a mixed effects model, with time as a fixed effect and random intercepts to account for repeated measures within donors. This approach allowed us to include all available data, regardless of whether donors completed all assessments. We also used descriptive statistics to examine: (a) the percentage of donors with clinically significant problems on a given outcome (eg, presence of psychiatric disorder, elevated fatigue or pain levels) at more than 1 time points; and (b) comorbidity patterns among the outcomes.

Donors’ scores on the outcomes were compared with normative data from population-based healthy community samples, when available, using 1-sample χ2 tests and t tests. Because each outcome was compared with normative data at 3 time points, we adjusted for multiple comparisons (3 per variable) using Hochberg’s modified Bonferroni method.47

To identify predictors and correlates of outcomes, repeated measures regression models were fit. We used generalized estimating equation models where dependence among observations from a given donor over time was taken into account when determining the impact of predictors/correlates. A separate model was fit for each outcome. Variables were entered into the model in 2 sequential stages, to reflect their temporal ordering of occurrence.48 First, sociodemographic and clinical characteristics were entered to evaluate their effects. Then, variables related to donors’ long-term perceptions of the donation experience were added to determine their contribution to the outcome beyond the sociodemographic/clinical variables’ impact. At each modeling stage, the final, most parsimonious model was chosen based on best subset selection guidelines.49 Missing data on the predictors/correlates were multiply imputed using Rubin procedure50 and IVEware.51 The extent of missing data is reported in Table 2 (footnote a). Variables were retained in models if P values from overall tests were less than 0.05.

T2-21
TABLE 2:
Demographic, clinical, and psychosocial characteristics of donors enrolled and approached for follow-up

We examined whether outcomes differed across centers and whether adjusting for centers affected other predictors’ impact. Thus, we compared model results before and after controlling for centers in sensitivity analyses.

RESULTS

Sample Description

We previously described the cohort of 517 donors, who averaged almost 6 years postdonation at enrollment14 (see also Table 2, first column). In the present study, 93 donors (18.0%) were lost over the 2-year follow-up: 46 completed only the initial assessment, and 47 completed the first 2 but not the third assessment. Among these 93 donors, 5 could not be located, 45 were located but did not respond to phone or mailed requests, and 43 were recontacted but refused additional interviews. We compared the 93 donors with the remaining 424 donors (Table 2). These groups were similar, except that donors who dropped out had lower education levels.

Description of Mental and Physical Health Outcomes Across Assessments

Table 3 shows the sample’s distribution on each measure in the 2 outcome domains at each assessment time point. Prevalence rates or mean scores on most variables were stable across the study period. The exceptions were that anxiety disorder prevalence changed significantly across assessments, with the highest rate at the first assessment, and the rate for having any 1 of the 3 psychiatric disorders showed a similar pattern.

T3-21
TABLE 3:
Patient-reported mental and physical health at the 3 long-term follow-up assessments in living liver donorsa

For each outcome, we examined whether donors met criteria for a psychiatric disorder or scored in the clinically significant range on a measure at only 1 time point or at multiple time points. As shown in Table 4, 7% to 23% met criteria for the psychiatric disorders at more than 1 time point. Overall, 22 of the 96 donors who had assessed psychiatric disorders during the study had them at multiple time points. Almost half of donors with depressive symptoms reported such symptoms at multiple assessments, and one third or more of donors with poor Mental Component Summary (MCS) scores, Physical Component Summary (PCS) scores, fatigue or pain at any assessment were likely to show these problems at multiple assessments.

T4-21
TABLE 4:
Percentage of donors who had each outcome at multiple assessments during the study period

Finally, we characterized the outcome variables' patterns of co-occurrence. First, we examined whether each donor experienced 1 or more psychiatric disorder during the 2-year study period, regardless of whether the disorders overlapped in time. Figure 1 displays these patterns for the 96 donors who had any disorder during the study period. For example, 46 donors had only alcohol use disorder, 4 had both anxiety and alcohol use disorders, and so on. Overall, alcohol use disorder most often occurred alone, that is, donors never met criteria for another disorder: only 19% (11/57) of those with alcohol use disorder also had anxiety and/or major depressive disorders. Comorbidity rates were higher for anxiety and major depressive disorders: 53% (21/39) of those with anxiety disorder met criteria for another assessed disorder, as did 60% (17/28) of those with major depressive disorder.

F1-21
FIGURE 1:
Comorbidity of psychiatric disorders during study period in 96 donors who met criteria for at least 1 disorder.

We examined whether individuals with multiple disorders had episodes of disorders that overlapped at a given assessment time point. Of the 21 cases in Figure 1 with 1 or more disorder, 81% (ie, all but 4 cases: 2 with alcohol use and anxiety, 2 with anxiety and major depression) had multiple disorders that overlapped at 1 or more time points.

We also examined co-occurrence of clinically significant fatigue and pain during the 2-year period. Of 178 donors with either problem, 31% reported both, 43% reported only pain, and 26% reported only fatigue. Among those reporting both (n = 56), 86% (all but 8 cases) had the conditions together at 1 or more time points.

Cases are too sparse to examine comorbidities of all combinations of specific mental and physical problems. However, of 218 donors who met caseness criteria for either psychiatric disorder or clinically significant pain or fatigue over the 2 years, 56 (26%) met criteria in both mental and physical domains, 40 (18%) had only mental disorders, and 122 (56%) had only pain or fatigue.

Comparison of Mental and Physical Health Outcome Levels to Normative Data

We compared the sample to normative data, where available (Table 3, rightmost column). Donors’ anxiety disorder rate was significantly higher than the normative rate at the first assessment but not thereafter. Their alcohol use disorder rate was significantly higher than the normative rate at 2 of the 3 assessments. The sample’s mean Short Form-36 MCS scores were significantly poorer than the normative mean at all time points. Donors had significantly less fatigue than normative levels at all time points, based on both mean scores and percentage with clinically significant fatigue.

Predictors and Correlates of Mental and Physical Health Outcomes

Regression results for the mental and physical health outcomes are shown in Tables 5 and 6, respectively. Because (a) less than 5% of the sample had major depressive disorder and less than 5% had anxiety disorder at any given time point; and (b) these disorders were highly comorbid, as discussed above, we created a composite reflecting whether individuals had either disorder to use in the regression analysis. For this composite variable, time of assessment was significant (Table 5): consistent with the patterns in Table 3, the likelihood of having a disorder was significantly lower after the initial assessment. Men were at greater risk for alcohol use disorder and lesser risk for depressive symptomatology. Relative to respective referent groups, obese donors and unrelated donors were at higher risk for depressive symptoms. A longer postdonation hospitalization increased the risks for depressive symptoms and poor MCS scores.

T5-21
TABLE 5:
Predictors of donors’ mental health outcomes from repeated measures regression analysis
T6-21
TABLE 6:
Predictors of donors’ physical health outcomes from repeated measures regression analysis

Table 5 shows that long-term perceptions of donation were also related to the mental health outcomes. Higher posttraumatic growth was associated with lower alcohol use disorder risk. Greater concern about health due to donation was associated with all 4 mental health outcomes. Donors who had incurred burdensome financial costs were at higher risk for the major depression/anxiety disorder composite, depressive symptoms, and poor MCS scores.

Among physical health outcomes, men were at lower risk for clinically significant fatigue, pain, and poor PCS scores (Table 6). Obese donors were at higher risk for fatigue, pain interference, and poor PCS scores. Unrelated donors were more likely to have clinically significant fatigue, and a longer postdonation hospitalization increased the risk for all 4 physical health outcomes. Concerning long-term perceptions of donation, the most consistently potent factors—associated with increased risk of all 4 outcomes—were reporting donation-related health concerns, and incurring burdensome donation-related financial costs. Greater posttraumatic growth was associated with lower risk of clinically significant fatigue, while a donor’s feeling that he or she was a better person for having donated was associated with higher risk of pain interference. Experiencing problems with health/life insurance was associated with higher likelihood of a poor PCS score.

Results in Tables 5 and 6 were unchanged when controlling for transplant center. There were significant between-center differences only for clinically significant pain (overall P = 0.038). Using the center with the most donors as the referent, donors at 2 centers were at increased risk to report pain; remaining centers did not differ significantly from the referent (Table S1, SDC,https://links.lww.com/TP/B487). The distributions of donors across centers were too sparse for additional analyses.

DISCUSSION

To our knowledge, ours is the first study to examine the prevalence, course of change, and co-occurrence of clinically significant patient-reported mental and physical health problems in the long-term years after living liver donation, using standardized, validated measures and a large, multisite cohort. We also explored comorbidity patterns for these outcomes, and considered potential predictors and correlates of patients’ reports of their health.

Several key findings emerged. Donors’ average scores on the physical health measures that we examined—including generic physical-related HRQOL (PCS) scores, pain severity and fatigue—were generally either similar to or even better (in the case of fatigue) than normative levels for healthy community residents at every assessment. However, this was not the case for the mental health outcomes. Donors showed higher rates of anxiety and alcohol use disorders than normative samples at 1 or more study assessments. Their mental health-related HRQOL (MCS) scores were also poorer than the normative mean at all assessments, although the difference was small. Although major depressive disorder and depression symptom severity were also temporally stable, their prevalence and average severity, respectively, were similar to those in normative samples, this is consistent with findings for donors assessed within 1 to 2 years postdonation.65-68 Although norms were not available for pain interference with daily activities, this outcome appeared to be relatively rare, as has been found for liver donors at 1-year postdonation.69 Overall, these results may suggest that depression, pain, and any decrements in general physical HRQOL are not unduly prominent in the long term after liver donation. Alternatively, because donors are highly screened before donation and thus likely to be healthier than general community normative samples (even when those samples are limited to individuals without self-reported chronic diseases), the donors' outcomes might be expected to be better rather than similar to normative rates.6,70 Thus, their depression, pain, and any impairments in physical HRQOL in the long-term postdonation may not be inconsequential.

Moreover, if it is expected that donor outcomes should be better than norms, our findings of elevated anxiety and alcohol use disorder rates are worrisome. Unfortunately, there are no other long-term studies of these conditions after liver donation. Anxiety disorder rates in our sample declined and did not exceed the normative rate by the third assessment; the low rates at 2 of the 3 assessments are consistent with rates and symptom burden found in studies focused on the early years postdonation.65-68 However, the elevated alcohol use disorder rates showed no reliable change across assessments. It is well known that the propensity for alcohol abuse runs in families,71 and most of our donors were family members of their recipients. Alcoholic liver disease (ALD) is a prominent indication for transplantation in Western countries, and the prevalence of alcohol use disorder in our sample might have been driven by donors at risk for alcohol problems by virtue of their family linkage to a transplant recipient who had ALD. We only have information on recipients’ indications for transplantation for a small subset of the donors in our cohort (n = 137, who had participated in the A2ALL-1 Consortium, which existed before the 2009 formulation of A2ALL-2, and which collected this recipient information). Among these 137 individuals, there was a weak, nonsignificant association between recipient ALD diagnosis and whether donors had alcohol use disorder during the present study (Fisher exact P = 0.421, effect size, phi [correlation between variables] = 0.07). Similarly, in a separate A2ALL-2 cohort studied during the first 2 years postdonation, we also found little relationship between donor alcohol abuse (ie, alcohol use disorder on the PRIME-MD) and recipient ALD diagnosis.65 Given that alcohol abuse was observed in up to 5% of donors at any given assessment in this previous study—similar to rates reported herein—we suggest monitoring for alcohol use in donors might be important not only in the short-term postdonation65,72 but also in the longer-term years.

Our examination of mental disorders' comorbidity patterns suggests that some donors were burdened with multiple mental health problems and that these problems usually co-occurred in time. A similar pattern of temporal co-occurrence was noted for fatigue and pain. From a clinical perspective, this suggests that if 1 area of difficulty is uncovered, more detailed probing may be needed to understand the full constellation of problems the donor may be experiencing.26

The identification of risk factors and correlates for the mental and physical health problems that we studied may also help transplant center teams to better target or refine detection efforts. Among sociodemographic and clinical predictors, sex, predonation body mass index (BMI), and length of hospitalization postdonation were the most robust predictors, emerging as important for most outcomes. A longer hospitalization—likely reflecting a more difficult recovery—increased donors’ risk for all physical outcomes, and 2 of 4 mental health outcomes. Sex and BMI were important for most physical outcomes—with women and obese donors at heightened risk for most these outcomes. The impact of BMI is consistent with evidence indicating its importance for kidney donors’ long-term outcomes.73 Female sex and BMI also increased our donors’ risk for depressive symptomatology. Consistent with known risk factors for alcohol abuse,71 men were at increased risk for this problem. Length of hospital stay, sex, and BMI are easy to ascertain and could thus be useful to transplant programs aiming to proactively identify liver donors most likely to have mental and/or physical health problems in the long-term years.

Donors’ perceptions of the donation experience, assessed at our first long-term time point, also proved relevant for their health outcomes. The most prominent factor was donation-related health concerns. Donors acknowledging any concerns were at elevated risk for every outcome. The experience of burdensome postdonation financial costs was also important for all outcomes except depressive symptomatology. This reinforces and extends the range of critical concerns noted in the transplant community regarding donor financial issues and costs associated with donation.3,46,74-76 Our data suggest that such burden may have impacts that diffuse across multiple areas of well-being, and may remain salient even years postdonation.

Our findings are also notable in that a critical transplant outcome, namely, the death of the donor’s recipient, did not emerge as an important predictor of any outcome, including conditions, such as major depression. As we and others have reported previously, both clinical experience and qualitative studies show that donors are deeply affected by recipient death.77-80 Nevertheless, bereaved donors almost universally state that they take comfort in having done all they could, and they have no regrets about having donated.13,14,20,77,78 Additionally, we previously reported very low average levels of perceived guilt or responsibility for the recipient’s death in our cohort,14 and other liver donor follow-up studies have not found recipient death to increase risk for adverse long-term general HRQOL.18,20,21 Moreover, the experience of grief after bereavement does not necessarily mean that an individual will meet criteria for a psychiatric disorder, including the conditions we assessed; in fact, a large empirical literature shows that the vast majority of bereaved individuals do not develop any psychiatric disorder.81,82 It is also noteworthy that most of our donors who lost their recipient experienced this event multiple years before any of our interviews.

Major study limitations are that we did not enroll donors before donation and follow them prospectively, and we did not assess nondonor comparison groups. Indeed, we are unaware of any long-term follow-up study in living donors that has examined outcomes relative to an important comparison group: eligible donor candidates who did not donate.83 Nevertheless, given the dearth of evidence on clinically significant psychosocial difficulties in the long-term postdonation and the lack of information on how these difficulties may trend over time, our study provides important new information. Moreover, we put our results into perspective by comparing them to normative data from US population-based cohorts of individuals without self-reported major chronic diseases and who were similar in age range, education range, and BMI range as our sample. Further, our strategy of making comparisons to normative data is a strategy that has been employed to facilitate interpretation in large, multicenter long-term psychosocial follow-up studies of living kidney donors (eg, Gross et al73) where it would not have been economically or practically feasible to collect prospective data over periods of many years since donation. Comparisons to normative data are well recognized as providing valuable information for the interpretation of results obtained in a given sample and for determining the clinical significance of those results.84-88

Additional study limitations include the fact that some A2ALL-2 centers were small, restricting our ability to detect center differences. We did find center differences in rates of donor-reported pain. We previously reported that, in a separate cohort of A2ALL-2 donors who donated more recently than the current cohort, centers varied in some elements of perioperative pain management.89 However, we have no information on centers’ pain management practices for our cohort, and it is not clear that any such differences would affect pain perceptions many years later. Regarding other potential predictors, we had no information on donors’ predonation history of the mental and physical health problems. Thus, our findings cannot speak to issues of whether donor selection practices should change. However, previous studies have not consistently found that lifetime psychiatric history, or predonation fatigue or pain predicted postdonation outcomes in these areas, at least in the first few years postdonation.68,69 There may also have been intervening factors between donation and time of our assessments, including life events unrelated to donation that increased risk for our outcomes but that we could not assess. Nevertheless, the existence of such factors would not necessarily obviate the importance of the predictors that we did identify. Another limitation is that we do not have information on other variables relevant to our outcomes, including any interventions received for them. Finally, our donor cohort is relatively well educated and predominantly non-Hispanic white, potentially limiting generalizability, and precluding examination of differences between specific ethnic minorities. However, like our cohort, the vast majority of US living liver donors are non-Hispanic whites90 (living donor ethnicity information is not available for Canada.91).

Beyond these limitations, our study serves to heighten awareness that, although most donors may not experience difficulties in the mental and physical health areas we examined, a subset of donors are at risk for such problems. Among these problems, anxiety and alcohol use may warrant more attention in both research and clinical surveillance efforts. Robust risk factors for our outcomes appear relatively straightforward to assess and, therefore, may be important for transplant programs to consider to identify at-risk donors. Some factors, such as predonation obesity and postdonation burdensome financial costs, are well recognized as important (but challenging) targets for intervention in their own right. If they can be ameliorated, risk for long-term mental and physical health problems may be lessened. This remains an important issue for future research, given that our study was observational and did not establish cause-effect relationships. Nevertheless, our findings suggest that the monitoring of donor well-being beyond the first few years postdonation should include patient-reported mental and physical health outcomes, and may be most efficiently performed by targeting surveillance efforts to donors at highest risk for such difficulties.

ACKNOWLEDGMENTS

This is publication number 40 of the Adult-to-Adult Living-Donor Liver Transplantation Cohort Study.

The following individuals were instrumental in the planning and conduct of this study at each of the participating institutions:

Columbia University Medical Center, New York, NY (DK62483): PI: Jean C. Emond, MD; Co-Is: Robert S. Brown, Jr., MD, MPH, James Guarrera, MD, Martin R. Prince, MD, PhD, Benjamin Samstein, MD, Elizabeth Verna, MD, MS; Study Coordinators: Taruna Chawla, MD, Scott Heese, MPH, Connie Kim, BS, Theresa Lukose, PharmD, Tarek Mansour, MB BCH, Joseph Pisa, BA, Rudina Odeh-Ramadan, PharmD, Jonah Zaretsky, BS.

Lahey Hospital & Medical Center, Burlington, MA (DK85515): PI: Elizabeth A. Pomfret, MD, PhD; Co-Is: Christiane Ferran, MD, PhD, Fredric Gordon, MD, James J. Pomposelli, MD, PhD, Mary Ann Simpson, PhD; Study Coordinators: Erick Marangos, Agnes Trabucco, BS, MTASCP.

Northwestern University, Chicago, IL (DK62467): PI: Michael M.I. Abecassis, MD, MBA; Co-Is: Talia B. Baker, MD, Zeeshan Butt, PhD, Laura M. Kulik, MD, Daniela P. Ladner, MD, Donna M. Woods, PhD; Study Coordinator: Patrice Al-Saden, RN, CCRC, Tija Berzins, Amna Daud, MD, MPH, Elizabeth Rauch, BS, Teri Strenski, PhD, Jessica Thurk, BA, MA, Erin Wymore, BA, MS, CHES.

University of California San Francisco, San Francisco, CA (DK62444): PI: Chris E. Freise, MD; Co-I: Norah A. Terrault, MD, MPH; Study Coordinators: Alexandra Birch, BS, Dulce MacLeod, RN.

University of Colorado, Aurora, CO (DK62536): PI: James R. Burton, Jr., MD; Co-Is: Gregory T. Everson, MD, Igal Kam, MD, James Trotter, MD, Michael A. Zimmerman, MD; Study Coordinators: Jessica Fontenot, BS, Carlos Garcia, RN, BS, Anastasia Krajec, RN.

University of Michigan Health System, Ann Arbor, MI (DK62498): PI: Robert M. Merion, MD; DCC Staff: Yevgeniya Abramovich, BA, Mary Akagi, MS, CCRP, Douglas R. Armstrong, BSN, MS, Charlotte A. Beil, MPH, Carl L. Berg, MD, Abby Brithinee, BA, Tania C. Ghani, MS, MSI, Brenda W. Gillespie, PhD, Beth Golden, BScN, Margaret Hill-Callahan, BS, LSW, Lisa Holloway, BS, CCRC, Terese A. Howell, BS, CCRC, Anna S.F. Lok, MD, Monique Lowe, MSI, Anna Nattie, BA, Akinlolu O. Ojo, MD, PhD, Samia Shaw, AAIT, Abigail Smith, MS, Robert A. Wolfe, PhD, Gary Xia, BA.

University of Pennsylvania, Philadelphia, PA (DK62494): PI: Abraham Shaked, MD, PhD, Kim Olthoff MD; Co-Is: David S. Goldberg, MD, Karen L. Krok, MD, K. Rajender Reddy, MD, Mark A. Rosen, MD, PhD, Robert M. Weinrieb, MD; Study Coordinators: Brian Conboy, PA, MBA, Mary Kaminski, PA-C, Debra McCorriston, RN, Mary Shaw, RN, BBA.

University of Pittsburgh Medical Center, Pittsburgh, PA (DK85587): PI: Abhinav Humar, MD; Co-Is: Andrea F. DiMartini, MD, Mary Amanda Dew, PhD, Mark Sturdevent, MD; Study Coordinators: Megan Basch, RN, Sheila Fedorek, RN, CCRC, Leslie Mitrik, BS, Mary L. McNulty, MLS.

University of Toronto, Toronto, ON, CA (DK85563): PI: David Grant, MD, FRCSC; Co-Is: Oyedele Adeyi, MD, FCAP, FRCPC, Susan Abbey, MD, FRCPC, Hance Clarke, MSc, MD, FRCPC, Susan Holtzman, PhD, Joel Katz, CRC, PhD, Gary Levy, FRCPC, MD, Nazia Selzner, MD, PhD; Study Coordinators: Kimberly Castellano, BSc, Andrea Morillo, BM, BCh, Erin Winter, BSc.

Virginia Commonwealth University - Medical College of Virginia Campus, Richmond, VA (DK62531): PIs: Adrian H. Cotterell, MD, Robert A. Fisher, MD; Co-Is: Martha K. Behnke, PhD, Adrian H. Cotterell, MD, Ann S. Fulcher, MD, Pamela M. Kimball, PhD, HCLD, Mary E. Olbrisch, PhD, ABPP, Marc P. Posner, MD, Mark A. Reimers, PhD, Amit Sharma, MD, R. Todd Stravitz, MD; Study Coordinators: April Ashworth, RN, BSN, Joanne Davis, RN, Sarah Hubbard, Andrea Lassiter, BS, Luke Wolfe, MS.

National Institute of Diabetes and Digestive and Kidney Diseases, Division of Digestive Diseases and Nutrition, Bethesda, MD: Edward Doo, MD, James E. Everhart, MD, MPH, Jay H. Hoofnagle, MD, Stephen James, MD, Patricia R. Robuck, PhD, Leonard B. Seeff, MD, Averell H. Sherker, MD, FRCPC, Rebecca J. Torrance, RN, MS.

Heather Van Doren, MFA, senior medical editor with Arbor Research Collaborative for Health, provided editorial assistance on this article.

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