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

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Abstract

Background

Prospective and longitudinal studies have examined liver donors’ medical outcomes beyond the first 1 to 2 years postdonation. There is no analogous longitudinal evidence on long-term psychosocial outcomes, including patient-reported clinically significant mental health problems and perceptions of physical well-being. We examined prevalence, descriptive characteristics, and predictors of diagnosable mental health conditions and self-reported physical health problems, including fatigue and pain, in the long-term years after liver donation.

Methods

Donors from 9 centers who initially completed telephone interviews at 3 to 10 years postdonation (mean, 5.8 years; SD, 1.9) were reinterviewed annually for 2 years using validated measures. Outcomes were examined descriptively. Repeated-measures regression analyses evaluated potential predictors and correlates of outcomes.

Results

Of 517 donors initially interviewed (66% of those eligible), 424 (82%) were reassessed at least once. Prevalence rates of major depression and clinically significant pain were similar to general population norms; average fatigue levels were better than norms. All prevalence rates showed little temporal change. Anxiety and alcohol use disorder rates exceeded normative rates at 1 or more assessments. Longer postdonation hospitalization, female sex, higher body mass index, concerns about donation-related health effects, and burdensome donation-related financial costs were associated with increased risk for most outcomes (P's < 0.05). Men were at higher risk for alcohol use disorder (P < 0.001).

Conclusions

Anxiety and alcohol use disorders were more common than would be expected; they may warrant increased research attention and clinical surveillance. Surveillance for long-term problems in the areas assessed may be optimized by targeting donors at higher risk based on identified predictors and correlates.

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