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Updated: Feb 2, 2026

Orthotopic Liver Transplantation in Rats
Published on: July 1, 2012
Pre- and post-transplant factors associated with body weight parameters after liver transplantation - A systematic
Sonja Beckmann1, Gerda Drent2, Todd Ruppar3
1Institute of Nursing Science, Department Public Health, University of Basel, Bernoullistrasse 28, CH-4056 Basel, Switzerland; Center of Clinical Nursing Science, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland.
Background:
Weight gain and obesity can increase liver transplant (LTx) recipients' disease burden. We aimed to summarize and synthesize the evidence on pre- and post-transplant factors related to post-LTx BMI, weight gain, and obesity.
Methods:
For this systematic review and meta-analysis we searched Medline (PubMed), Cochrane library, CINAHL, PsycINFO, and EMBASE for quantitative studies on 6 classes of factors (i.e., genetic, sociodemographic, behavioral, biomedical, psychological, and environmental) linked to body weight parameters in adult first-time LTx patients. A 19-item instrument was used for quality assessment. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for relationships investigated in ≥5 studies. Factors investigated in <5 studies were summarized and described.
Results:
Of 16,495 articles retrieved, 43 assessed factors in LTx. These examined 82 mainly biomedical and sociodemographic factors. However, variation between definitions allowed inclusion of only 2 factors (i.e., tacrolimus, cyclosporine) in our meta-analyses of 6 studies examining a shared parameter for body weight (median patient sample: 171 (range: 63-455); Europe n = 3; United States n = 3; publication years: 1997-2015). Neither tacrolimus (OR, 0.75; 95% CI, 0.47-1.21; p = 0.24) nor cyclosporine (OR, 1.40; 95% CI, 0.89-2.18; p = 0.14) were related significantly with post-LTx obesity.
Conclusions:
Evidence on modifiable factors related to post-LTx body weight parameters is still scarce, as definition variability limits data extraction and pooling for meta-analyses. To facilitate future research, studies should apply theoretical frameworks to guide their study design, select variables of interest and systematically examine interrelationships among selected factors.
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