e-GLR Score Predicts Early Graft Loss in Adult Live-Donor Liver Transplantation

Abstract

Objective: This study aimed to analyze risk factors and develop a predictive model for early allograft loss due to early graft dysfunction (EGD) in adult live-donor liver transplantation (LDLT). Methods: Data of patients who underwent LDLT from 2011 to 2019 were reviewed for EGD, associated factors, and outcomes. A homogeneous group of 387 patients was analyzed: random cohort A (n = 274) for primary analysis and random cohort B (n = 113) for validation. Results: Of 274 recipients, 92 (33.6%) developed EGD. The risk of graft loss within 90 days was 29.3% and 7.1% in those with and without EGD, respectively (P < 0.001). Multivariate logistic regression analysis determined donor age (P = 0.045), estimated (e) graft weight (P = 0.001), and the model for end-stage liver disease (MELD) score (0.001) as independent predictors of early graft loss due to EGD. Regression coefficients of these factors were employed to formulate the risk model: Predicted (P) early graft loss risk (e-GLR) score = 10 × [(donor age × 0.052) + (e-Graft weight × 1.681) + (MELD × 0.145)] − 8.606 (e-Graft weight = 0, if e-Graft weight ≥640 g and e-Graft weight = 1, and if e-Graft weight < 640 g). Internal cross-validation revealed a high predictive value (C-statistic = 0.858). Conclusions: Our novel risk score can efficiently predict early allograft loss following graft dysfunction, which enables donor-recipient matching, evaluation, and prognostication simply and reliably in adult LDLT.