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Diabetes mellitus (DM) significantly impacts long‐term survival after liver transplantation (LT). We identified survival factors for LT recipients who had DM to inform preventive care using machine‐learning analysis. We analyzed risk factors for mortality in patients from across the United States using the Scientific Registry of Transplant Recipients (SRTR). Patients had undergone LT from 1987 to 2019, with a follow‐up of 6.47 years (standard deviation [SD] 5.95). Findings were validated on a cohort from the University Health Network (UHN) from 1989 to 2014 (follow‐up 8.15 years [SD 5.67]). Analysis was conducted with Cox proportional hazards and gradient boosting survival. The training set included 84.67% SRTR data (n = 15,289 patients), and the test set included 15.33% SRTR patients (n = 2769) and data from UHN patients (n = 1290). We included 18,058 adults (12,108 [67.05%] men, average age 54.21 years [SD 9.98]) from the SRTR who had undergone LT and had complete data for investigated features. A total of 4634 patients had preexisting DM, and 3158 had post‐LT DM. The UHN data consisted of 1290 LT recipients (910 [70.5%] men, average age 54.0 years [SD 10.4]). Increased serum creatinine and hypertension significantly impacted mortality with preexisting DM 1.36 (95% confidence interval [CI], 1.21‐1.54) and 1.20 (95% CI, 1.06‐1.35) times, respectively. Sirolimus use increased mortality 1.36 times (95% CI, 1.18‐1.58) in nondiabetics and 1.33 times (95% CI, 1.09‐1.63) in patients with preexisting DM. A similar effect was found in post‐LT DM, although it was not statistically significant (1.38 times; 95% CI, 1.07‐1.77;  P  = 0.07). Survival predictors generally achieved a 0.60 to 0.70 area under the receiver operating characteristic for 5‐year mortality. LT recipients who have DM have a higher mortality risk than those without DM. Hypertension, decreased renal function, and sirolimus for maintenance immunosuppression compound this mortality risk. These predisposing factors must be intensively treated and modified to optimize long‐term survival after transplant.

Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning