“Real‐time” risk models of postoperative morbidity and mortality for liver transplants

AIM: A comprehensive description of morbidity and mortality risk factors for post liver transplant has not been available to date. In this study, we established real‐time risk models of postoperative morbidities and mortality in liver transplant recipients using two Japanese nationwide databases. METHODS: Data from two Japanese nationwide databases were combined and used for this study. We developed real‐time prognostic models for morbidity and mortality from a derivation cohort (n = 1472) and validated the findings with an independent cohort (n = 395). Preoperative variables (C1), preoperative and intraoperative variables (C2), and all variables including postoperative morbidities within 30 days (C3) were analyzed to evaluate the independent risk factors for postoperative morbidity and mortality. RESULTS: We established real‐time risk models for morbidity and mortality. Areas under the curve (AUC) of C1 and C2 risk models for mortality were 0.74 (0.63‐0.82) and 0.79 (0.69‐0.86), respectively. Multivariate logistic analysis using C3 showed that hemoglobin <10 g/dL, operative time (hours), and five postoperative morbidities (prolonged ventilation >48 hours, coma >24 hours, renal dysfunction, postoperative systemic sepsis, and serum total bilirubin ≥10 mg/dL) represented independent risk factors for mortality (AUC = 0.87, 95% confidence interval [CI]: 0.78‐0.93). CONCLUSIONS: Real‐time risk models of postoperative morbidities and mortality at various perioperative time points in liver transplant recipients were established. These novel approaches may improve postoperative outcomes of liver transplant recipients. Furthermore, these real‐time risk models may be applicable to other surgical procedures.