Establishment of a risk assessment system for complications of hepatectomy based on preoperative variables

Abstract

To reduce the incidence of postoperative complications, it is important to predict them and intervene before surgery if necessary. However, there is no ideal system to evaluate the overall risk of postoperative complications of liver surgery on the basis of preoperative variables. Therefore, this study aimed to design and validate a risk assessment system to predict postoperative complications of hepatectomy on the basis of preoperative variables. Binomial logistic regression was used to derive the “hepatectomy overall risk formula” (HORF) for predicting postoperative complications on the basis of preoperative variables. Multivariate analysis revealed that Child-Pugh grade B–C (odds ratio [OR] = 1.984, p = 0.002), medical diseases requiring drug treatment (OR = 1.883, p = 0.003), major hepatectomy (OR = 1.947, p < 0.001), adjacent organ invasion (OR = 3.616, p = 0.023), and preoperative hospital stay > 7 days (OR = 1.565, p = 0.004) were independent risk factors for postoperative complications of hepatectomy. The area under the curve for the HORF was 0.736. The optimal cut-off value for predicting complications was 0.32 (32%). The area under the curve for the HORF in the validation dataset was 0.727. The HORF can accurately predict postoperative complications of hepatectomy on the basis of preoperative variables, and thus enables the determination of the necessity for intervention before surgery.