Risk Prediction Models for Postoperative Decompensation and Infection in Patients With Cirrhosis: A Veterans Affairs Cohort Study

Abstract

Background and Aims: Patients with cirrhosis have an increased risk of postoperative mortality for a range of surgeries; however, they are also at risk of postoperative complications such as infection and cirrhosis decompensation. To date, there are no prediction scores that specifically risk stratify patients for these morbidities. Methods: This was a retrospective study using data of patients with cirrhosis who underwent diverse surgeries in the Veterans Health Administration. Validated algorithms and/or manual adjudication were used to ascertain postoperative decompensation and postoperative infection through 90 days. Multivariable logistic regression was used to evaluate prediction models in derivation and validation sets using variables from the recently-published Veterans Outcomes and Costs Associated with Liver Disease (VOCAL)-Penn cirrhosis surgical risk scores for postoperative mortality. Models were compared with the Mayo risk score, Model for End-stage Liver Disease (MELD)-sodium, and Child-Turcotte-Pugh (CTP) scores. Results: A total 4712 surgeries were included; patients were predominantly male (97.2 %), white (63.3 %), and with alcohol-related liver disease (35.3 %). Through 90 postoperative days, 8.7 % of patients experienced interval decompensation, and 4.5 % infection. Novel VOCAL-Penn prediction models for decompensation demonstrated good discrimination for interval decompensation (C-statistic 0.762 vs 0.663 Mayo vs 0.603 MELD-sodium vs 0.560 CTP; P