Performance of Risk Prediction Models for Post-operative Mortality in Patients Undergoing Liver Resection
Overview
Affiliations
Background: Liver resection is commonly performed for hepatic tumors, however preoperative risk stratification remains challenging. We evaluated the performance of contemporary prediction models for short-term mortality after liver resection in patients with and without cirrhosis.
Methods: This retrospective cohort study examined National Surgical Quality Improvement Program data. We included patients who underwent liver resections from 2014 to 2019. VOCAL-Penn, MELD, MELD-Na, ALBI, and Mayo risk scores were evaluated in terms of model discrimination and calibration for 30-day post-operative mortality.
Results: A total 15,198 patients underwent liver resection, of whom 249 (1.6%) experienced 30-day post-operative mortality. The VOCAL-Penn score had the highest discrimination (area under the ROC curve [AUC] 0.74) compared to all other models. The VOCAL-Penn score similarly outperformed other models in patients with (AUC 0.70) and without (AUC 0.74) cirrhosis.
Conclusion: The VOCAL-Penn score demonstrated superior predictive performance for 30-day post-operative mortality after liver resection as compared to existing clinical standards.
Surgical risk stratification in patients with cirrhosis.
Ostojic A, Mahmud N, Reddy K Hepatol Int. 2024; 18(3):876-891.
PMID: 38472607 PMC: 11864775. DOI: 10.1007/s12072-024-10644-y.
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