Performance of risk prediction models for post-operative mortality in patients undergoing liver resection |
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| Affiliation: | 1. Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;2. Department of Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA;3. Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;4. Leonard David Institute of Health Economics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA;5. Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;6. Department of Surgery, Surgical Outcomes Research Center, University of Virginia, Charlottesville, VA, USA;1. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA;2. Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan;1. Cincinnati Research in Outcomes and Safety in Surgery (CROSS), Department of Surgery, University of Cincinnati College of Medicine, Cincinnati, OH, USA;2. Department of Surgery, Division of Transplantation, University of Cincinnati College of Medicine, Cincinnati, OH, USA;3. Department of Surgery, Division of Surgical Oncology, University of Cincinnati College of Medicine, Cincinnati, OH, USA |
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| Abstract: | BackgroundLiver 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.MethodsThis 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.ResultsA 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.ConclusionThe VOCAL-Penn score demonstrated superior predictive performance for 30-day post-operative mortality after liver resection as compared to existing clinical standards. |
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| Keywords: | Risk prediction VOCAL-Penn score Liver resection Mayo risk score Albumin-bilirubin score |
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