Nadim Mahmud1,2, Zachary Fricker3, Rebecca A Hubbard4, George N Ioannou5,6, James D Lewis1,2, Tamar H Taddei7,8, Kenneth D Rothstein1, Marina Serper1,9, David S Goldberg10, David E Kaplan1,9. 1. Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA. 2. Leonard David Institute of Health Economics, University of Pennsylvania, Philadelphia, PA. 3. Division of Gastroenterology, Hepatology, and Nutrition, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA. 4. Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA. 5. Division of Gastroenterology, Department of Medicine, Veterans Affairs Puget Sound Healthcare System and University of Washington, Seattle, WA. 6. Health Services Research and Development, Veterans Affairs Puget Sound Healthcare System, Seattle, WA. 7. Division of Digestive Diseases, Yale University School of Medicine, New Haven, CT. 8. VA Connecticut Healthcare System, West Haven, CT. 9. Department of Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA. 10. Division of Digestive Health and Liver Diseases, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL.
Abstract
BACKGROUND AND AIMS: Patients with cirrhosis are at increased risk of postoperative mortality. Currently available tools to predict postoperative risk are suboptimally calibrated and do not account for surgery type. Our objective was to use population-level data to derive and internally validate cirrhosis surgical risk models. APPROACH AND RESULTS: We conducted a retrospective cohort study using data from the Veterans Outcomes and Costs Associated with Liver Disease (VOCAL) cohort, which contains granular data on patients with cirrhosis from 128 U.S. medical centers, merged with the Veterans Affairs Surgical Quality Improvement Program (VASQIP) to identify surgical procedures. We categorized surgeries as abdominal wall, vascular, abdominal, cardiac, chest, or orthopedic and used multivariable logistic regression to model 30-, 90-, and 180-day postoperative mortality (VOCAL-Penn models). We compared model discrimination and calibration of VOCAL-Penn to the Mayo Risk Score (MRS), Model for End-Stage Liver Disease (MELD), Model for End-Stage Liver Disease-Sodium MELD-Na, and Child-Turcotte-Pugh (CTP) scores. We identified 4,712 surgical procedures in 3,785 patients with cirrhosis. The VOCAL-Penn models were derived and internally validated with excellent discrimination (30-day postoperative mortality C-statistic = 0.859; 95% confidence interval [CI], 0.809-0.909). Predictors included age, preoperative albumin, platelet count, bilirubin, surgery category, emergency indication, fatty liver disease, American Society of Anesthesiologists classification, and obesity. Model performance was superior to MELD, MELD-Na, CTP, and MRS at all time points (e.g., 30-day postoperative mortality C-statistic for MRS = 0.766; 95% CI, 0.676-0.855) in terms of discrimination and calibration. CONCLUSIONS: The VOCAL-Penn models substantially improve postoperative mortality predictions in patients with cirrhosis. These models may be applied in practice to improve preoperative risk stratification and optimize patient selection for surgical procedures (www.vocalpennscore.com).
BACKGROUND AND AIMS: Patients with cirrhosis are at increased risk of postoperative mortality. Currently available tools to predict postoperative risk are suboptimally calibrated and do not account for surgery type. Our objective was to use population-level data to derive and internally validate cirrhosis surgical risk models. APPROACH AND RESULTS: We conducted a retrospective cohort study using data from the Veterans Outcomes and Costs Associated with Liver Disease (VOCAL) cohort, which contains granular data on patients with cirrhosis from 128 U.S. medical centers, merged with the Veterans Affairs Surgical Quality Improvement Program (VASQIP) to identify surgical procedures. We categorized surgeries as abdominal wall, vascular, abdominal, cardiac, chest, or orthopedic and used multivariable logistic regression to model 30-, 90-, and 180-day postoperative mortality (VOCAL-Penn models). We compared model discrimination and calibration of VOCAL-Penn to the Mayo Risk Score (MRS), Model for End-Stage Liver Disease (MELD), Model for End-Stage Liver Disease-Sodium MELD-Na, and Child-Turcotte-Pugh (CTP) scores. We identified 4,712 surgical procedures in 3,785 patients with cirrhosis. The VOCAL-Penn models were derived and internally validated with excellent discrimination (30-day postoperative mortality C-statistic = 0.859; 95% confidence interval [CI], 0.809-0.909). Predictors included age, preoperative albumin, platelet count, bilirubin, surgery category, emergency indication, fatty liver disease, American Society of Anesthesiologists classification, and obesity. Model performance was superior to MELD, MELD-Na, CTP, and MRS at all time points (e.g., 30-day postoperative mortality C-statistic for MRS = 0.766; 95% CI, 0.676-0.855) in terms of discrimination and calibration. CONCLUSIONS: The VOCAL-Penn models substantially improve postoperative mortality predictions in patients with cirrhosis. These models may be applied in practice to improve preoperative risk stratification and optimize patient selection for surgical procedures (www.vocalpennscore.com).
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