Nadim Mahmud1, Zachary Fricker2, James D Lewis3, Tamar H Taddei4, David S Goldberg5, David E Kaplan6. 1. Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Leonard David Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania; Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: nadim@pennmedicine.upenn.edu. 2. Division of Gastroenterology, Hepatology, and Nutrition, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts. 3. Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. 4. Division of Digestive Diseases, Yale University School of Medicine, New Haven, Connecticut; VA Connecticut Healthcare System, West Haven, Connecticut. 5. Division of Digestive Health and Liver Diseases, Department of Medicine, University of Miami Miller School of Medicine, Miami, Florida. 6. Division of Gastroenterology and Hepatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania.
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 < .001); however, discrimination was only fair for postoperative infection (C-statistic 0.666 vs 0.592 Mayo [P = .13] vs 0.502 MELD-sodium [P < .001] vs 0.503 CTP [P < .001]). The model for interval decompensation had excellent calibration in both derivation and validation sets. CONCLUSION: We report the derivation and internal validation of a novel, parsimonious prediction model for postoperative decompensation in patients with cirrhosis. This score demonstrated superior discrimination and calibration as compared with existing clinical standards, and will be available at www.vocalpennscore.com.
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 < .001); however, discrimination was only fair for postoperative infection (C-statistic 0.666 vs 0.592 Mayo [P = .13] vs 0.502 MELD-sodium [P < .001] vs 0.503 CTP [P < .001]). The model for interval decompensation had excellent calibration in both derivation and validation sets. CONCLUSION: We report the derivation and internal validation of a novel, parsimonious prediction model for postoperative decompensation in patients with cirrhosis. This score demonstrated superior discrimination and calibration as compared with existing clinical standards, and will be available at www.vocalpennscore.com.
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