David G Koch1, Holly Tillman2, Valerie Durkalski2, William M Lee3, Adrian Reuben4. 1. Division of Gastroenterology and Hepatology, Medical University of South Carolina, Charleston, South Carolina. Electronic address: kochd@musc.edu. 2. Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina. 3. Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center at Dallas, Dallas, Texas. 4. Division of Gastroenterology and Hepatology, Medical University of South Carolina, Charleston, South Carolina.
Abstract
BACKGROUND & AIMS: Patients with acute liver failure (ALF) have a high risk of death that can be substantially reduced with liver transplantation. It is a challenge to predict which patients with ALF will survive without liver transplant because available prognostic scoring systems are inadequate. We devised a mathematical model, using a large dataset collected by the Acute Liver Failure Study Group, which can predict transplant-free survival in patients with ALF. METHODS: We performed a retrospective analysis of data from 1974 subjects who met criteria for ALF (coagulopathy and hepatic encephalopathy within 26 weeks of the first symptoms, without pre-existing liver disease) enrolled in the Acute Liver Failure Study Group database from January 1, 1998 through June 11, 2013. We randomly assigned the subjects to development and validation cohorts. Data from the development cohort were analyzed to identify factors associated with transplant-free survival (alive without transplantation by 21 days after admission to the study). Statistically significant variables were used to create a multivariable logistic regression model. RESULTS: Most subjects were women (70%) and white (78%); acetaminophen overdose was the most common cause (48% of subjects). The rate of transplant-free survival was 50%. Admission values of hepatic encephalopathy grade, ALF etiology, vasopressor use, and log transformations of bilirubin and international normalized ratio were significantly associated with transplant-free survival, based on logistic regression analysis. In the validation cohort, the resulting model predicted transplant-free survival with a C statistic value of 0.84, 66.3% accuracy (95% confidence interval, 63.1%-69.4%), 37.1% sensitivity (95% confidence interval, 32.5%-41.8%), and 95.3% specificity (95% confidence interval, 92.9%-97.1%). CONCLUSIONS: Using data from the Acute Liver Failure Study Group, we developed a model that predicts transplant-free survival of patients with ALF based on easily identifiable hospital admission data. External validation studies are required.
BACKGROUND & AIMS:Patients with acute liver failure (ALF) have a high risk of death that can be substantially reduced with liver transplantation. It is a challenge to predict which patients with ALF will survive without liver transplant because available prognostic scoring systems are inadequate. We devised a mathematical model, using a large dataset collected by the Acute Liver Failure Study Group, which can predict transplant-free survival in patients with ALF. METHODS: We performed a retrospective analysis of data from 1974 subjects who met criteria for ALF (coagulopathy and hepatic encephalopathy within 26 weeks of the first symptoms, without pre-existing liver disease) enrolled in the Acute Liver Failure Study Group database from January 1, 1998 through June 11, 2013. We randomly assigned the subjects to development and validation cohorts. Data from the development cohort were analyzed to identify factors associated with transplant-free survival (alive without transplantation by 21 days after admission to the study). Statistically significant variables were used to create a multivariable logistic regression model. RESULTS: Most subjects were women (70%) and white (78%); acetaminophenoverdose was the most common cause (48% of subjects). The rate of transplant-free survival was 50%. Admission values of hepatic encephalopathy grade, ALF etiology, vasopressor use, and log transformations of bilirubin and international normalized ratio were significantly associated with transplant-free survival, based on logistic regression analysis. In the validation cohort, the resulting model predicted transplant-free survival with a C statistic value of 0.84, 66.3% accuracy (95% confidence interval, 63.1%-69.4%), 37.1% sensitivity (95% confidence interval, 32.5%-41.8%), and 95.3% specificity (95% confidence interval, 92.9%-97.1%). CONCLUSIONS: Using data from the Acute Liver Failure Study Group, we developed a model that predicts transplant-free survival of patients with ALF based on easily identifiable hospital admission data. External validation studies are required.
Authors: Ewout W Steyerberg; Sacha E Bleeker; Henriëtte A Moll; Diederick E Grobbee; Karel G M Moons Journal: J Clin Epidemiol Date: 2003-05 Impact factor: 6.437
Authors: M B Zaman; E Hoti; A Qasim; D Maguire; P A McCormick; J E Hegarty; J G Geoghegan; O Traynor Journal: Transplant Proc Date: 2006-09 Impact factor: 1.066
Authors: Ewout W Steyerberg; Andrew J Vickers; Nancy R Cook; Thomas Gerds; Mithat Gonen; Nancy Obuchowski; Michael J Pencina; Michael W Kattan Journal: Epidemiology Date: 2010-01 Impact factor: 4.822
Authors: Anna Rutherford; Lindsay Y King; Linda S Hynan; Chetan Vedvyas; Wenyu Lin; William M Lee; Raymond T Chung Journal: Gastroenterology Date: 2012-08-08 Impact factor: 22.682
Authors: Angeles Baquerizo; Dean Anselmo; Christopher Shackleton; Teng-Wei Chen; Carlos Cao; Michael Weaver; Jeffrey Gornbein; Sunil Geevarghese; Nicholas Nissen; Douglas Farmer; Achilles Demetriou; Ronald W Busuttil Journal: Transplantation Date: 2003-06-27 Impact factor: 4.939
Authors: Johannes Hadem; Penelope Stiefel; Matthias J Bahr; Hans L Tillmann; Kinan Rifai; Jürgen Klempnauer; Heiner Wedemeyer; Michael P Manns; Andrea S Schneider Journal: Clin Gastroenterol Hepatol Date: 2008-03 Impact factor: 11.382
Authors: Constantine J Karvellas; Jaime L Speiser; Mélanie Tremblay; William M Lee; Christopher F Rose Journal: Hepatology Date: 2017-01-19 Impact factor: 17.425
Authors: Nina Weiler; Andreas Schlotmann; Andreas Anton Schnitzbauer; Stefan Zeuzem; Martin-Walter Welker Journal: Dtsch Arztebl Int Date: 2020-01-24 Impact factor: 5.594
Authors: Lisa C Casey; Robert J Fontana; Ariel Aday; David B Nelson; Jody A Rule; Michelle Gottfried; Minh Tran; William M Lee Journal: Hepatology Date: 2020-10-05 Impact factor: 17.425