Retrospective Cohort Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Jun 27, 2020; 12(6): 298-311
Published online Jun 27, 2020. doi: 10.4254/wjh.v12.i6.298
LIV-4: A novel model for predicting transplant-free survival in critically ill cirrhotics
Christina C Lindenmeyer, Gianina Flocco, Vedha Sanghi, Rocio Lopez, Ahyoung J Kim, Fadi Niyazi, Neal A Mehta, Aanchal Kapoor, William D Carey, Eduardo Mireles-Cabodevila, Carlos Romero-Marrero
Christina C Lindenmeyer, Gianina Flocco, Neal A Mehta, William D Carey, Carlos Romero-Marrero, Department of Gastroenterology, Hepatology and Nutrition, Cleveland Clinic, Cleveland, OH 44195, United States
Vedha Sanghi, Ahyoung J Kim, Fadi Niyazi, Department of Internal Medicine, Cleveland Clinic, Cleveland, OH 44195, United States
Rocio Lopez, Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44106, United States
Aanchal Kapoor, Eduardo Mireles-Cabodevila, Department of Critical Care Medicine, Cleveland Clinic, Cleveland, OH 44195, United States
Author contributions: Lindenmeyer CC designed the study and drafted the article; Lindenmeyer CC, Flocco G, Sanghi V, Kim AJ, Niyazi F and Mehta NA acquired data; Lindenmeyer CC, Lopez R, Kapoor A, Carey WD, Mireles-Cabodevila E and Romero-Marrero C analyzed and interpreted data; all of the authors made critical revision for important intellectual content and final approval.
Institutional review board statement: The study was reviewed and approved by the Cleveland Clinic Foundation Institutional Review Board.
Informed consent statement: The Cleveland Clinic Foundation Institutional Review Board waives the written consent for all retrospective medical record reviews done for research purposes (as the one done for this study) if the investigators can ensure there are adequate protections to maintain the data in a secure manner with access limited to the study team and if sharing or releasing identifiable data to any outside person or entity will not occur. For this reason, no Informed Consent Form was used for this study.
Conflict-of-interest statement: There are no conflicts of interest associated with any of the senior authors or other coauthors who contributed their efforts to this manuscript. All the authors have no conflict of interest related to the manuscript.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Christina C Lindenmeyer, MD, Staff Physician, Assistant Professor of Medicine, Department of Gastroenterology, Hepatology and Nutrition, Cleveland Clinic, 9500 Euclid Avenue, Mail Code A51, Cleveland, OH 44195, United States. lindenc@ccf.org
Received: January 26, 2020
Peer-review started: January 26, 2020
First decision: March 15, 2020
Revised: May 15, 2020
Accepted: May 19, 2020
Article in press: May 19, 2020
Published online: June 27, 2020
Processing time: 154 Days and 5.3 Hours
Abstract
BACKGROUND

Critically ill patients with cirrhosis, particularly those with acute decompensation, have higher mortality rates in the intensive care unit (ICU) than patients without chronic liver disease. Prognostication of short-term mortality is important in order to identify patients at highest risk of death. None of the currently available prognostic models have been widely accepted for use in cirrhotic patients in the ICU, perhaps due to complexity of calculation, or lack of universal variables readily available for these patients. We believe a survival model meeting these requirements can be developed, to guide therapeutic decision-making and contribute to cost-effective healthcare resource utilization.

AIM

To identify markers that best identify likelihood of survival and to determine the performance of existing survival models.

METHODS

Consecutive cirrhotic patients admitted to a United States quaternary care center ICU between 2008-2014 were included and comprised the training cohort. Demographic data and clinical laboratory test collected on admission to ICU were analyzed. Area under the curve receiver operator characteristics (AUROC) analysis was performed to assess the value of various scores in predicting in-hospital mortality. A new predictive model, the LIV-4 score, was developed using logistic regression analysis and validated in a cohort of patients admitted to the same institution between 2015-2017.

RESULTS

Of 436 patients, 119 (27.3%) died in the hospital. In multivariate analysis, a combination of the natural logarithm of the bilirubin, prothrombin time, white blood cell count, and mean arterial pressure was found to most accurately predict in-hospital mortality. Derived from the regression coefficients of the independent variables, a novel model to predict inpatient mortality was developed (the LIV-4 score) and performed with an AUROC of 0.86, compared to the Model for End-Stage Liver Disease, Chronic Liver Failure-Sequential Organ Failure Assessment, and Royal Free Hospital Score, which performed with AUROCs of 0.81, 0.80, and 0.77, respectively. Patients in the internal validation cohort were substantially sicker, as evidenced by higher Model for End-Stage Liver Disease, Model for End-Stage Liver Disease-Sodium, Acute Physiology and Chronic Health Evaluation III, SOFA and LIV-4 scores. Despite these differences, the LIV-4 score remained significantly higher in subjects who expired during the hospital stay and exhibited good prognostic values in the validation cohort with an AUROC of 0.80.

CONCLUSION

LIV-4, a validated model for predicting mortality in cirrhotic patients on admission to the ICU, performs better than alternative liver and ICU-specific survival scores.

Keywords: Risk stratification; Resource allocation; Intensive care unit; Acute-on-chronic liver failure; Modeling; Mortality

Core tip: Critically ill patients with cirrhosis have higher mortality rates in the intensive care unit (ICU) than patients without chronic liver disease. None of the currently available prognostic models have been widely accepted for use in cirrhotic patients in the ICU, perhaps due to complexity of calculation. We believe survival modeling can guide therapeutic decision-making and contribute to cost-effective healthcare resource utilization. We describe the development of a novel model to predict in-hospital mortality in critically ill patients with cirrhosis. Our validated model for predicting mortality on admission to the ICU performs better than previously published liver and ICU-specific scores.