Cargando…
LIV-4: A novel model for predicting transplant-free survival in critically ill cirrhotics
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 ri...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7364328/ https://www.ncbi.nlm.nih.gov/pubmed/32742572 http://dx.doi.org/10.4254/wjh.v12.i6.298 |
Sumario: | 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. |
---|