Neutrophil-to-Lymphocyte Ratio Predicts Death in Acute-on-Chronic Liver Failure Patients Admitted to the Intensive Care Unit: A Retrospective Cohort Study

Abstract

The neutrophil-to-lymphocyte ratio (NLR) is an inflammation score recognized as associated with outcome. Although inflammation has been shown to correlate with the development of acute-on-chronic liver failure (ACLF), we sought to investigate the role of NLR in predicting 90-day mortality in cirrhotic patients experiencing ACLF. We performed a retrospective cohort study involving a total of 108 consecutive cirrhotic patients admitted in the intensive care unit (ICU). NLR, clinical and biological data were recorded. Of the total, 75 patients had ACLF. The 90-day mortality rate was 53%. ACLF patients displayed higher NLR values in comparison with cirrhotic patients without ACLF throughout the ICU stay. NLR proved more elevated in nonsurvivors ACLF patients, with mortality correlating with increasing quartiles of NLR. On multivariable Cox regression analysis, NLR was found to be a predictor of mortality along with the Sequential Organ Failure Assessment (SOFA) score and mechanical ventilation requirement. The model for end-stage liver disease (MELD) score was not predictive of 90-days mortality. Performance analysis revealed an area under curve of 0.71 [95% confidence interval: 0.59-0.82] regarding NLR capacity to predict 90-days mortality. When including NLR, SOFA score, and mechanical ventilation requirement into the final model, the area under curve was significantly higher (0.81 [95% confidence interval: 0.72-0.91]).These findings suggest that NLR is associated with mortality in ACLF patients admitted to the ICU. Combining NLR, SOFA score, and the need for mechanical ventilation could be a useful prognostic tool to identify ACLF patients at a higher risk of mortality.

Fig. 1

Severity scores, neutrophil-to-lymphocyte ratio evolution and C-reactive protein.

Fig. 2

Kaplan-Meier survival analysis across quartiles of neutrophil-to-lymphocyte ratio.

Fig. 3

Logistic regression model predicting 90-days mortality and receiver-operating characteristic curves for estimated models.