Author:
Anoop K. V.,Devadas Krishnadas,Varghese Jijo
Abstract
Abstract
Background
Declining eosinophil count has recently been associated with sepsis. Thus, absolute eosinophil count (AEC) can be used as a marker of the severity of sepsis, which helps in the early identification of high-risk patients, and better management can be offered to such patients. The aim of this study was to assess whether AEC at the time of ICU admission can be used as a predictor of in-hospital mortality in cirrhotics with sepsis.
Results
This was a retrospective study which was conducted in 105 cirrhotic patients admitted with sepsis in the Department of Gastroenterology, Medical College Trivandrum, from May 2014 to October 2014. Every consecutive patient with cirrhosis and sepsis (defined as systemic inflammatory response syndrome (SIRS) and the presence of infections) admitted to the ICU/high dependency unit was recruited for the study. Among the various parameters analyzed, model for end-stage liver disease (MELD) score, Child-Pugh Turcot (CTP) score, albumin levels, total count, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), alanine aminotransferase (ALT), bilirubin, creatinine, urea, and absolute eosinophil count were statistically significant in predicting in-hospital mortality. The AUROC of AEC was plotted and found to be 0.881, which was better than other parameters for predicting in-hospital mortality. The cutoff of AEC by Youden’s index was 110 cells/cumm (sensitivity 91.3%, specificity 89%, positive predictive value 87.5%, and negative predictive value 93%) to predict in-hospital mortality. The AUROC of MELD was 0.78 with a cutoff of > 24 (sensitivity 89%, specificity 74.6%, positive predictive value 73%, and negative predictive value 89%) to predict the mortality. The odds ratio for predicting mortality was highest for absolute eosinophil count (92.75) followed by MELD (24.57), total count (20.475), CTP (10), and the presence of SIRS (9.08).
Conclusion
In critically ill cirrhosis patients with sepsis, AEC < 110 cells/cumm can predict in-hospital mortality.
Publisher
Springer Science and Business Media LLC
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