The Effectiveness of Neutrophil-Lymphocyte Ratio in Predicting in-Hospital Mortality in Non-ST-Elevation Myocardial Infarction. (9th March 2020)

• Record Type: Journal Article
• Authors: Avci, Begüm Şeyda; Avci, Akkan; Dönmez, Yurdaer; Kaya, Adem; Gülen, Müge; Özer, Ali İlker; Bulut, Atilla; Koç, Mevlüt; Nazik, Hakan; Satar, Salim
• Other Names: Kam Chak W. Academic Editor.
• Is Part Of: Emergency medicine international. Volume 2020(2020)
• Publication Date: 2020-03-09
• Subjects: Emergency medicine -- Periodicals; Medical emergencies -- Periodicals; 616.025
• DOI: 10.1155/2020/8718304
• Languages: English
• ISSNs: 2090-2840

Abstract

Abstract : Background . Myocardial infarction is the most common cause of death all over the world. There are many studies in predicting mortality. The aim of this study was to determine the effectiveness of hematologic parameters measured at the moment of admission to the emergency room in predicting in-hospital mortality and to determine cutoff values of strongly predictive values. Methods . A total of 681 patients over 18 years of age, whose date could be obtained, were included in the study. From the hemogram parameters, white blood cells (WBC), red cell distribution width (RDW), mean platelet volume (MPV), and neutrophils-to-lymphocytes ratio (NLR) values were determined and recorded. CK-MB and high-sensitive troponin T values were recorded as cardiac markers. For statistical analysis, "SPSS for Windows version 21" package program was used. Results . 62.6% ( n = 426) of the patients were male, and 37.4% ( n = 255) of the patients were female. The NLR was found to be the strongest predictor (area under the curve (AUC), 0.783, SD = 0.052, 95% confidence interval (CI)). It was found that the WBC value came in the second place after NLR as a strong predictor of mortality (AUC, 0.702, SD = 0.075, 95% CI). Conclusion . According to the hemogram results which were acquired with a simple and cheap method, we found that WBC and especially NLR values obtained with a simple method can be used as powerful predictors.