18 May 2020 : Database Analysis
Prognostic Value of Neutrophil-Lymphocyte Ratio in Cardiogenic Shock: A Cohort Study
Yangpei Peng1ADE, Jie Wang2ABC, Huaqiang Xiang1BCF, Yingbei Weng1BD, Fangning Rong1FG, Yangjing Xue1AEG, Kangting Ji1ADG*DOI: 10.12659/MSM.922167
Med Sci Monit 2020; 26:e922167
Abstract
BACKGROUND: Inflammation plays an important part in the pathogenesis of cardiogenic shock (CGS). Whether the neutrophil-lymphocyte ratio (NLR), an integrated biomarker of inflammation, is associated with the outcome of CGS patients remains unknown. This retrospective cohort study was performed to identify the utility of using NLR among patients with CGS.
MATERIAL AND METHODS: Data were extracted from the MIMIC database. We applied smooth curve fitting to define the NLR cutoff values. The primary outcome was 30-day mortality. Cox proportional hazards models, subgroup analysis, and receiver operator characteristic (ROC) curve analysis were performed.
RESULTS: A total of 1470 CGS patients were extracted, among which 801 (54.5%) were men. The mean age of the population was 70.37 years. An inverse U-shaped relationship was observed between NLR and mortality in CGS patients, with the highest risk being at values ranging from 9.4 to 15. For the primary outcome of 30-day mortality, the adjusted HR (95% CI) values of the middle tertile (NLR 9.4–15) and the upper tertile (NLR >15) were 1.47 (1.14, 1.88) and 1.22 (0.94, 1.57) compared with the reference of lower tertile (NLR <9.4). ROC curve analysis showed that NLR had a more sensitive prognostic value in predicting 30-day mortality of CGS than the neutrophil or lymphocyte percentage alone (0.660 vs. 0.540, 0.549).
CONCLUSIONS: An inverse U-shaped curve was presented between NLR and the mortality of CGS. NLR seemed to be a readily available and independent prognostic biomarker for patients with CGS. The prognostic value of NLR was more sensitive than the neutrophil or lymphocyte percentage alone, but not as good as SOFA or SAPSII score.
Keywords: Immunity, Lymphocytes, Neutrophils, Shock, Cardiogenic, Aged, 80 and over, Cohort Studies, Databases, Factual, Leukocyte Count, Lymphocyte Count, Proportional Hazards Models, ROC Curve
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