Predictive value of C-reactive protein to lymphocyte ratio for stroke-associated pneumonia
10.3760/cma.j.issn.1673-4165.2021.08.006
- VernacularTitle:C反应蛋白/淋巴细胞比值对卒中相关性肺炎的预测价值
- Author:
Xinsheng ZHANG
1
;
Wei LI
;
Jiazhi CHENG
;
Jianping ZHANG
Author Information
1. 聊城市光明眼科医院神经内科 252004
- Keywords:
Stroke;
Brain ischemia;
Pneumonia;
C-reactive protein;
Lymphocyte count;
Risk factors;
Biomarkers;
Predictive value of tests
- From:
International Journal of Cerebrovascular Diseases
2021;29(8):589-593
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the predictive value of C-reactive protein to lymphocyte ratio (CLR) for stroke-associated pneumonia (SAP).Methods:Consecutive patients with acute ischemic stroke admitted to the Department of Neurology, Guangming Ophthalmic Hospital from September 2018 to December 2020 were enrolled retrospectively. Fasting venous blood was taken the next morning after admission to detect the levels of C-reactive protein and lymphocytes. The baseline clinical data of the patients in the SAP group and the non-SAP group were compared. Multivariate logistic regression analysis was used to identify the independent predictors of SAP. The predictive value of CLR for SAP was evaluated by receiver operator characteristic (ROC) curve analysis. Results:A total of 479 patients with acute ischemic stroke were included. The median CLR was 3.69×10 -9, 81 patients (16.9%) had SAP. The incidence of SAP in the high CLR group was significantly higher than that in the low CLR group (26.7% vs. 7.1%; P=0.001). Univariate analysis showed that there were significant differences in age, atrial fibrillation, dysphagia, baseline National Institutes of Health Stroke Scale score, stroke etiology type, leukocyte count, fasting blood glucose, total cholesterol and CLR between the SAP group and the non-SAP group (all P<0.05). Multivariate logistic regression analysis showed that after adjusting for confounding factors, CLR was an independent predictor of SAP (odds ratio 3.472, 95% confidence interval 1.431-14.706; P=0.013). ROC curve analysis showed that the area under the curve of CLR predicting SAP was 0.735 (95% confidence interval 0.693-0.774; P<0.001). The optimal cut-off value was 6.14 ×10 -9. The sensitivity and specificity were 69.1% and 72.6% respectively. Conclusion:Higher baseline CLR can predict SAP risk in patients with acute ischemic stroke.
