C-reactive protein in the detection of post-stroke infections: systematic review and individual participant data analysis

四分位数 冲程(发动机) 医学 逻辑回归 优势比 C反应蛋白 内科学 接收机工作特性 荟萃分析 置信区间 炎症 机械工程 工程类
作者
Alejandro Bustamante,Andrea Vilar-Bergua,Sophie Guettier,Josep Sánchez-Poblet,Teresa García-Berrocoso,Dolors Giralt,Felix Fluri,Raffi Topakian,Hans Worthmann,Andreas Hug,Tihamer Molnar,Ulrike Waje-Andreassen,Mira Katan,Craig J. Smith,Joan Montaner
出处
期刊:Journal of Neurochemistry [Wiley]
卷期号:141 (2): 305-314 被引量:21
标识
DOI:10.1111/jnc.13973
摘要

We conducted a systematic review and individual participant data meta-analysis to explore the role of C-reactive protein (CRP) in early detection or prediction of post-stroke infections. CRP, an acute-phase reactant binds to the phosphocholine expressed on the surface of dead or dying cells and some bacteria, thereby activating complement and promoting phagocytosis by macrophages. We searched PubMed up to May-2015 for studies measuring CRP in stroke and evaluating post-stroke infections. Individual participants’ data were merged into a single database. CRP levels were standardized and divided into quartiles. Factors independently associated with post-stroke infections were determined by logistic regression analysis and the additional predictive value of CRP was assessed by comparing areas under receiver operating characteristic curves and integrated discrimination improvement index. Data from seven studies including 699 patients were obtained. Standardized CRP levels were higher in patients with post-stroke infections beyond 24 h. Standardized CRP levels in the fourth quartile were independently associated with infection in two different logistic regression models, model 1 [stroke severity and dysphagia, odds ratio = 9.70 (3.10–30.41)] and model 2 [age, sex, and stroke severity, odds ratio = 3.21 (1.93–5.32)]. Addition of CRP improved discrimination in both models [integrated discrimination improvement = 9.83% (0.89–18.77) and 5.31% (2.83–7.79), respectively], but accuracy was only improved for model 1 (area under the curve 0.806–0.874, p = 0.036). In this study, CRP was independently associated with development of post-stroke infections, with the optimal time-window for measurement at 24–48 h. However, its additional predictive value is moderate over clinical information. Combination with other biomarkers in a panel seems a promising strategy for future studies.

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