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Meta-Analysis
. 2017 Apr;141(2):305-314.
doi: 10.1111/jnc.13973. Epub 2017 Mar 8.

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

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Free article
Meta-Analysis

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

Alejandro Bustamante et al. J Neurochem. 2017 Apr.
Free article

Abstract

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.

Keywords: C-reactive protein; biomarkers; individual participant data meta-analysis; infections; stroke; systematic review.

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