TY - JOUR
T1 - C-Reactive protein in the detection of post-stroke infections
T2 - Systematic review and individual participant data analysis
AU - Bustamante, Alejandro
AU - Vilar-Bergua, Andrea
AU - Guettier, Sophie
AU - Sánchez-Poblet, Josep
AU - García-Berrocoso, Teresa
AU - Giralt, Dolors
AU - Fluri, Felix
AU - Topakian, Raffi
AU - Worthmann, Hans
AU - Hug, Andreas
AU - Molnar, Tihamer
AU - Waje-Andreassen, Ulrike
AU - Katan, Mira
AU - Smith, Craig J
AU - Montaner, Joan
N1 - This article is protected by copyright. All rights reserved.
PY - 2017
Y1 - 2017
N2 - 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 ROC curves and integrated discrimination improvement index (IDI). Data from seven studies including 699 patients were obtained. Standardized CRP levels were higher in patients with post-stroke infections beyond 24 hours. Standardized CRP levels in the fourth quartile were independently associated with infection in two different logistic regression models, model 1 [stroke severity and dysphagia, OR=9.70(3.10-30.41)] and model 2 [age, sex and stroke severity, OR=3.21(1.93-5.32)]. Addition of CRP improved discrimination in both models [IDI=9.83% (0.89-18.77) and 5.31% (2.83-7.79), respectively], but accuracy was only improved for model 1 (AUC 0.806 to 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 hours. However, its additional predictive value is moderate over clinical information. Combination with other biomarkers in a panel seems a promising strategy for future studies. This article is protected by copyright. All rights reserved.
AB - 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 ROC curves and integrated discrimination improvement index (IDI). Data from seven studies including 699 patients were obtained. Standardized CRP levels were higher in patients with post-stroke infections beyond 24 hours. Standardized CRP levels in the fourth quartile were independently associated with infection in two different logistic regression models, model 1 [stroke severity and dysphagia, OR=9.70(3.10-30.41)] and model 2 [age, sex and stroke severity, OR=3.21(1.93-5.32)]. Addition of CRP improved discrimination in both models [IDI=9.83% (0.89-18.77) and 5.31% (2.83-7.79), respectively], but accuracy was only improved for model 1 (AUC 0.806 to 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 hours. However, its additional predictive value is moderate over clinical information. Combination with other biomarkers in a panel seems a promising strategy for future studies. This article is protected by copyright. All rights reserved.
U2 - 10.1111/jnc.13973
DO - 10.1111/jnc.13973
M3 - Article
C2 - 28171699
SN - 0022-3042
JO - Journal of neurochemistry
JF - Journal of neurochemistry
ER -