Biomarkers for predicting short-term mortality in community-acquired pneumonia: A systematic review and meta-analysis.
J Infect. 2016 Jan 14;
Authors: Viasus D, Del Rio-Pertuz G, Simonetti AF, Garcia-Vidal C, Acosta-Reyes J, Garavito A, Carratalà J
OBJECTIVES: The Pneumonia Severity Index and CURB-65 are risk assessment tools widely used in community-acquired pneumonia (CAP). However, limitations in these prognostic scores have led to increasing interest in finding biomarkers that might provide additional information. To date, the role of these biomarkers has not been fully elucidated.
METHODS: We systematically searched the Medline, Web of Knowledge, Science Direct, and LILACS databases. We included studies that assessed the accuracy of biomarkers for the prediction of in-hospital or ≤30-day mortality, in hospitalized adults with CAP. Two independent investigators extracted patient and study characteristics, which were thereafter pooled using a random effects model. Relationships between sensitivity and specificity of biomarkers and prognostic scores were plotter using the area under the receiver operator characteristic curve (AUC).
RESULTS: We included 24 articles and 2 databases from 1,069 reviewed abstracts, which provided 10,319 patients for analysis. Reported mortality rates varied from 2.4% to 34.6%. The highest AUC values for predicting mortality were associated with pro-adrenomedullin (0.80) and prohormone forms of atrial natriuretic peptide (0.79), followed by cortisol (0.78), procalcitonin (0.75), copeptin (0.71), and C-reactive protein (0.62). There were no statistically significant differences between the AUCs of the studied biomarkers, other than for copeptin and C-reactive protein, which performed comparatively poorly. When compared with the CAP-specific scores, the AUCs were not significantly different from those of most biomarkers.
CONCLUSIONS: The identified biomarkers are able to predict mortality with moderate to good accuracy in CAP. However, biomarkers have no clear advantage over CAP-specific scores for predicting mortality.
PMID: 26777314 [PubMed - as supplied by publisher]