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BioMed Research International
Volume 2013 (2013), Article ID 504136, 12 pages
http://dx.doi.org/10.1155/2013/504136
Review Article

Risk Prediction Models for Mortality in Community-Acquired Pneumonia: A Systematic Review

1Norfolk and Norwich University Hospital, Colney Lane, Norwich NR4 7UY, UK
2Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
3School of Medicine & Dentistry, Division of Applied Health Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK

Received 30 April 2013; Accepted 7 August 2013

Academic Editor: Demosthenes Bouros

Copyright © 2013 Chun Shing Kwok et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background. Several models have been developed to predict the risk of mortality in community-acquired pneumonia (CAP). This study aims to systematically identify and evaluate the performance of published risk prediction models for CAP. Methods. We searched MEDLINE, EMBASE, and Cochrane library in November 2011 for initial derivation and validation studies for models which predict pneumonia mortality. We aimed to present the comparative usefulness of their mortality prediction. Results. We identified 20 different published risk prediction models for mortality in CAP. Four models relied on clinical variables that could be assessed in community settings, with the two validated models BTS1 and CRB-65 showing fairly similar balanced accuracy levels (0.77 and 0.72, resp.), while CRB-65 had AUROC of 0.78. Nine models required laboratory tests in addition to clinical variables, and the best performance levels amongst the validated models were those of CURB and CURB-65 (balanced accuracy 0.73 and 0.71, resp.), with CURB-65 having an AUROC of 0.79. The PSI (AUROC 0.82) was the only validated model with good discriminative ability among the four that relied on clinical, laboratorial, and radiological variables. Conclusions. There is no convincing evidence that other risk prediction models improve upon the well-established CURB-65 and PSI models.