Development and validation of a clinical prediction rule for severe community-acquired pneumonia.

Am J Respir Crit Care Med

Service of Pneumology, Department of Emergency Medicine, Research Unit, Hospital de Galdakao, Galdako, Bizkaia, Spain.

Published: December 2006

Rationale: Objective strategies are needed to improve the diagnosis of severe community-acquired pneumonia in the emergency department setting.

Objectives: To develop and validate a clinical prediction rule for identifying patients with severe community-acquired pneumonia, comparing it with other prognostic rules.

Methods: Data collected from clinical information and physical examination of 1,057 patients visiting the emergency department of a hospital were used to derive a clinical prediction rule, which was then validated in two different populations: 719 patients from the same center and 1,121 patients from four other hospitals.

Measurements And Main Results: In the multivariate analyses, eight independent predictive factors were correlated with severe community-acquired pneumonia: arterial pH < 7.30, systolic blood pressure < 90 mm Hg, respiratory rate > 30 breaths/min, altered mental status, blood urea nitrogen > 30 mg/dl, oxygen arterial pressure < 54 mm Hg or ratio of arterial oxygen tension to fraction of inspired oxygen < 250 mm Hg, age > or = 80 yr, and multilobar/bilateral lung affectation. From the beta parameter obtained in the multivariate model, a score was assigned to each predictive variable. The model shows an area under the curve of 0.92. This rule proved better at identifying patients evolving toward severe community-acquired pneumonia than either the modified American Thoracic Society rule, the British Thoracic Society's CURB-65, or the Pneumonia Severity Index.

Conclusions: A simple score using clinical data available at the time of the emergency department visit provides a practical diagnostic decision aid, and predicts the development of severe community-acquired pneumonia.

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Source
http://dx.doi.org/10.1164/rccm.200602-177OCDOI Listing

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