Published in:
Open Access
01-10-2011 | Research
Community-acquired polymicrobial pneumonia in the intensive care unit: aetiology and prognosis
Authors:
Catia Cillóniz, Santiago Ewig, Miquel Ferrer, Eva Polverino, Albert Gabarrús, Jorge Puig de la Bellacasa, Josep Mensa, Antoni Torres
Published in:
Critical Care
|
Issue 5/2011
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Abstract
Introduction
The frequency and clinical significance of polymicrobial aetiology in community-acquired pneumonia (CAP) patients admitted to the ICU have been poorly studied. The aim of the present study was to describe the prevalence, clinical characteristics and outcomes of severe CAP of polymicrobial aetiology in patients admitted to the ICU.
Methods
The prospective observational study included 362 consecutive adult patients with CAP admitted to the ICU within 24 hours of presentation; 196 (54%) patients had an established aetiology.
Results
Polymicrobial infection was present in 39 (11%) cases (20% of those with defined aetiology): 33 cases with two pathogens, and six cases with three pathogens. The most frequently identified pathogens in polymicrobial infections were Streptococcus pneumoniae (n = 28, 72%), respiratory viruses (n = 15, 39%) and Pseudomonas aeruginosa (n = 8, 21%). Chronic respiratory disease and acute respiratory distress syndrome criteria were independent predictors of polymicrobial aetiology. Inappropriate initial antimicrobial treatment was more frequent in the polymicrobial aetiology group compared with the monomicrobial aetiology group (39% vs. 10%, P < 0.001), and was an independent predictor of hospital mortality (adjusted odds ratio = 10.79, 95% confidence interval = 3.97 to 29.30; P < 0.001). The trend for higher hospital mortality of the polymicrobial aetiology group compared with the monomicrobial aetiology group (n = 8, 21% versus n = 17, 11%), however, was not significantly different (P = 0.10).
Conclusions
Polymicrobial pneumonia occurs frequently in patients admitted to the ICU. This is a risk factor for inappropriate initial antimicrobial treatment, which in turn independently predicts hospital mortality.