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Clinical aspects and prognostic factors in elderly patients hospitalised for community-acquired pneumonia
The aims of this study were to determine the clinical and epidemiological characteristics of community-acquired pneumonia (CAP) in the elderly, to identify prognostic factors, and to establish a predictive model for mortality of CAP. Elderly patients with CAP admitted to "Carlos Haya" Hosp...
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Published in: | European journal of clinical microbiology & infectious diseases 2001-01, Vol.20 (1), p.14-19 |
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Main Authors: | , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | The aims of this study were to determine the clinical and epidemiological characteristics of community-acquired pneumonia (CAP) in the elderly, to identify prognostic factors, and to establish a predictive model for mortality of CAP. Elderly patients with CAP admitted to "Carlos Haya" Hospital in Malaga, Spain, over a 36-month period were included. Multivariate analysis was used to identify prognostic factors from variables present on admission, from which a discrimination rule was constructed to predict mortality. A total of 343 patients were included, with the annual incidence ranging from 16.3 to 28.1 per 1,000 admissions. Most (82.5%) had some kind of accompanying or underlying disease. Clinical presentation was atypical in 87 (25.4%). Microbiological diagnosis was made in 24.5%. There were 49 (14.3%) deaths. The prognostic factors in multivariate analysis on admission were bilateral radiographic infiltrate, a blood urea nitrogen level of more than 7 mmol/l, absence of fever, a respiratory rate of 30/min or more, confusion, and shock. The discriminating rule to predict mortality comprising three or more of these factors was 91.2% specific, with a negative predictive value of 93.4% and an overall accuracy of 86.9%. CAP in the elderly is associated with a high degree of mortality. The discriminating rule incorporating the prognostic factors identified is a powerful predictor of mortality. |
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ISSN: | 0934-9723 1435-4373 |
DOI: | 10.1007/s100960000413 |