Literature DB >> 23669439

Predictive factors of mortality in severe community-acquired pneumonia: a model with data on the first 24h of ICU admission.

J M Sirvent1, M Carmen de la Torre, C Lorencio, A Taché, C Ferri, J Garcia-Gil, A Torres.   

Abstract

OBJECTIVE: To construct a model of factors predicting mortality in severe community-acquired pneumonia (SCAP) with data on the first 24h after admission to the intensive care unit (ICU).
DESIGN: A prospective, observational study was carried out.
SETTING: The ICU of a university hospital. PATIENTS: ICU-admitted patients with SCAP were studied prospectively.
INTERVENTIONS: Admission pneumonia scores were calculated, and clinical variables were registered during the first 24h. Relationships between predictors of mortality at 28 days were assessed by means of a multivariate logistic regression model.
RESULTS: A total number of 242 SCAP patients were evaluated. The SAPS II severity score was 37.2±15.5 points. Bivariate analysis showed high mortality to be more frequent in elderly patients, as well as in patients with high SAPS II scores, neoplastic disease or chronic renal failure. The other prognostic factors related to increased mortality included mechanical ventilation, acute respiratory distress syndrome (ARDS), acute renal failure, bacteremia, and septic shock. Mortality at 28 days was 23.1% (56 patients). Multivariate analysis of the risk factors generated a new predictive model of mortality applicable within the first 24h after ICU admission and comprising 5 main factors: age, CURB severity score 3-4, septic shock, ARDS, and acute renal failure.
CONCLUSIONS: Age in years, CURB score 3-4, septic shock, ARDS, and acute renal failure during the first 24h of ICU admission were found to be independent predictors of mortality in SCAP patients.
Copyright © 2012 Elsevier España, S.L. and SEMICYUC. All rights reserved.

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Year:  2013        PMID: 23669439     DOI: 10.1016/j.medin.2013.03.003

Source DB:  PubMed          Journal:  Med Intensiva        ISSN: 0210-5691            Impact factor:   2.491


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