Predictive factors of mortality in severe community-acquired pneumonia: A model with data on the first 24 h of ICU admission
Abstract Objective To construct a model of factors predicting mortality in severe community-acquired pneumonia (SCAP) with data on the first 24 h after admission to the intensive care unit (ICU). Design A prospective, observational study was carried out. Setting The ICU of a university hospital. Pat...
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Veröffentlicht in: | Medicina intensiva 2013-06, Vol.37 (5), p.308-315 |
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Zusammenfassung: | Abstract Objective To construct a model of factors predicting mortality in severe community-acquired pneumonia (SCAP) with data on the first 24 h 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 24 h. 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 24 h 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 24 h of ICU admission were found to be independent predictors of mortality in SCAP patients. |
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ISSN: | 0210-5691 |
DOI: | 10.1016/j.medin.2013.03.003 |