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Pharm World Sci ; 26(5): 263-7, 2004 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-15598066

RESUMO

INTRODUCTION: The length of stay (LOS) in patients admitted to intensive care units (ICUs) is influenced by the clinical history of the patient, so the main factors affecting clinical outcome are logical candidates to be predictors of LOS. Since there is still limited information about which factors can influence LOS in these patients, we undertook this observational study in Italian hospitals. MATERIALS AND METHODS: From 1 August to 31 October 2001 we enrolled a maximum of 10 consecutive patients admitted to ICUs in 16 Italian hospitals. The following information was recorded from each patient: date of admission; APACHE II score on admission; active sepsis and/or septic shock on admission; sepsis and/or septic shock developed during the stay in ICU; Glasgow coma scale on the third day; date and clinical outcome upon discharge from the hospital (alive or dead). RESULTS: In the study 131 patients were enrolled; 31 (23.7%) had active sepsis upon admission to ICU and 10 (7.6%) had septic shock; 12 (9.2%) developed sepsis during hospitalization and 12 (9.2%) developed septic shock. At the end of the study, 101 patients were alive and 30 had died. The overall mean LOS was 12 days. The mean LOS was 18.3 days for the subgroup with sepsis and 8.3 days in the subgroup without sepsis. Sepsis was the only factor that significantly influenced the LOS (P = 0.016). CONCLUSIONS: Our study was aimed to analyse the factors that influence the LOS in ICU patients and found that among the variables that affected LOS, sepsis had the greatest impact. Other studies had evaluated the impact of some variables on LOS and identified sepsis and infection as a determinant prolonging LOS.


Assuntos
Unidades de Terapia Intensiva , Tempo de Internação , Observação/métodos , Adulto , Idoso , Intervalos de Confiança , Feminino , Humanos , Unidades de Terapia Intensiva/estatística & dados numéricos , Tempo de Internação/estatística & dados numéricos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Modelos de Riscos Proporcionais , Estudos Prospectivos , Fatores de Risco
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