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Clinics ; 68(8): 1103-1108, 2013. tab, graf
Artigo em Inglês | LILACS | ID: lil-685438

RESUMO

OBJECTIVES: Medical and surgical intensive care unit patients represent two different populations and require different treatment approaches. The aim of this study was to investigate the parameters associated with mortality in medical and surgical intensive care units. METHODS: This was a prospective cohort study of adult patients admitted to a medical and surgical intensive care unit teaching hospital over an 11-month period. Factors associated with mortality were explored using logistic regression analysis. RESULTS: In total, 827 admissions were observed, and 525 patients >18 years old and with a length of stay >24 h were analyzed. Of these patients, 227 were in the medical and 298 were in the surgical intensive care unit. The surgical patients were older (p<0.01) and had shorter lengths of stay (p<0.01). The mortality in the intensive care unit (35.1 vs. 26.2, p = 0.02) and hospital (48.8 vs. 35.5, p<0.01) was higher for medical patients. For patients in the surgical intensive care unit, death was independently associated with the need for mechanical ventilation, prognostic score (SAPS II), community-acquired infection, nosocomial infection, and intensive care unit-acquired infection. For patients in the medical intensive care unit, death was independently associated with the need for mechanical ventilation and prognostic score. CONCLUSIONS: Although the presence of infection is associated with a high mortality in both the medical and surgical intensive care units, the results of this prospective study suggest that infection has a greater impact in patients admitted to the surgical intensive care unit. Measures and trials to prevent and treat sepsis may be most effective in the surgical intensive care unit population. .


Assuntos
Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Infecção Hospitalar/mortalidade , Mortalidade Hospitalar , Unidades de Terapia Intensiva/estatística & dados numéricos , Cuidados Críticos/estatística & dados numéricos , Brasil/epidemiologia , Estimativa de Kaplan-Meier , Modelos Logísticos , Tempo de Internação/estatística & dados numéricos , Avaliação de Resultados em Cuidados de Saúde , Estudos Prospectivos , Admissão do Paciente/estatística & dados numéricos , Fatores de Risco , Fatores de Tempo
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