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J Crit Care ; 29(1): 60-5, 2014 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-24268622

RESUMO

PURPOSE: To describe the admission factors associated with prolonged (>14 days) intensive care unit (ICU) stay (PIS). MATERIALS AND METHODS: Retrospective analysis of 3257 admissions during a 1.5-year period in a tertiary hospital. We tested the association between clinically relevant variables and PIS (>14 days) through binary logistic regression using the backward method. A Kaplan-Meier curve and the log-rank test were used to compare hospital outcomes for ICU survivors between patients with and without PIS. RESULTS: In total, 6.6% of all admissions had a prolonged stay, consuming over 40% of all ICU bed-days. Illness severity; respiratory support at admission; performance status; readmission; admission from a ward, emergency room or other hospital; admission due to intracranial mass effect; severe chronic obstructive pulmonary disease; and the temperature at admission were all associated with PIS in a multivariate analysis. The created model had a good area under the curve (0.82) and was calibrated (Hosmer-Lemeshow test p = 0.431). Post hoc analysis on ICU survivors on in patients with at least two days of ICU stay yielded similar results. Hospital survival after ICU discharge was similar for patients with and without PIS (log-rank test p = 0.50). CONCLUSION: A small number of ICU admissions consume a great proportion of ICU bed-days. Illness severity, a need for support and performance status are important predictors of PIS. Patients who survive a PIS have similar hospital mortality to patients with a shorter stay.


Assuntos
Estado Terminal , Unidades de Terapia Intensiva/estatística & dados numéricos , Tempo de Internação/estatística & dados numéricos , Admissão do Paciente/estatística & dados numéricos , Idoso , Idoso de 80 Anos ou mais , Brasil , Comorbidade , Feminino , Mortalidade Hospitalar , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Readmissão do Paciente/estatística & dados numéricos , Respiração Artificial/estatística & dados numéricos , Estudos Retrospectivos , Índice de Gravidade de Doença , Centros de Atenção Terciária/estatística & dados numéricos , Fatores de Tempo , Resultado do Tratamento
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