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What factors predict length of stay in the intensive care unit? Systematic review and meta-analysis.
Peres, Igor Tona; Hamacher, Silvio; Oliveira, Fernando Luiz Cyrino; Thomé, Antônio Márcio Tavares; Bozza, Fernando Augusto.
Afiliação
  • Peres IT; Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil. Electronic address: igor.peres@aluno.puc-rio.br.
  • Hamacher S; Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil. Electronic address: hamacher@puc-rio.br.
  • Oliveira FLC; Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil. Electronic address: cyrino@puc-rio.br.
  • Thomé AMT; Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil. Electronic address: mt@puc-rio.br.
  • Bozza FA; Evandro Chagas National Institute of Infectious Disease, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil; IDOR, D'Or Institute for Research and Education, Rio de Janeiro, RJ, Brazil. Electronic address: bozza.fernando@gmail.com.
J Crit Care ; 60: 183-194, 2020 12.
Article em En | MEDLINE | ID: mdl-32841815
PURPOSE: Studies have shown that a small percentage of ICU patients have prolonged length of stay (LoS) and account for a large proportion of resource use. Therefore, the identification of prolonged stay patients can improve unit efficiency. In this study, we performed a systematic review and meta-analysis to understand the risk factors of ICU LoS. MATERIALS AND METHODS: We searched MEDLINE, Embase and Scopus databases from inception to November 2018. The searching process focused on papers presenting risk factors of ICU LoS. A meta-analysis was performed for studies reporting appropriate statistics. RESULTS: From 6906 citations, 113 met the eligibility criteria and were reviewed. A meta-analysis was performed for six factors from 28 papers and concluded that patients with mechanical ventilation, hypomagnesemia, delirium, and malnutrition tend to have longer stay, and that age and gender were not significant factors. CONCLUSIONS: This work suggested a list of risk factors that should be considered in prediction models for ICU LoS, as follows: severity scores, mechanical ventilation, hypomagnesemia, delirium, malnutrition, infection, trauma, red blood cells, and PaO2:FiO2. Our findings can be used by prediction models to improve their predictive capacity of prolonged stay patients, assisting in resource allocation, quality improvement actions, and benchmarking analysis.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Respiração Artificial / Índice de Gravidade de Doença / Delírio / Unidades de Terapia Intensiva / Tempo de Internação / Deficiência de Magnésio Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: J Crit Care Assunto da revista: TERAPIA INTENSIVA Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Respiração Artificial / Índice de Gravidade de Doença / Delírio / Unidades de Terapia Intensiva / Tempo de Internação / Deficiência de Magnésio Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: J Crit Care Assunto da revista: TERAPIA INTENSIVA Ano de publicação: 2020 Tipo de documento: Article