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Luiza Gabriella Antonio e Silva 1 Article
Risk factors for hospital mortality in intensive care unit survivors: a retrospective cohort study
Luiza Gabriella Antonio e Silva, Claudia Maria Dantas de Maio Carrilho, Thalita Bento Talizin, Lucienne Tibery Queiroz Cardoso, Edson Lopes Lavado, Cintia Magalhães Carvalho Grion
Acute Crit Care. 2023;38(1):68-75.   Published online February 27, 2023
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AbstractAbstract PDF
Deaths can occur after a patient has survived treatment for a serious illness in an intensive care unit (ICU). Mortality rates after leaving the ICU can be considered indicators of health care quality. This study aims to describe risk factors and mortality of surviving patients discharged from an ICU in a university hospital. Methods: Retrospective cohort study carried out from January 2017 to December 2018. Data on age, sex, length of hospital stay, diagnosis on admission to the ICU, hospital discharge outcome, presence of infection, and Simplified Acute Physiology Score (SAPS) III prognostic score were collected. Infected patients were considered as those being treated for an infection on discharge from the ICU. Patients were divided into survivors and non-survivors on leaving the hospital. The association between the studied variables was performed using the logistic regression model. Results: A total of 1,025 patients who survived hospitalization in the ICU were analyzed, of which 212 (20.7%) died after leaving the ICU. When separating the groups of survivors and non-survivors according to hospital outcome, the median age was higher among non-survivors. Longer hospital stays and higher SAPS III values were observed among non-survivors. In the logistic regression, the variables age, length of hospital stay, SAPS III, presence of infection, and readmission to the ICU were associated with hospital mortality. Conclusions: Infection on ICU discharge, ICU readmission, age, length of hospital stay, and SAPS III increased risk of death in ICU survivors.


Citations to this article as recorded by  
  • Analysis of the infectious agent’s structure and antibiotic resistance parameters in patients in intensive care units of a multidisciplinary hospital
    O. I. Butranova, S. K. Zyryanov, A. A. Gorbacheva, G A. Putsman
    Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice.2024; (4): 4.     CrossRef
  • Interpretability-based machine learning for predicting the risk of death from pulmonary inflammation in Chinese intensive care unit patients
    Yihai Zhai, Danxiu Lan, Siying Lv, Liqin Mo
    Frontiers in Medicine.2024;[Epub]     CrossRef

ACC : Acute and Critical Care