Acute and Critical Care (Feb 2023)

Predicting factors associated with prolonged intensive care unit stay of patients with COVID-19

  • Won Ho Han,
  • Jae Hoon Lee,
  • June Young Chun,
  • Young Ju Choi,
  • Youseok Kim,
  • Mira Han,
  • Jee Hee Kim

DOI
https://doi.org/10.4266/acc.2022.01235
Journal volume & issue
Vol. 38, no. 1
pp. 41 – 48

Abstract

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Background Predicting the length of stay (LOS) for coronavirus disease 2019 (COVID-19) patients in the intensive care unit (ICU) is essential for efficient use of ICU resources. We analyzed the clinical characteristics of patients with severe COVID-19 based on their clinical care and determined the predictive factors associated with prolonged LOS. Methods We included 96 COVID-19 patients who received oxygen therapy at a high-flow nasal cannula level or above after ICU admission during March 2021 to February 2022. The demographic characteristics at the time of ICU admission and results of severity analysis (Sequential Organ Failure Assessment [SOFA], Acute Physiology and Chronic Health Evaluation [APACHE] II), blood tests, and ICU treatments were analyzed using a logistic regression model. Additionally, blood tests (C-reactive protein, D-dimer, and the PaO2 to FiO2 ratio [P/F ratio]) were performed on days 3 and 5 of ICU admission to identify factors associated with prolonged LOS. Results Univariable analyses showed statistically significant results for SOFA score at the time of ICU admission, C-reactive protein level, high-dose steroids, mechanical ventilation (MV) care, continuous renal replacement therapy, extracorporeal membrane oxygenation, and prone position. Multivariable analysis showed that MV care and P/F ratio on hospital day 5 were independent factors for prolonged ICU LOS. For D-dimer, no significant variation was observed at admission; however, after days 3 and 5 days of admission, significant between-group variation was detected. Conclusions MV care and P/F ratio on hospital day 5 are independent factors that can predict prolonged LOS for COVID-19 patients.

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