Predicting factors associated with prolonged intensive care unit stay of patients with COVID-19.
Acute Crit Care
; 38(1): 41-48, 2023 Feb.
Article
en En
| MEDLINE
| ID: mdl-36935533
ABSTRACT
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.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Acute Crit Care
Año:
2023
Tipo del documento:
Article