Risk factors associated with intensive care unit (ICU) admission and in-hospital death among adults hospitalized with COVID-19: a two-center retrospective observational study in tertiary care hospitals.


Journal

Emergency radiology
ISSN: 1438-1435
Titre abrégé: Emerg Radiol
Pays: United States
ID NLM: 9431227

Informations de publication

Date de publication:
Aug 2021
Historique:
received: 20 11 2020
accepted: 19 01 2021
pubmed: 4 2 2021
medline: 23 7 2021
entrez: 3 2 2021
Statut: ppublish

Résumé

The COVID-19 pandemic is straining the health care systems worldwide. Therefore, health systems should make strategic shifts to ensure that limited resources provide the highest benefit for COVID-19 patients. This study aimed to describe the risk factors associated with poor in-hospital outcomes to help clinicians make better patient care decisions. This retrospective observational study enrolled 176 laboratory-confirmed COVID-19 patients. Demographic characteristics, clinical data, lymphocyte count, CT imaging findings on admission, and clinical outcomes were collected and compared. Two radiologists evaluated the distribution and CT features of the lesions and also scored the extent of lung involvement. The receiver operating characteristic (ROC) curve was used to determine the optimum cutoff point for possible effective variables on patients' outcomes. Multivariable logistic regression models were used to determine the risk factors associated with ICU admission and in-hospital death. Thirty-eight (21.5%) patients were either died or admitted to ICU from a total of 176 enrolled ones. The mean age of the patients was 57.5 ± 16.1 years (males: 61%). The best cutoff point for predicting poor outcomes based on age, CT score, and O The findings indicate that older age, higher CT score, and lower O

Sections du résumé

BACKGROUND BACKGROUND
The COVID-19 pandemic is straining the health care systems worldwide. Therefore, health systems should make strategic shifts to ensure that limited resources provide the highest benefit for COVID-19 patients.
OBJECTIVE OBJECTIVE
This study aimed to describe the risk factors associated with poor in-hospital outcomes to help clinicians make better patient care decisions.
MATERIAL AND METHODS METHODS
This retrospective observational study enrolled 176 laboratory-confirmed COVID-19 patients. Demographic characteristics, clinical data, lymphocyte count, CT imaging findings on admission, and clinical outcomes were collected and compared. Two radiologists evaluated the distribution and CT features of the lesions and also scored the extent of lung involvement. The receiver operating characteristic (ROC) curve was used to determine the optimum cutoff point for possible effective variables on patients' outcomes. Multivariable logistic regression models were used to determine the risk factors associated with ICU admission and in-hospital death.
RESULT RESULTS
Thirty-eight (21.5%) patients were either died or admitted to ICU from a total of 176 enrolled ones. The mean age of the patients was 57.5 ± 16.1 years (males: 61%). The best cutoff point for predicting poor outcomes based on age, CT score, and O
CONCLUSION CONCLUSIONS
The findings indicate that older age, higher CT score, and lower O

Identifiants

pubmed: 33534017
doi: 10.1007/s10140-021-01903-8
pii: 10.1007/s10140-021-01903-8
pmc: PMC7856446
doi:

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

691-697

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© 2021. American Society of Emergency Radiology.

Références

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Auteurs

Azin Shayganfar (A)

Department of Radiology, School of Medicine, Isfahan University of Medical Sciences, Hezarjerib Avenue, Isfahan, Iran.

Ramin Sami (R)

Department of Internal medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Somayeh Sadeghi (S)

Department of Internal medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Mehrnegar Dehghan (M)

Isfahan University of Medical sciences, Isfahan, Iran.

Nilufar Khademi (N)

Isfahan University of Medical sciences, Isfahan, Iran.

Reyhaneh Rikhtehgaran (R)

Department of Mathematical Sciences, Isfahan University of Technology, Isfahan, Iran.

Reza Basiratnia (R)

Department of Radiology, School of Medicine, Isfahan University of Medical Sciences, Hezarjerib Avenue, Isfahan, Iran.

Felora Ferdosi (F)

Department of Radiology, School of Medicine, Isfahan University of Medical Sciences, Hezarjerib Avenue, Isfahan, Iran.

Somayeh Hajiahmadi (S)

Department of Radiology, School of Medicine, Isfahan University of Medical Sciences, Hezarjerib Avenue, Isfahan, Iran. sohajiahmadi@gmail.com.

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Classifications MeSH