Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan.
Coronavirus disease 2019
Critical illness
Japanese
Predictive model
Journal
Respiratory investigation
ISSN: 2212-5353
Titre abrégé: Respir Investig
Pays: Netherlands
ID NLM: 101581124
Informations de publication
Date de publication:
Nov 2021
Nov 2021
Historique:
received:
15
05
2021
revised:
25
07
2021
accepted:
09
08
2021
pubmed:
21
9
2021
medline:
18
11
2021
entrez:
20
9
2021
Statut:
ppublish
Résumé
This study aimed to examine risk factors associated with critical coronavirus disease 19 (COVID-19) and to establish a risk predictive model for Japanese patients. We retrospectively assessed adult Japanese patients diagnosed with COVID-19 at the Japanese Red Cross Medical Center, Tokyo, Japan between February 1, 2020 and March 10, 2021. The patients were divided into critical and non-critical groups based on their condition during the clinical courses. Univariate and multivariate logistic regression analyses were performed to investigate the relationship between clinical characteristics and critical illness. Based on the results, we established a predictive model for the development of critical COVID-19. In total, 300 patients were enrolled in this study. Among them, 86 were included in the critical group. Analyses revealed that age ≥65 y, hemodialysis, need for O Upon diagnosis, the predictive model can be used to identify adult Japanese patients with COVID-19 who will require intensive treatment.
Sections du résumé
BACKGROUND
BACKGROUND
This study aimed to examine risk factors associated with critical coronavirus disease 19 (COVID-19) and to establish a risk predictive model for Japanese patients.
METHODS
METHODS
We retrospectively assessed adult Japanese patients diagnosed with COVID-19 at the Japanese Red Cross Medical Center, Tokyo, Japan between February 1, 2020 and March 10, 2021. The patients were divided into critical and non-critical groups based on their condition during the clinical courses. Univariate and multivariate logistic regression analyses were performed to investigate the relationship between clinical characteristics and critical illness. Based on the results, we established a predictive model for the development of critical COVID-19.
RESULTS
RESULTS
In total, 300 patients were enrolled in this study. Among them, 86 were included in the critical group. Analyses revealed that age ≥65 y, hemodialysis, need for O
CONCLUSIONS
CONCLUSIONS
Upon diagnosis, the predictive model can be used to identify adult Japanese patients with COVID-19 who will require intensive treatment.
Identifiants
pubmed: 34538593
pii: S2212-5345(21)00146-5
doi: 10.1016/j.resinv.2021.08.001
pmc: PMC8433043
pii:
doi:
Substances chimiques
C-Reactive Protein
9007-41-4
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
804-809Informations de copyright
Copyright © 2021 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Conflict of Interest The authors declare no conflicts of interest.