Early triage of critically ill COVID-19 patients using deep learning.
Nat Commun
; 11(1): 3543, 2020 07 15.
Article
em En
| MEDLINE
| ID: mdl-32669540
ABSTRACT
The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern. It is imperative to identify these patients early. We show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission. We develop this model using a cohort of 1590 patients from 575 medical centers, with internal validation performance of concordance index 0.894 We further validate the model on three separate cohorts from Wuhan, Hubei and Guangdong provinces consisting of 1393 patients with concordance indexes of 0.890, 0.852 and 0.967 respectively. This model is used to create an online calculation tool designed for patient triage at admission to identify patients at risk of severe illness, ensuring that patients at greatest risk of severe illness receive appropriate care as early as possible and allow for effective allocation of health resources.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Pneumonia Viral
/
Triagem
/
Infecções por Coronavirus
/
Aprendizado Profundo
Tipo de estudo:
Clinical_trials
/
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
/
Middle aged
Idioma:
En
Revista:
Nat Commun
Ano de publicação:
2020
Tipo de documento:
Article