Early triage of critically ill COVID-19 patients using deep learning.
Nat Commun
; 11(1): 3543, 2020 07 15.
Artículo
en Inglés
| MEDLINE | ID: covidwho-974925
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:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
Neumonía Viral
/
Triaje
/
Infecciones por Coronavirus
/
Aprendizaje Profundo
Tipo de estudio:
Estudio de cohorte
/
Estudios diagnósticos
/
Estudio observacional
/
Estudio pronóstico
Límite:
Humanos
/
Middle aged
Idioma:
Inglés
Revista:
Nat Commun
Asunto de la revista:
Biologia
/
Ciencia
Año:
2020
Tipo del documento:
Artículo
País de afiliación:
S41467-020-17280-8
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