Open AccessEstablishment of a Clinical Nomogram Model to Predict the Progression of COVID-19 to Severe Disease
Author(s) -
Changli Tu,
Guojie Wang,
Yayuan Geng,
Na Guo,
Ning Cui,
Jing Liu
Publication year - 2021
Publication title -
therapeutics and clinical risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 55
eISSN - 1178-203X
pISSN - 1176-6336
DOI - 10.2147/tcrm.s308961
Subject(s) - medicine , nomogram , logistic regression , covid-19 , disease , pandemic , retrospective cohort study , pediatrics , emergency medicine , infectious disease (medical specialty)
Coronavirus disease 2019 (COVID-19) is a worldwide public health pandemic with a high mortality rate, among severe cases. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. It is important to ensure early detection of the virus to curb disease progression to severe COVID-19. This study aims to establish a clinical-nomogram model to predict the progression to severe COVID-19 in a timely and efficient manner.