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Validation of clinical risk models for predicting COVID-19 severity
Emergency Medicine Journal ( IF 2.7 ) Pub Date : 2022-10-01 , DOI: 10.1136/emermed-2021-211821
Rahul Aggarwal 1 , Timothy S Anderson 1, 2 , Aditya Mohanty 1, 2 , Adlin Pinheiro 2 , Long Ngo 1, 2 , Andrew Ahn 2 , Neal Peterson 2 , Mark Dunlop 2 , Thomas Mawson 2 , Taliya Lantsman 2 , Natalia Forbath 2 , Jennifer P Stevens 1, 2 , Shoshana J Herzig 2, 3
Affiliation  

Liang and colleagues developed a risk prediction score, COVID-GRAM, to identify adults with COVID-19 at higher risk of intensive care stay, mechanical ventilation or death.1 This score had strong performance in Chinese cohorts and has been validated in multiple non-US cohorts, although with variation in its performance (C-statistic ranging from 0.64 to 0.91).1 2 It has yet to been studied in US populations.1 2 Differences in the US hospital practices and patient population may affect the applicability of COVID-GRAM to this population. Additionally, clinical rationale and prior studies suggest that CURB-65 may predict severe disease in COVID-19.3 We compare the performances of COVID-GRAM with CURB-65 for predicting critical illness in patients with COVID-19 in a US population. This retrospective study included adult patients admitted to an academic medical centre in Boston Massachusetts with a diagnosis of COVID-19 between 1 January 2020 and 29 June 2020. Individuals with prior COVID-19 hospitalisations were excluded. Patients were followed until outcome occurrence or the end of hospitalisation (whichever came first). Demographic and clinical data, patient outcomes and variables used in COVID-GRAM and CURB-65 were obtained from the electronic health record. The primary outcome was critical illness—defined as a …
更新日期:2022-09-20
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