Validation of clinical risk models for predicting COVID-19 severity,Emergency Medicine Journal

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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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