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Development and validation of a population-based risk stratification model for severe COVID-19 in the general population

Authors :
Emili Vela
Gerard Carot-Sans
Montse Clèries
David Monterde
Xènia Acebes
Adrià Comella
Luís García Eroles
Marc Coca
Damià Valero-Bover
Pol Pérez Sust
Jordi Piera-Jiménez
Source :
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Abstract The shortage of recently approved vaccines against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted the need for evidence-based tools to prioritize healthcare resources for people at higher risk of severe coronavirus disease (COVID-19). Although age has been identified as the most important risk factor (particularly for mortality), the contribution of underlying comorbidities is often assessed using a pre-defined list of chronic conditions. Furthermore, the count of individual risk factors has limited applicability to population-based “stratify-and-shield” strategies. We aimed to develop and validate a COVID-19 risk stratification system that allows allocating individuals of the general population into four mutually-exclusive risk categories based on multivariate models for severe COVID-19, a composite of hospital admission, transfer to intensive care unit (ICU), and mortality among the general population. The model was developed using clinical, hospital, and epidemiological data from all individuals among the entire population of Catalonia (North-East Spain; 7.5 million people) who experienced a COVID-19 event (i.e., hospitalization, ICU admission, or death due to COVID-19) between March 1 and September 15, 2020, and validated using an independent dataset of 218,329 individuals with COVID-19 confirmed by reverse transcription—polymerase chain reaction (RT-PCR), who were infected after developing the model. No exclusion criteria were defined. The final model included age, sex, a summary measure of the comorbidity burden, the socioeconomic status, and the presence of specific diagnoses potentially associated with severe COVID-19. The validation showed high discrimination capacity, with an area under the curve of the receiving operating characteristics of 0.85 (95% CI 0.85–0.85) for hospital admissions, 0.86 (0.86–0.97) for ICU transfers, and 0.96 (0.96–0.96) for deaths. Our results provide clinicians and policymakers with an evidence-based tool for prioritizing COVID-19 healthcare resources in other population groups aside from those with higher exposure to SARS-CoV-2 and frontline workers.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.1253eb5806f9420e921ff18973cfefd5
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-022-07138-y