Machine learning models for the prediction of COVID-19 prognosis in the primary health care setting
In addition to age and epidemic wave, predictors such as social deprivation, diabetes mellitus, obesity, COPD, cardiovascular disease, high blood pressure, and dyslipidemia significantly indicate poor prognosis in COVID-19 patients diagnosed in PHC, and the developed application facilitates risk quantification for individual patients.
Authors
- Joan Barrot (ORCID: https://orcid.org/0000-0002-7482-7647)
- Dı́dac Mauricio (ORCID: https://orcid.org/0000-0002-2868-0250)
- Josep Franch‐Nadal (ORCID: https://orcid.org/0000-0002-5175-1555)
- Jordi Real (ORCID: https://orcid.org/0000-0002-5979-8948)
- Bogdan Vlacho (ORCID: https://orcid.org/0000-0003-3768-8112)
- Manel Mata‐Cases (ORCID: https://orcid.org/0000-0003-3693-3622)
- Joan A. Caylà (ORCID: https://orcid.org/0000-0003-3891-111X)
Institutions
- Universitat de Vic - Universitat Central de Catalunya (ES)
- Generalitat de Catalunya (ES)
- Instituto de Salud Carlos III (ES)
- Hospital de Sant Pau (ES)
- Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (ES)
- Consorci d’Atenció Primària de Salut Barcelona Esquerra (ES)
- Institut Universitari d'Investigació en Atenció Primària Jordi Gol (ES)
- Institut Català de la Salut (ES)
- Universitat de Barcelona (ES)
Publication Details
- Journal
- BMC Primary Care
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1186/s12875-025-02960-5
- Citations
- 1
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Instituto de Salud Carlos III