biostudies-literaturela Roi-Teeuw HMDutch Heart FoundationZonMwNetherlands Organisation for Health Research and Developmentoead101https://www.ebi.ac.uk/biostudies/studies/S-EPMC10690016biostudies-literatureUnknown3(6)<h4>Aims</h4>Previous studies suggest relatively increased cardiovascular risk after COVID-19 infection. This study assessed incidence and explored individual risk and timing of cardiovascular disease occurring post-COVID-19 in a large primary care database.<h4>Methods and results</h4>Data were extracted from the UK's Clinical Practice Research Datalink. Incidence rates within 180 days post-infection were estimated for arterial or venous events, inflammatory heart disease, and new-onset atrial fibrillation or heart failure. Next, multivariable logistic regression models were developed on 220 751 adults with COVID-19 infection before 1 December 2020 using age, sex and traditional cardiovascular risk factors. All models were externally validated in (i) 138 034 vaccinated and (ii) 503 404 unvaccinated adults with a first COVID-19 infection after 1 December 2020. Discriminative performance and calibration were evaluated with internal and external validation. Increased incidence rates were observed up to 60 days after COVID-19 infection for venous and arterial cardiovascular events and new-onset atrial fibrillation, but not for inflammatory heart disease or heart failure, with the highest rate for venous events (13 per 1000 person-years). The best prediction models had <i>c</i>-statistics of 0.90 or higher. However, <5% of adults had a predicted 180-day outcome-specific risk larger than 1%. These rare outcomes complicated calibration.<h4>Conclusion</h4>Risks of arterial and venous cardiovascular events and new-onset atrial fibrillation are increased within the first 60 days after COVID-19 infection in the general population. Models' <i>c</i>-statistics suggest high discrimination, but because of the very low absolute risks, they are insufficient to inform individual risk management.European heart journal openIncidence and individual risk prediction of post-COVID-19 cardiovascular disease in the general population: a multivariable prediction model development and validation study.PMC106900160839105211000301-001-2020-T063la Roi-Teeuw HMvan Smeden MKlungel OHvan Doorn SGeersing GJRutten FHSouverein PCfalseIncidence and individual risk prediction of post-COVID-19 cardiovascular disease in the general population: a multivariable prediction model development and validation study.<h4>Aims</h4>Previous studies suggest relatively increased cardiovascular risk after COVID-19 infection. This study assessed incidence and explored individual risk and timing of cardiovascular disease occurring post-COVID-19 in a large primary care database.<h4>Methods and results</h4>Data were extracted from the UK's Clinical Practice Research Datalink. Incidence rates within 180 days post-infection were estimated for arterial or venous events, inflammatory heart disease, and new-onset atrial fibrillation or heart failure. Next, multivariable logistic regression models were developed on 220 751 adults with COVID-19 infection before 1 December 2020 using age, sex and traditional cardiovascular risk factors. All models were externally validated in (i) 138 034 vaccinated and (ii) 503 404 unvaccinated adults with a first COVID-19 infection after 1 December 2020. Discriminative performance and calibration were evaluated with internal and external validation. Increased incidence rates were observed up to 60 days after COVID-19 infection for venous and arterial cardiovascular events and new-onset atrial fibrillation, but not for inflammatory heart disease or heart failure, with the highest rate for venous events (13 per 1000 person-years). The best prediction models had <i>c</i>-statistics of 0.90 or higher. However, <5% of adults had a predicted 180-day outcome-specific risk larger than 1%. These rare outcomes complicated calibration.<h4>Conclusion</h4>Risks of arterial and venous cardiovascular events and new-onset atrial fibrillation are increased within the first 60 days after COVID-19 infection in the general population. Models' <i>c</i>-statistics suggest high discrimination, but because of the very low absolute risks, they are insufficient to inform individual risk management.2023-01-01T00:00:00Z2023 Nov2026-04-07T15:47:18.062Z2025-02-19T01:18:53.727ZS-EPMC106900163804662210.1093/ehjopen/oead101