Incidence and individual risk prediction of post-COVID-19 cardiovascular disease in the general population: a multivariable prediction model development and validation study

Abstract

Background and Aims 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. Methods Data were extracted from the United Kingdom’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 December 1st 2020 using age, sex and traditional cardiovascular risk factors. All models were externally validated in (1) 138,034 vaccinated and (2) 503,404 unvaccinated adults with a first Covid-19 infection after December 1st 2020. Discriminative performance and calibration were evaluated with internal and external validation. Results 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 c-statistics of 0.90 or higher. However, less than 5% of adults had a predicted 180-day outcome-specific risk larger than 1%. These rare outcomes complicated calibration. Conclusions 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’ c-statistics suggest high discrimination, but because of the very low absolute risks they are insufficient to inform individual risk management.