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

Abstract

Abstract Background Previous studies showed that relative risks of various cardiovascular events are increased after Covid-19, even in non-hospitalized individuals. The global burden of post-Covid-19 cardiovascular disease is large and not (yet) hospitalized Covid-19 infected adults may represent a potential target for prevention strategies to mitigate this burden. However, good estimates of individual absolute risks in the general population and risk stratification models are lacking, yet pivotal to assess its impact and direct health care policy. Purpose This study aimed to assess the absolute risk of post-Covid-19 cardiovascular events in the general population, and subsequently explore individual risk prediction in this domain. Methods Covid-19 diagnosed adults were identified from the United Kingdom’s Clinical Practice Research Datalink Aurum, a primary care electronic healthcare database. We assessed 180-day incidence rates of atherosclerotic events (acute coronary syndrome, stroke and transient ischaemic accident), venous thrombo-embolic events (pulmonary embolism and deep venous thrombosis), and newly diagnosed atrial fibrillation and heart failure. Multivariable logistic regression models using elastic net penalization were developed on a cohort of 220,751 adults with Covid-19 before 1 December 2020 (before the start of national vaccination campaigns). Candidate predictors included age, sex, body mass index, smoking, medical history and medication. Three models were fit for each endpoint, with increasing numbers of predictors. All models were validated in (1) 138,034 vaccinated and (2) 503,404 non-vaccinated adults with a first Covid-19 diagnosis after 1 December 2020. We evaluated discriminative and calibration performance upon internal cross-validation and in both validation cohorts. Results Post-Covid-19 cardiovascular event incidences ranged from 13 (venous thromboembolic events) down to 4 (heart failure de novo) per 1000 person-years. Incidences were relatively increased up to 50 days after Covid-19 infection. However, on an absolute scale, individual risks were very low: only less than one in twenty adults with Covid-19 had a predicted 180-day risk larger than 1% and these mainly included individuals aged 60 years or older. Even though the best models had high discriminative performance (AUC > 0.90), rare outcomes complicated predictive performance and calibration. Conclusions Risks of atherosclerotic events, venous thromboembolic events, and newly diagnosed atrial fibrillation and heart failure are increased after Covid-19 infection in the general population, notably within the first 50 days after infection and in individuals aged 60 years or older. However, individual risks are too low to be predictive or helpful to guide individual risk management. Risk mitigation strategies should therefore be aimed at population-based prevention (such as increasing vaccination uptake) and at individual management of Covid-19 hospitalized patients.Graphical abstractPredicted 180-day risk after Covid-19