Risk Stratification Models for Stroke in Patients Hospitalized with COVID-19 Infection

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

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 and results

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 c-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.

Conclusion

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.

Ischemic strokes in COVID-19: risk factors, obesity paradox, and distinction between trigger and causal association

Background and purpose

Stroke has been described as a COVID-19 complication. However, its occurrence rate, risk factors, and causal relationships are still not well established.

Methods

We describe the characteristics of confirmed COVID-19-related strokes among all cases of COVID-19 hospitalized in our health network, from November 1, 2020 to April 30, 2021. Risk factor analysis has been conducted for ischemic stroke (IS), which represents 92% of all confirmed cases of Covid-19-related strokes, and a "causal attribution to infection" classification is provided.

Results

In all, 62/4105 hospitalized COVID-19 patients had an acute stroke (1.51%). Severe COVID-19 (OR 2.27-CI 1.06-4.77; p = 0.032), atrial fibrillation (OR 3.65-CI 1.63-7.98; p = 0.001), and ischemic heart disease (OR 4.590-CI 1.714-12.137; p = 0.002) proved to be independent risk factors for IS, while obesity was a protective factor (OR 0.90-CI 0.82-0.97; p = 0.012). COVID-19 had a causal role in 32.1% of IS cases, was a relevant cofactor in 28.6% of cases of IS, and was a possible trigger in 39.3% of events.

Conclusion

Our stroke occurrence rate is consistent with other population-based reports (range 0.34-2.7%). Prespecified peculiar clinical and radiological features allow the distinction between "IS caused by COVID-19" and "IS triggered by COVID-19." Clinical history of vascular diseases and risk factors is crucial in determining the risk of IS in patients with COVID-19. However, the protective effect of a BMI > 30 kg/m2 seems to suggest an obesity paradox.