Atrial fibrillation (AF) is the most common heart rhythm disorder in clinical practice. It worsens the quality of life of patients, leads to an increase in the mortality rate because of its association with a high risk of thromboembolic complications. The current pandemic of a new coronavirus infection, which began in March 2020, was marked by an increase in cardiovascular diseases, including an increase in the number of patients with AF.
View Article and Find Full Text PDFThe individual results of SARS-CoV-2 serological tests measured after the first pandemic wave of 2020 cannot be directly interpreted as a probability of having been infected. Plus, these results are usually returned as a binary or ternary variable, relying on predefined cut-offs. We propose a Bayesian mixture model to estimate individual infection probabilities, based on 81,797 continuous anti-spike IgG tests from Euroimmun collected in France after the first wave.
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