Lip GYH, Genaidy A, Tran G, et al. - This study was carried out to assess incident atrial fibrillation (AF) risks in a large prospective population of elderly patients with/without incident COVID-19 cases and baseline cardiovascular/non-cardiovascular multi-morbidities. Researchers applied two procedures: main effect modeling and secondly, a machine-learning (ML) approach, accounting for the complex dynamic relationships among comorbidity variables. A prospective elderly US cohort of 280,592 patients from medical databases in an 8-month investigation of with/without newly incident COVID19 cases was studied. In a cohort with diverse cardiovascular/non-cardiovascular multi-morbidities, COVID-19 status has major implications for incident AF. The findings showed that the ML approach accounting for dynamic multimorbidity changes had good prediction for new-onset AF amongst incident COVID19 cases.