Background - COVID-19 has led to over 1 million deaths worldwide and has been associated with cardiac complications including cardiac arrhythmias. The incidence and pathophysiology of these manifestations remain elusive. In this worldwide survey of patients hospitalized with COVID-19 who developed cardiac arrhythmias, we describe clinical characteristics associated with various arrhythmias, as well as global differences in modulations of routine electrophysiology practice during the pandemic. Methods - We conducted a retrospective analysis of patients hospitalized with COVID-19 infection worldwide with and without incident cardiac arrhythmias. Patients with documented atrial fibrillation (AF), atrial flutter (AFL), supraventricular tachycardia (SVT), non-sustained or sustained ventricular tachycardia (VT), ventricular fibrillation (VF), atrioventricular block (AVB), or marked sinus bradycardia (HR<40bpm) were classified as having arrhythmia. De-identified data was provided by each institution and analyzed. Results - Data was collected for 4,526 patients across 4 continents and 12 countries, 827 of whom had an arrhythmia. Cardiac comorbidities were common in patients with arrhythmia: 69% had hypertension, 42% diabetes mellitus, 30% had heart failure and 24% coronary artery disease. Most had no prior history of arrhythmia. Of those who did develop an arrhythmia, the majority (81.8%) developed atrial arrhythmias, 20.7% developed ventricular arrhythmias, and 22.6% had bradyarrhythmia. Regional differences suggested a lower incidence of AF in Asia compared to other continents (34% vs. 63%). Most patients in in North America and Europe received hydroxychloroquine, though the frequency of hydroxychloroquine therapy was constant across arrhythmia types. Forty-three percent of patients who developed arrhythmia were mechanically ventilated and 51% survived to hospital discharge. Many institutions reported drastic decreases in electrophysiology procedures performed. Conclusions - Cardiac arrhythmias are common and associated with high morbidity and mortality among patients hospitalized with COVID-19 infection. There were significant regional variations in the types of arrhythmias and treatment approaches.

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A B S T R A C T PurposeNonadherence to adjuvant hormonal therapy is common and is associated with increased prescription copayment amount and black race. Studies suggest that household wealth may partly explain racial disparities. We investigated the impact of net worth on disparities in adherence and discontinuation. Patients and MethodsWe used the OptumInsight insurance claims database to identify women older than age 50 years diagnosed with early breast cancer, from January 1, 2007, to December 31, 2011, who were using hormonal therapy. Nonadherence was defined as a medication possession ratio of Յ 80% of eligible days over a 2-year period. We evaluated the association of demographic and clinical characteristics, annual household income, household net worth (Ͻ $250,000, $250,000 to $750,000, or Ͼ $750,000), insurance type, and copayments (Ͻ $10, $10 to $20, or Ͼ $20) with adherence to hormonal therapy. Logistic regression analyses were conducted by sequentially adding sociodemographic and financial variables to race. ResultsWe identified 10,302 patients; 2,473 (24%) were nonadherent. In the unadjusted analyses, adherence was negatively associated with black race (odds ratio [OR], 0.76; P Ͻ .001), advanced age, comorbidity, and Medicare insurance. Adherence was positively associated with medium (OR, 1.33; P Ͻ .001) and high (OR, 1.66; P Ͻ .001) compared with low net worth. The negative association of black race with adherence (OR, 0.76) was reduced by adding net worth to the model (OR, 0.84; P Ͻ .05). Correcting for other variables had a minimal impact on the association between race and adherence (OR, 0.87; P ϭ .08). The interaction between net worth and race was significant (P Ͻ .01). ConclusionWe found that net worth partially explains racial disparities in hormonal therapy adherence. These results suggest that economic factors may contribute to disparities in the quality of care.