Key result
Proposed diagnostic algorithm for exercise-induced ventricular arrhythmias identifies underlying disease in ~83% of patients.
Why the study?
The study was conducted to examine the clinical and electrocardiographic characteristics of exercise-induced arrhythmias and develop an algorithm for managing patients with exercise-induced ventricular arrhythmias.
Does a proposed diagnostic algorithm help identify the underlying causes of exercise-induced ventricular arrhythmias?
Observational (n=80)
Does a proposed diagnostic algorithm help identify the underlying causes of exercise-induced ventricular arrhythmias?
A systematic diagnostic algorithm can effectively identify underlying structural or ischemic heart disease in the majority of patients presenting with exercise-induced ventricular arrhythmias.
Supports systematic evaluation of exercise-induced ventricular arrhythmias; hypothesis-generating and requires prospective validation before practice change.
Aim. To study the clinical and electrocardiographic characteristics of exerciseinduced arrhythmias and develop an algorithm for managing patients with exerciseinduced ventricular arrhythmias (VA). Material and methods . For the period from 2015 to 2019 203 patients with VA during periods of wakefulness were selected from the database of patients who performed Holter monitoring; 167 of them were selected, who underwent a treadmill test (TT) according to the standard Bruce protocol. During TT, the qualitative and quantitative characteristics of VA were assessed. Further examination and treatment were carried out according to the proposed algorithm. Results. In 80 patients (48% of all those who underwent TT), regardless of VA presence in the pretest, arrhythmias had an exercise nature and appeared and/or progressed during exercise. These patients were included in the present study to assess the causal relationship of VA with any disease. Following the algorithm, coronary artery disease was verified in 15 people, stage I-II hypertension — in 25, and minor heart defects — in 21. Of the remaining 19 patients without association of exercise-induced VA with any disease during the initial examination, 5 patients were diagnosed with arrhythmogenic cardiomyopathy/right ventricular dysplasia during prospective follow-up. In the remaining 14, VAs were considered idiopathic. Conclusion. The presented algorithm can accelerate both the search for the causes of exercise-induced VA and the choice of personalized treatment.
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Жабина et al. (2022) conducted an observational in exercise-induced ventricular arrhythmias (n=80). Diagnostic algorithm was evaluated on Identification of underlying disease. A proposed diagnostic algorithm for exercise-induced ventricular arrhythmias identified an underlying cardiac or systemic disease in 66 of 80 patients, leaving 14 cases as idiopathic.
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