Key result
Ambulatory ECGs detect paroxysmal atrial arrhythmias in ~39% of patients, linked to multiple clinical predictors.
Why the study?
Arrhythmias can appear suddenly without symptoms and risk causing other diseases or death, motivating this study to determine predicting factors for paroxysmal arrhythmias.
What factors are associated with the incidence of paroxysmal arrhythmias in ambulatory ECG monitored patients?
Cohort (n=406)
No
What factors are associated with the incidence of paroxysmal arrhythmias in ambulatory ECG monitored patients?
Sociodemographic and clinical factors, including age, gender, smoking, and comorbidities, are significantly associated with the occurrence of specific types of paroxysmal arrhythmias.
Background/Aim: Arrhythmia is a heart rhythm disorder that can appear suddenly without any symptoms and has the risk of causing other diseases and even death. This study aimed to determine predicting factors for the incidence of paroxysmal arrhythmias. Methods: This retrospective observational cohort study used patients' medical records in the Cardiovascular Outpatient Service Unit at RSUD Budhi Asih, Jakarta, Indonesia, from 2017-2021. Based on inclusion and exclusion criteria, 406 patients were analysed. The occurrence of paroxysmal arrhythmias based on the doctor's diagnosis in medical record data was divided into paroxysmal atrial, supraventricular, ventricular and atrioventricular block (AV block) arrhythmias. Data analysis used the Chi-square test. Results: A total of 39.4 % of patients had paroxysmal atrial arrhythmias. Factors associated with the occurrence of paroxysmal atrial arrhythmias were age, gender, smoking behaviour, comorbidities and heart-pumping ability. On the other hand, body mass index, hypertension and diabetes mellitus were shown to be significantly associated with paroxysmal supraventricular arrhythmias. Gender, smoking behaviour, diabetes mellitus, coronary heart disease, thyroid disease and heart pumping ability were predicting factors for paroxysmal ventricular arrhythmias. Meanwhile, only gender and heart disease were factors associated with paroxysmal AV block arrhythmias. Conclusion: Sociodemographic and individual clinical conditions were associated with paroxysmal arrhythmias. However, these factors vary according to the outbreak of the arrhythmia.
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Dwiyanto et al. (2025) conducted a cohort in Paroxysmal arrhythmias (n=406). Sociodemographic and clinical risk factors was evaluated on Incidence of paroxysmal atrial arrhythmias. In patients undergoing ambulatory ECG monitoring, paroxysmal atrial arrhythmias were the most common finding (39.4%), with age, gender, smoking, comorbidities, and heart-pumping ability identified as significant predictors.
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