Why the study?
Despite the central role of ECG, limitations in capturing intermittent events and interpretation variability create diagnostic gaps, especially for infrequent or asymptomatic arrhythmias.
Key points are not available for this paper at this time.
Design
Narrative review
May support extended monitoring for sporadic arrhythmia detection in practice; leaves open prospective outcome trials and AI integration.
Cardiac arrhythmias represent a broad spectrum of electrical disturbances and are associated with significant morbidity and mortality, necessitating accurate and timely diagnosis for effective management. Despite the central role of electrocardiography (ECG), limitations in capturing intermittent events and variability in interpretation create diagnostic gaps, particularly in patients with infrequent or asymptomatic presentations. This narrative review aims to synthesize current diagnostic approaches by integrating conventional ECG with advanced monitoring modalities, including ambulatory systems, implantable cardiac monitors, device-derived diagnostic data from pacemakers and implantable cardioverter-defibrillators, electrophysiological studies, imaging, and digital health technologies. Key findings indicate that while standard ECG remains indispensable for initial assessment, extended external monitoring and implantable cardiac monitors significantly improve detection rates, especially in sporadic arrhythmias. Additionally, diagnostic data from pacemakers and implantable cardioverter-defibrillators provide additional rhythm surveillance in patients with therapeutic cardiovascular implantable electronic devices. Multimodal integration, incorporating imaging and artificial intelligence-driven analytics, enhances diagnostic precision and supports personalized risk stratification. These developments have important clinical implications by enabling earlier detection, improving patient-specific management, and facilitating remote monitoring strategies. The findings highlight the need for structured, patient-centered diagnostic pathways that align modality selection with symptom frequency and clinical risk profiles. Continued technological innovation and data integration are expected to refine diagnostic accuracy and efficiency. Effective arrhythmia diagnosis relies on combining traditional and advanced tools within an integrated framework to optimize clinical outcomes.
No takes yet. Share an insight, caveat, or question.
Thengilan et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: