A Prospective Real-World Study Evaluating the Feasibility and Diagnostic Yield of Patient-Recorded Smartwatch EKGs...

Introduction: Palpitations are one of the most common cardiovascular complaints, affecting approximately 6% to 11% of the general population. Since palpitations often occur sporadically and resolve before medical evaluation, diagnosing the underlying rhythm disturbance requires documentation via an electrocardiogram (ECG) recorded during the symptomatic episode. The standard tool for this purpose has long been the 24-h Holter monitor, which has significant limitations, with diagnostic yields as low as 10% to 15%. Objective: This study aims to evaluate the feasibility and diagnostic yield of single-lead ECG recordings from smartwatches in patients presenting with palpitations. Methods: From 1 May 2023 to 1 May 2025, we conducted a prospective, real-world cohort study among consecutive adults referred to the University Hospital of Ferrara-based arrhythmia outpatient clinics for evaluation of palpitations. Eligibility required patients to be ≥21 years of age, report palpitations for which ambulatory documentation was clinically indicated, and already own a compatible smartwatch capable of single-lead ECG. Participants were trained to record a 30-s single-lead ECG at the onset of symptoms. Tracings were transmitted securely and independently reviewed by two blinded electrophysiologists. Results: Fifty-nine patients were enrolled (mean age 52 years, 64% male). Thirty-one patients (52%) transmitted at least one smartwatch-derived electrocardiographic tracing. Seventy-seven smartwatch tracings were received. Of these, 73 (95%) were interpretable; 57 (78%) showed an arrhythmia, whereas 16 (22%) demonstrated normal sinus rhythm. Four recordings (5%) were non-interpretable. From the 57 arrhythmic tracings, 44 distinct arrhythmic diagnoses were identified. Paroxysmal atrial fibrillation (AF) accounted for 16 episodes. Other diagnosed arrhythmias included atrial flutter (n = 6), paroxysmal supraventricular tachycardia (PSVT) (n = 4), premature atrial complexes (PAC) (n = 6), premature ventricular complexes (PVC) (n = 9), inappropriate sinus tachycardia (n = 12), and second-degree atrioventricular (AV) block type I (n = 4). Conclusions: Smartwatch-based ECG monitoring in symptomatic patients is feasible and provides a high diagnostic yield for a broad spectrum of arrhythmias. Unlike large-scale population screening approaches, which generate vast datasets with limited clinical benefit, a symptom-driven strategy applied to carefully selected, educated, and motivated patients proves both clinically valuable and organizationally sustainable. Indeed, the mean number of tracings transmitted per patient was low (1.3), confirming the clinical and operational sustainability of this patient-triggered, real-world approach.