The Journal of emergency medicine · 2025
Smartwatch-Based Detection of Ventricular Dysrhythmias: A Systematic Review of Literature.
СтатьяСистематический обзорНазвание и аннотация: Перевод в очереди
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Avidan Yuval, Khoury Razi, Naoum Ibrahim, Danon Asaf, Aker Amir
Аннотация
BACKGROUND: The rise of smartwatches introduces a novel technology for detecting dysrhythmias. However, the diagnosis of ventricular dysrhythmias (VDs) usually requires automatic recording modes. There is a scarcity of literature on smartwatch-based VDs detection.
OBJECTIVES: We conducted a literature review to synthesize current evidence on the clinical profiles of smartwatch-detected VDs and to highlight their detectability in real-world settings.
METHODS: PubMed, Embase, Scopus, and the Cochrane Library were searched from inception to May 2025 for studies reporting smartwatch-based detection of VDs, with availability of participant-level data. Two investigators independently extracted study data and quality.
RESULTS: A total of 20 patients from 18 articles were included, with a mean age of 48 years; 35% were over 60 years of age, and 35% had a documented history of structural heart disease. Primary complaints were palpitations (70%) and syncope (20%). Sustained monomorphic ventricular tachycardia was the most common dysrhythmia (60%), followed by polymorphic ventricular tachycardia (25%). Vasospastic angina and idiopathic ventricular tachycardia were the leading diagnoses. Interventions included coronary angiography (25%), electrophysiology studies (35%), catheter ablation (35%), and implantable cardioverter defibrillators (45%). The rest received medical therapy.
CONCLUSIONS: Smartwatches may provide valuable outpatient data that support timely diagnosis and appropriate therapy across diverse clinical scenarios. As exemplified in this review, the detectability of VDs through smartwatches in real-world settings is feasible. Emergency department interrogation of smartwatch data may provide valuable information.
OBJECTIVES: We conducted a literature review to synthesize current evidence on the clinical profiles of smartwatch-detected VDs and to highlight their detectability in real-world settings.
METHODS: PubMed, Embase, Scopus, and the Cochrane Library were searched from inception to May 2025 for studies reporting smartwatch-based detection of VDs, with availability of participant-level data. Two investigators independently extracted study data and quality.
RESULTS: A total of 20 patients from 18 articles were included, with a mean age of 48 years; 35% were over 60 years of age, and 35% had a documented history of structural heart disease. Primary complaints were palpitations (70%) and syncope (20%). Sustained monomorphic ventricular tachycardia was the most common dysrhythmia (60%), followed by polymorphic ventricular tachycardia (25%). Vasospastic angina and idiopathic ventricular tachycardia were the leading diagnoses. Interventions included coronary angiography (25%), electrophysiology studies (35%), catheter ablation (35%), and implantable cardioverter defibrillators (45%). The rest received medical therapy.
CONCLUSIONS: Smartwatches may provide valuable outpatient data that support timely diagnosis and appropriate therapy across diverse clinical scenarios. As exemplified in this review, the detectability of VDs through smartwatches in real-world settings is feasible. Emergency department interrogation of smartwatch data may provide valuable information.