Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Smart Study, a clinical future for accessible smart technology
0
Zitationen
4
Autoren
2025
Jahr
Abstract
Abstract Background Cardiac rhythm disorders account for a large portion of cardiovascular diseases, straining healthcare systems globally (1). Single-lead electrocardiograms incorporated into watches, phones and other ‘smart’ devices are increasingly being used by consumers to access healthcare (2). Purpose We hypothesized that single lead electrocardiograms generated by smart devices may be useful in diagnostic pathways for the management of heart rhythm disorders. In addition, we sought to assess the impact of smart device data on the referral journey to the arrhythmia clinic. Methods From November 2023 to May 2024 adult (≥18 years) patients referred to the arrhythmia clinic of a district general hospital in the United Kingdom, were recruited into the study if their symptoms and/or clinical concerns were generated or captured by a single-lead ECG from a smart device. All study participants underwent clinical review, baseline ECG and subsequently traditional Holter monitoring and correlation with smart device data was assessed by a cardiac electrophysiologist. Results A total of 24 patients (54% female; median age 49, IQR 19-80) with a mean follow up of 10 months were included in the study. Smart device data were generated from Garmin’s (4%), Apple Watches (46%), Fitbits (13%) and AliveCor KardiaMobile. The majority (75%) of patients sought medical attention due to smart device alerts, often in the absence of symptoms. Atrial fibrillation (30%), narrow complex tachycardia (42%) and normal sinus rhythm/bradycardia (12%) were detected. We observed a 100% positive correlation between traditional ECG monitoring in patients who had simultaneous recordings from smart devices. Conclusion These findings suggest that the current generation of smart devices are highly accurate and can serve as valuable adjuncts in the investigation and management of patients with suspected heart rhythm disorders. However, these devices generate alerts even in the absence of symptoms. Diagnostic pathways to accommodate an increasing number of referrals from concerned consumers will need to be designed.Participant demographics and results Recruitment process
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.239 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.095 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.463 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.428 Zit.