ArticleEuropean heart journal. Digital health2023
Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial: detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor.
Article in European heart journal. Digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04563572 (Determine AF Burden With PPG Trial - Detection and Quantification of Episodes of Atrial Fibrillation Using a Cloud Analytics Service Connected to a Wearable With Photoplethysmographic), which is not on this map. Cited by 14 papers.
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Determine AF Burden With PPG Trial - Detection and Quantification of Episodes of Atrial Fibrillation Using a Cloud Analytics Service Connected to a Wearable With Photoplethysmographic (PPG) Sensor
Who cites it
14 citing papers in PubMed, 18 citations in OpenAlex.
- Beyond burden metrics: Wearable photoplethysmography-derived spatiotemporal progression of atrial fibrillation linked to clinical outcomes.Heart rhythm O2 · 2026Article
- Photoplethysmography-Based Machine Learning Approaches for Atrial Fibrillation Burden: Algorithm Development and Validation.JMIR cardio · 2025Article
- Association of ventricular tachycardia burden with 30-day in-hospital mortality in an intensive care unit cohort.Heart rhythm O2 · 2025Article
- Short-term atrial fibrillation onset prediction using machine learning.European heart journal. Digital health · 2025Article
- Association of Atrial Fibrillation Burden With Cardiovascular Outcomes in New-Onset Atrial Fibrillation Complicating Myocardial Infarction.Journal of the American Heart Association · 2025Observational
- Fully Automated Photoplethysmography-Based Wearable Atrial Fibrillation Screening in a Hospital Setting.Diagnostics (Basel, Switzerland) · 2025Article
- Wearable Devices for Quantifying Atrial Fibrillation Burden: A Systematic Review and Bayesian Meta-Analysis.Journal of cardiovascular development and disease · 2025Review
- Ambulatory atrial fibrillation detection and quantification by wristworn AI device compared to standard holter monitoring.NPJ digital medicine · 2025Article
- Wear Your Heart on Your Sleeve: Smart Textile ECG Wearables for Comfort, Integration, Signal Quality and Continuous Monitoring in Paroxysmal Atrial Fibrillation.Sensors (Basel, Switzerland) · 2025Review
- Continuous smartwatch monitoring after atrial fibrillation ablation: feasibility of burden estimation and association with quality of life.Frontiers in cardiovascular medicine · 2025Article
- A Narrowband IoT Personal Sensor for Long-Term Heart Rate Monitoring and Atrial Fibrillation Detection.Sensors (Basel, Switzerland) · 2024Article
- [Characterization of atrial fibrillation burden using wearables].Herzschrittmachertherapie & Elektrophysiologie · 2024Review
- Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024Article
- Continuous atrial fibrillation monitoring using a wearable smartwatch: Using long-term Holter as reference.Digital healthArticle
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aims: Recent studies suggest that atrial fibrillation (AF) burden (time AF is present) is an independent risk factor for stroke. The aim of this trial was to study the feasibility and accuracy to identify AF episodes and quantify AF burden in patients with a known history of paroxysmal AF with a photoplethysmography (PPG)-based wearable. Methods and results: In this prospective, single-centre trial, the PPG-based estimation of AF burden was compared with measurements of a conventional 48 h Holter electrocardiogram (ECG), which served as the gold standard. An automated algorithm performed PPG analysis, while a cardiologist, blinded for the PPG data, analysed the ECG data. Detected episodes of AF measured by both methods were aligned timewise.Out of 100 patients recruited, 8 had to be excluded due to technical issues. Data from 92 patients were analysed [55.4% male; age 73.3 years (standard deviation, SD: 10.4)]. Twenty-five patients presented AF during the study period. The intraclass correlation coefficient of total AF burden minutes detected by the two measurement methods was 0.88. The percentage of correctly identified AF burden over all patients was 85.1% and the respective parameter for non-AF time was 99.9%. Conclusion: Our results demonstrate that a PPG-based wearable in combination with an analytical algorithm appears to be suitable for a semiquantitative estimation of AF burden in patients with a known history of paroxysmal AF. Trial Registration number: NCT04563572.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.