Background And Aims: Atrial fibrillation (AF) or atrial flutter (AFL) after cardiac surgery are common and associated with adverse outcomes. The increased risk related to AF or AFL may extend beyond discharge. This study aims to determine whether photoplethysmography (PPG)-based smartphone monitoring to detect AF or AFL after hospital discharge following cardiac surgery improves AF management.
View Article and Find Full Text PDFBackground: Consumer-oriented wearable devices (CWDs) such as smartphones and smartwatches have gained prominence for their ability to detect atrial fibrillation (AF) through proprietary algorithms using electrocardiography or photoplethysmography (PPG)-based digital recordings. Despite numerous individual validation studies, a direct comparison of interdevice performance is lacking.
Objective: This study aimed to evaluate and compare the ability of CWDs to distinguish between sinus rhythm and AF.
Background: Recurrence after atrial fibrillation (AF) ablation is frequent. Monitoring with long-term electrocardiograms (ECGs) is constrained by limited monitoring time, measurement dispersion, and cost. Selected photoplethysmography (PPG) smartphone applications have demonstrated excellent accuracy for AF detection and could mitigate these limitations.
View Article and Find Full Text PDFObjectives: Cardiac arrhythmias predict poor outcome after myocardial infarction (MI). We studied if arrhythmia monitoring with an insertable cardiac monitor (ICM) can improve treatment and outcome.
Design: BIO|GUARD-MI was a randomized, international open-label study with blinded outcome assessment.
Aims: Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions.
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