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Validation of a novel smartphone-based photoplethysmographic method for ambulatory heart rhythm diagnostics: the SMARTBEATS study.
Europace
March 2024
Karolinska Institutet, Department of Clinical Sciences, Danderyd University Hospital, Entrévägen 2, 182 88, Stockholm, Sweden.
Aims: In the current guidelines, smartphone photoplethysmography (PPG) is not recommended for diagnosis of atrial fibrillation (AF), without a confirmatory electrocardiogram (ECG) recording. Previous validation studies have been performed under supervision in healthcare settings, with limited generalizability of the results. We aim to investigate the diagnostic performance of a smartphone-PPG method in a real-world setting, with ambulatory unsupervised smartphone-PPG recordings, compared with simultaneous ECG recordings and including patients with atrial flutter (AFL).
View Article and Find Full Text PDFRealtime Diagnosis from Electrocardiogram Artificial Intelligence-Guided Screening for Atrial Fibrillation with Long Follow-Up (REGAL): Rationale and design of a pragmatic, decentralized, randomized controlled trial.
Am Heart J
January 2024
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
Background: Atrial fibrillation (AF) is associated with increased risks of stroke and dementia. Early diagnosis and treatment could reduce the disease burden, but AF is often undiagnosed. An artificial intelligence (AI) algorithm has been shown to identify patients with previously unrecognized AF; however, monitoring these high-risk patients has been challenging.
View Article and Find Full Text PDFDiagnostic accuracy of the PMcardio smartphone application for artificial intelligence-based interpretation of electrocardiograms in primary care (AMSTELHEART-1).
Cardiovasc Digit Health J
June 2023
Department of General Practice, Amsterdam UMC location University of Amsterdam, Amsterdam, Netherlands.
Background: The use of 12-lead electrocardiogram (ECG) is common in routine primary care, however it can be difficult for less experienced ECG readers to adequately interpret the ECG.
Objective: To validate a smartphone application (PMcardio) as a stand-alone interpretation tool for 12-lead ECG in primary care.
Methods: We recruited consecutive patients who underwent 12-lead ECG as part of routinely indicated primary care in the Netherlands.
Article Synopsis
- The Heartline Study is a large-scale trial aimed at evaluating the effectiveness of wearable devices, like the Apple Watch, for early detection of atrial fibrillation (AF) in older adults (65+) who either have no history of AF or are already diagnosed and on anticoagulant treatment.
- Participants are randomly assigned to either use the Apple Watch with features for detecting irregular heart rhythms and ECG monitoring or to just engage with a digital health program through an iPhone app, while all assessments are completed via the app.
- The main goal is to determine if using the Apple Watch can reduce the time it takes to get a clinical diagnosis of AF, alongside gathering data on various health outcomes related to AF management.
Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction.
Nat Med
December 2022
Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA.
Although artificial intelligence (AI) algorithms have been shown to be capable of identifying cardiac dysfunction, defined as ejection fraction (EF) ≤ 40%, from 12-lead electrocardiograms (ECGs), identification of cardiac dysfunction using the single-lead ECG of a smartwatch has yet to be tested. In the present study, a prospective study in which patients of Mayo Clinic were invited by email to download a Mayo Clinic iPhone application that sends watch ECGs to a secure data platform, we examined patient engagement with the study app and the diagnostic utility of the ECGs. We digitally enrolled 2,454 unique patients (mean age 53 ± 15 years, 56% female) from 46 US states and 11 countries, who sent 125,610 ECGs to the data platform between August 2021 and February 2022; 421 participants had at least one watch-classified sinus rhythm ECG within 30 d of an echocardiogram, of whom 16 (3.
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