Diagnostic Performance of a Smartphone‐Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting
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Open Access
- 6 July 2016
- journal article
- research article
- Published by Ovid Technologies (Wolters Kluwer Health) in Journal of the American Heart Association
- Vol. 5 (7)
- https://doi.org/10.1161/jaha.116.003428
Abstract
Background: Diagnosing atrial fibrillation ( AF ) before ischemic stroke occurs is a priority for stroke prevention in AF . Smartphone camera–based photoplethysmographic ( PPG ) pulse waveform measurement discriminates between different heart rhythms, but its ability to diagnose AF in real‐world situations has not been adequately investigated. We sought to assess the diagnostic performance of a standalone smartphone PPG application, Cardiio Rhythm, for AF screening in primary care setting. Methods and Results: Patients with hypertension, with diabetes mellitus, and/or aged ≥65 years were recruited. A single‐lead ECG was recorded by using the AliveCor heart monitor with tracings reviewed subsequently by 2 cardiologists to provide the reference standard. PPG measurements were performed by using the Cardiio Rhythm smartphone application. AF was diagnosed in 28 (2.76%) of 1013 participants. The diagnostic sensitivity of the Cardiio Rhythm for AF detection was 92.9% (95% CI ] 77–99%) and was higher than that of the AliveCor automated algorithm (71.4% [95% CI 51–87%]). The specificities of Cardiio Rhythm and the AliveCor automated algorithm were comparable (97.7% [95% CI : 97–99%] versus 99.4% [95% CI 99–100%]). The positive predictive value of the Cardiio Rhythm was lower than that of the AliveCor automated algorithm (53.1% [95% CI 38–67%] versus 76.9% [95% CI 56–91%]); both had a very high negative predictive value (99.8% [95% CI 99–100%] versus 99.2% [95% CI 98–100%]). Conclusions: The Cardiio Rhythm smartphone PPG application provides an accurate and reliable means to detect AF in patients at risk of developing AF and has the potential to enable population‐based screening for AF .Keywords
This publication has 25 references indexed in Scilit:
- iPhone ECG application for community screening to detect silent atrial fibrillation: A novel technology to prevent strokeInternational Journal of Cardiology, 2013
- A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillationHeart Rhythm, 2012
- 2012 focused update of the ESC Guidelines for the management of atrial fibrillationEuropean Heart Journal, 2012
- Subclinical Atrial Fibrillation and the Risk of StrokeThe New England Journal of Medicine, 2012
- Investigating a smartphone imaging unit for photoplethysmographyPhysiological Measurement, 2010
- Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort studyThe Lancet, 2009
- Screening versus routine practice in detection of atrial fibrillation in patients aged 65 or over: cluster randomised controlled trialBMJ, 2007
- Meta-analysis: Antithrombotic Therapy to Prevent Stroke in Patients Who Have Nonvalvular Atrial FibrillationAnnals of Internal Medicine, 2007
- Photoplethysmography and its application in clinical physiological measurementPhysiological Measurement, 2007
- Stroke Severity in Atrial FibrillationStroke, 1996