Diagnostic Performance of a Smartphone-Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting

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. © 2016 the authors. published on behalf of the american heart association,inc.,by wiley blackwell.