• N. Engl. J. Med. · Nov 2019

    Pragmatic Clinical Trial

    Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.

    • Marco V Perez, Kenneth W Mahaffey, Haley Hedlin, John S Rumsfeld, Ariadna Garcia, Todd Ferris, Vidhya Balasubramanian, Andrea M Russo, Amol Rajmane, Lauren Cheung, Grace Hung, Justin Lee, Peter Kowey, Nisha Talati, Divya Nag, Santosh E Gummidipundi, Alexis Beatty, Mellanie True Hills, Sumbul Desai, Christopher B Granger, Manisha Desai, Mintu P Turakhia, and Apple Heart Study Investigators.
    • From the Division of Cardiovascular Medicine (M.V.P.), Stanford Center for Clinical Research (K.W.M., A.R., N.T.), the Quantitative Sciences Unit (H.H., A.G., V.B., J.L., S.E.G., M.D.), Information Resources and Technology (T.F., G.H.), Department of Medicine (S.D.), and the Center for Digital Health (M.P.T.), Stanford University, Stanford, Apple, Cupertino (L.C., D.N., A.B., S.D.), and the Veterans Affairs Palo Alto Health Care System, Palo Alto (M.P.T.) - all in California; the University of Colorado School of Medicine, Aurora (J.S.R.); the Division of Cardiovascular Disease, Cooper Medical School of Rowan University, Camden, NJ (A.M.R.); the Lankenau Heart Institute and Jefferson Medical College, Philadelphia (P.K.); StopAfib.org, American Foundation for Women's Health, Decatur, TX (M.T.H.); and the Duke Clinical Research Institute, Duke University, Durham, NC (C.B.G.).
    • N. Engl. J. Med. 2019 Nov 14; 381 (20): 1909-1917.

    BackgroundOptical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown.MethodsParticipants without atrial fibrillation (as reported by the participants themselves) used a smartphone (Apple iPhone) app to consent to monitoring. If a smartwatch-based irregular pulse notification algorithm identified possible atrial fibrillation, a telemedicine visit was initiated and an electrocardiography (ECG) patch was mailed to the participant, to be worn for up to 7 days. Surveys were administered 90 days after notification of the irregular pulse and at the end of the study. The main objectives were to estimate the proportion of notified participants with atrial fibrillation shown on an ECG patch and the positive predictive value of irregular pulse intervals with a targeted confidence interval width of 0.10.ResultsWe recruited 419,297 participants over 8 months. Over a median of 117 days of monitoring, 2161 participants (0.52%) received notifications of irregular pulse. Among the 450 participants who returned ECG patches containing data that could be analyzed - which had been applied, on average, 13 days after notification - atrial fibrillation was present in 34% (97.5% confidence interval [CI], 29 to 39) overall and in 35% (97.5% CI, 27 to 43) of participants 65 years of age or older. Among participants who were notified of an irregular pulse, the positive predictive value was 0.84 (95% CI, 0.76 to 0.92) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular pulse notification and 0.71 (97.5% CI, 0.69 to 0.74) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular tachogram. Of 1376 notified participants who returned a 90-day survey, 57% contacted health care providers outside the study. There were no reports of serious app-related adverse events.ConclusionsThe probability of receiving an irregular pulse notification was low. Among participants who received notification of an irregular pulse, 34% had atrial fibrillation on subsequent ECG patch readings and 84% of notifications were concordant with atrial fibrillation. This siteless (no on-site visits were required for the participants), pragmatic study design provides a foundation for large-scale pragmatic studies in which outcomes or adherence can be reliably assessed with user-owned devices. (Funded by Apple; Apple Heart Study ClinicalTrials.gov number, NCT03335800.).Copyright © 2019 Massachusetts Medical Society.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

Want more great medical articles?

Keep up to date with a free trial of metajournal, personalized for your practice.
1,624,503 articles already indexed!

We guarantee your privacy. Your email address will not be shared.