. 2019 Nov 14;381(20):1909-1917.

doi: 10.1056/NEJMoa1901183.

Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation

Marco V Perez¹, Kenneth W Mahaffey¹, Haley Hedlin¹, John S Rumsfeld¹, Ariadna Garcia¹, Todd Ferris¹, Vidhya Balasubramanian¹, Andrea M Russo¹, Amol Rajmane¹, Lauren Cheung¹, Grace Hung¹, Justin Lee¹, Peter Kowey¹, Nisha Talati¹, Divya Nag¹, Santosh E Gummidipundi¹, Alexis Beatty¹, Mellanie True Hills¹, Sumbul Desai¹, Christopher B Granger¹, Manisha Desai¹, Mintu P Turakhia¹; Apple Heart Study Investigators

Collaborators, Affiliations

Collaborators

Apple Heart Study Investigators:
Marco V Perez, Mintu P Turakhia, Karma Lhamo, Shea Smith, Maya Berdichesky, Bhanu Sharma, Kenneth Mahaffey, Justin Parizo, Christoph Olivier, Mai Nguyen, Sushmitha Tallapalli, Rajvir Kaur, Rebecca Gardner, Grace Hung, Don Mitchell, Garrick Olson, Somalee Datta, Dmitry Gerenrot, Xu Wang, Patrick McCoy, Bikas Satpathy, Hans Jacobsen, Dmitry Makovey, Andrew Martin, Alex Perino, Connor O'Brien, Avani Gupta, Christine Toruno, Steve Waydo, Chris Brouse, Danielle Dorfman, Jeff Stein, Jerry Huang, Mithun Patel, Steve Fleischer, Evan Doll, Mike O'Reilly, Kelsey Dedoshka, Ming Chou, Heather Daniel, Matt Crowley, Candace Martin, Tim Kirby, Maz Brumand, Kelly McCrystale, Myra Haggerty, Jennifer Newberger, Dan Keen, Peter Antall, Kristina Holbrook, Allison Braly, Garrett Noone, Ben Leathers, Alisa Montrose, Jeff Kosowsky, Danielle Lewis, J R Finkelmeier, Kristen Bemis, Kenneth W Mahaffey, Manisha Desai, Nisha Talati, Divya Nag, Amol Rajmane, Sumbul Desai, Deidre Caldbeck, Lauren Cheung, Christopher Granger, John Rumsfeld, Peter R Kowey, Mellanie T Hills, Andrea Russo, Frank Rockhold, Christine Albert, Alvaro Alonso, Lisa Wruck, Karen Friday, Matthew Wheeler, Chad Brodt, Shirley Park, Albert Rogers, Ronald Jones, David Ouyang, Lee Chang, Alberta Yen, Julie Dong, Petra Mamic, Paul Cheng, Rajan Shah, Peem Lorvidhaya

Affiliation

¹ 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.).

PMID: 31722151
PMCID: PMC8112605
DOI: 10.1056/NEJMoa1901183

Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation

Marco V Perez et al. N Engl J Med. 2019.

. 2019 Nov 14;381(20):1909-1917.

doi: 10.1056/NEJMoa1901183.

Authors

Collaborators

Apple Heart Study Investigators:
Marco V Perez, Mintu P Turakhia, Karma Lhamo, Shea Smith, Maya Berdichesky, Bhanu Sharma, Kenneth Mahaffey, Justin Parizo, Christoph Olivier, Mai Nguyen, Sushmitha Tallapalli, Rajvir Kaur, Rebecca Gardner, Grace Hung, Don Mitchell, Garrick Olson, Somalee Datta, Dmitry Gerenrot, Xu Wang, Patrick McCoy, Bikas Satpathy, Hans Jacobsen, Dmitry Makovey, Andrew Martin, Alex Perino, Connor O'Brien, Avani Gupta, Christine Toruno, Steve Waydo, Chris Brouse, Danielle Dorfman, Jeff Stein, Jerry Huang, Mithun Patel, Steve Fleischer, Evan Doll, Mike O'Reilly, Kelsey Dedoshka, Ming Chou, Heather Daniel, Matt Crowley, Candace Martin, Tim Kirby, Maz Brumand, Kelly McCrystale, Myra Haggerty, Jennifer Newberger, Dan Keen, Peter Antall, Kristina Holbrook, Allison Braly, Garrett Noone, Ben Leathers, Alisa Montrose, Jeff Kosowsky, Danielle Lewis, J R Finkelmeier, Kristen Bemis, Kenneth W Mahaffey, Manisha Desai, Nisha Talati, Divya Nag, Amol Rajmane, Sumbul Desai, Deidre Caldbeck, Lauren Cheung, Christopher Granger, John Rumsfeld, Peter R Kowey, Mellanie T Hills, Andrea Russo, Frank Rockhold, Christine Albert, Alvaro Alonso, Lisa Wruck, Karen Friday, Matthew Wheeler, Chad Brodt, Shirley Park, Albert Rogers, Ronald Jones, David Ouyang, Lee Chang, Alberta Yen, Julie Dong, Petra Mamic, Paul Cheng, Rajan Shah, Peem Lorvidhaya

Affiliation

¹ 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.).

PMID: 31722151
PMCID: PMC8112605
DOI: 10.1056/NEJMoa1901183

Abstract

Background: Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown.

Methods: Participants 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.

Results: We 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.

Conclusions: The 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.).

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Figures

**Figure 1.. Participant Selection.**
Of the 1216 potential participants who were excluded because they did not have a first study visit, 4 received an ECG patch. AF denotes atrial fibrillation, and ECG electrocardiography.

**Figure 2.. Irregular Pulse Notifications, According to Age and Sex.**
Horizontal bars indicate 97.5% confidence intervals.

**Figure 3.. Yield of Atrial Fibrillation on ECG Patch Monitoring.**
Horizontal bars indicate 97.5% confidence intervals.

See this image and copyright information in PMC

Comment in

Watched by Apple.
Campion EW, Jarcho JA. Campion EW, et al. N Engl J Med. 2019 Nov 14;381(20):1964-1965. doi: 10.1056/NEJMe1913980. N Engl J Med. 2019. PMID: 31722159 No abstract available.
Bleibt bald kein VHF mehr unentdeckt?
Holzgreve H. Holzgreve H. MMW Fortschr Med. 2019 Dec;161(21-22):30. doi: 10.1007/s15006-019-1224-y. MMW Fortschr Med. 2019. PMID: 31828643 German. No abstract available.
A Smartwatch to Identify Atrial Fibrillation.
De Silva K, Chow C, Kumar S. De Silva K, et al. N Engl J Med. 2020 Mar 5;382(10):974. doi: 10.1056/NEJMc1916858. N Engl J Med. 2020. PMID: 32130824 No abstract available.
A Smartwatch to Identify Atrial Fibrillation.
Auer J, Primus C. Auer J, et al. N Engl J Med. 2020 Mar 5;382(10):974. doi: 10.1056/NEJMc1916858. N Engl J Med. 2020. PMID: 32130825 No abstract available.
A Smartwatch to Identify Atrial Fibrillation.
Qiu J, Wang Y. Qiu J, et al. N Engl J Med. 2020 Mar 5;382(10):974-975. doi: 10.1056/NEJMc1916858. N Engl J Med. 2020. PMID: 32130826 No abstract available.
A Smartwatch to Identify Atrial Fibrillation.
Wyatt KD. Wyatt KD. N Engl J Med. 2020 Mar 5;382(10):975. doi: 10.1056/NEJMc1916858. N Engl J Med. 2020. PMID: 32130827 No abstract available.
[Smartwatch: a tool for public health?].
Berrut G. Berrut G. Geriatr Psychol Neuropsychiatr Vieil. 2020 Mar 1;18(1):5. doi: 10.1684/pnv.2020.0847. Geriatr Psychol Neuropsychiatr Vieil. 2020. PMID: 32160985 French. No abstract available.
Review article: Large-scale assessment of a smartwatch to identify atrial fibrillation. Perez, M, Mahaffey, K, Hedlin, H., et al.
Kohlman-Trigoboff D. Kohlman-Trigoboff D. J Vasc Nurs. 2020 Jun;38(2):93-94. doi: 10.1016/j.jvn.2020.04.001. Epub 2020 May 4. J Vasc Nurs. 2020. PMID: 32534659 No abstract available.

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Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation

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Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation

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