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dc.contributor.authorLubitz, Steven A
dc.contributor.authorFaranesh, Anthony Z
dc.contributor.authorSelvaggi, Caitlin
dc.contributor.authorAtlas, Steven J
dc.contributor.authorMcManus, David D
dc.contributor.authorSinger, Daniel E
dc.contributor.authorPagoto, Sherry L.
dc.contributor.authorMcConnell, Michael V
dc.contributor.authorPantelopoulos, Alexandros
dc.contributor.authorFoulkes, Andrea S
dc.date.accessioned2024-01-16T17:56:35Z
dc.date.available2024-01-16T17:56:35Z
dc.date.issued2022-09-23
dc.identifier.citationLubitz SA, Faranesh AZ, Selvaggi C, Atlas SJ, McManus DD, Singer DE, Pagoto S, McConnell MV, Pantelopoulos A, Foulkes AS. Detection of Atrial Fibrillation in a Large Population Using Wearable Devices: The Fitbit Heart Study. Circulation. 2022 Nov 8;146(19):1415-1424. doi: 10.1161/CIRCULATIONAHA.122.060291. Epub 2022 Sep 23. PMID: 36148649; PMCID: PMC9640290.en_US
dc.identifier.eissn1524-4539
dc.identifier.doi10.1161/CIRCULATIONAHA.122.060291en_US
dc.identifier.pmid36148649
dc.identifier.urihttp://hdl.handle.net/20.500.14038/52973
dc.description.abstractBackground: Morbidity from undiagnosed atrial fibrillation (AF) may be preventable with early detection. Many consumer wearables contain optical photoplethysmography (PPG) sensors to measure pulse rate. PPG-based software algorithms that detect irregular heart rhythms may identify undiagnosed AF in large populations using wearables, but minimizing false-positive detections is essential. Methods: We performed a prospective remote clinical trial to examine a novel PPG-based algorithm for detecting undiagnosed AF from a range of wrist-worn devices. Adults aged ≥22 years in the United States without AF, using compatible wearable Fitbit devices and Android or iOS smartphones, were included. PPG data were analyzed using a novel algorithm that examines overlapping 5-minute pulse windows (tachograms). Eligible participants with an irregular heart rhythm detection (IHRD), defined as 11 consecutive irregular tachograms, were invited to schedule a telehealth visit and were mailed a 1-week ambulatory ECG patch monitor. The primary outcome was the positive predictive value of the first IHRD during ECG patch monitoring for concurrent AF. Results: A total of 455 699 participants enrolled (median age 47 years, 71% female, 73% White) between May 6 and October 1, 2020. IHRDs occurred for 4728 (1%) participants, and 2070 (4%) participants aged ≥65 years during a median of 122 (interquartile range, 110-134) days at risk for an IHRD. Among 1057 participants with an IHRD notification and subsequent analyzable ECG patch monitor, AF was present in 340 (32.2%). Of the 225 participants with another IHRD during ECG patch monitoring, 221 had concurrent AF on the ECG and 4 did not, resulting in an IHRD positive predictive value of 98.2% (95% CI, 95.5%-99.5%). For participants aged ≥65 years, the IHRD positive predictive value was 97.0% (95% CI, 91.4%-99.4%). Conclusions: A novel PPG software algorithm for wearable Fitbit devices exhibited a high positive predictive value for concurrent AF and identified participants likely to have AF on subsequent ECG patch monitoring. Wearable devices may facilitate identifying individuals with undiagnosed AF. Registration: URL: https://www. Clinicaltrials: gov; Unique identifier: NCT04380415.en_US
dc.language.isoenen_US
dc.relation.ispartofCirculationen_US
dc.relation.urlhttps://doi.org/10.1161/circulationaha.122.060291en_US
dc.rights© 2022 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial-NoDerivs License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited, the use is noncommercial, and no modifications or adaptations are made.en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectatrial fibrillationen_US
dc.subjectdiagnostic screening programsen_US
dc.subjectdigital technologyen_US
dc.subjectphotoplethysmographyen_US
dc.subjectwearable electronic devicesen_US
dc.titleDetection of Atrial Fibrillation in a Large Population Using Wearable Devices: The Fitbit Heart Studyen_US
dc.typeJournal Articleen_US
dc.source.journaltitleCirculation
dc.source.volume146
dc.source.issue19
dc.source.beginpage1415
dc.source.endpage1424
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.identifier.journalCirculation
refterms.dateFOA2024-01-16T17:56:36Z
dc.contributor.departmentMedicineen_US


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© 2022 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under
the terms of the Creative Commons Attribution Non-Commercial-NoDerivs License, which permits use, distribution, and reproduction in any medium, provided that the
original work is properly cited, the use is noncommercial, and no modifications or adaptations are made.
Except where otherwise noted, this item's license is described as © 2022 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial-NoDerivs License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited, the use is noncommercial, and no modifications or adaptations are made.