Rationale and design of a large population study to validate software for the assessment of atrial fibrillation from data acquired by a consumer tracker or smartwatch: The Fitbit heart study

[Display omitted] Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software alg...

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Published in:The American heart journal Vol. 238; pp. 16 - 26
Main Authors: Lubitz, Steven A., Faranesh, Anthony Z., Atlas, Steven J., McManus, David D., Singer, Daniel E., Pagoto, Sherry, Pantelopoulos, Alexandros, Foulkes, Andrea S.
Format: Journal Article
Language:English
Published: United States Elsevier Inc 01.08.2021
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ISSN:0002-8703, 1097-6744, 1097-6744
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Abstract [Display omitted] Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment. The Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF. The Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.
AbstractList [Display omitted] Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment. The Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF. The Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.
Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment.BACKGROUNDEarly detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment.The Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF.METHODSThe Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF.The Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.CONCLUSIONSThe Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.
Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment. The Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF. The Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.
BackgroundEarly detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment.MethodsThe Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF.ConclusionsThe Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.
Author Pagoto, Sherry
Pantelopoulos, Alexandros
McManus, David D.
Singer, Daniel E.
Lubitz, Steven A.
Atlas, Steven J.
Foulkes, Andrea S.
Faranesh, Anthony Z.
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  surname: Lubitz
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  organization: Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
– sequence: 2
  givenname: Anthony Z.
  surname: Faranesh
  fullname: Faranesh, Anthony Z.
  organization: Fitbit, Inc, San Francisco, CA
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  givenname: Steven J.
  surname: Atlas
  fullname: Atlas, Steven J.
  organization: Harvard Medical School, Boston, MA
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  givenname: David D.
  surname: McManus
  fullname: McManus, David D.
  organization: Division of Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, MA
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  givenname: Daniel E.
  surname: Singer
  fullname: Singer, Daniel E.
  organization: Harvard Medical School, Boston, MA
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  givenname: Alexandros
  surname: Pantelopoulos
  fullname: Pantelopoulos, Alexandros
  organization: Fitbit, Inc, San Francisco, CA
– sequence: 8
  givenname: Andrea S.
  surname: Foulkes
  fullname: Foulkes, Andrea S.
  organization: Harvard Medical School, Boston, MA
BackLink https://www.ncbi.nlm.nih.gov/pubmed/33865810$$D View this record in MEDLINE/PubMed
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PublicationDate_xml – month: 08
  year: 2021
  text: 2021-08-01
  day: 01
PublicationDecade 2020
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: Philadelphia
PublicationTitle The American heart journal
PublicationTitleAlternate Am Heart J
PublicationYear 2021
Publisher Elsevier Inc
Elsevier Limited
Publisher_xml – name: Elsevier Inc
– name: Elsevier Limited
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Snippet [Display omitted] Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology...
Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of...
BackgroundEarly detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is...
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SubjectTerms Algorithms
Cardiac arrhythmia
Computer programs
Consent
Data acquisition
EKG
Enrollments
Fibrillation
Flutter
Heart
Heart rate
Morbidity
Participation
Population studies
Population-based studies
Rhythm
Sensors
Smart devices
Smartphones
Smartwatches
Software
Telemedicine
Waveforms
Wearable computers
Wearable technology
Wrist
Title Rationale and design of a large population study to validate software for the assessment of atrial fibrillation from data acquired by a consumer tracker or smartwatch: The Fitbit heart study
URI https://www.clinicalkey.com/#!/content/1-s2.0-S0002870321000934
https://dx.doi.org/10.1016/j.ahj.2021.04.003
https://www.ncbi.nlm.nih.gov/pubmed/33865810
https://www.proquest.com/docview/2543022003
https://www.proquest.com/docview/2515063936
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