Prospective Validation Study of AI-based Prediction Algorithm for the Prediction of Paroxysmal Atrial Fibrillation
NCT ID: NCT05725187
Last Updated: 2024-09-26
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ENROLLING_BY_INVITATION
600 participants
OBSERVATIONAL
2022-10-14
2025-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Low risk group for paroxysmal atrial fibrillation
Subject patients are above 20 in age who are hospitalized in our hospital or outpatients with arrhythmia symptoms after the clinical research approval. The sinus rhythm electrocardiogram at the time of the patient's participation in the study is put into the artificial intelligence prediction algorithm, and the risk stratification results are blinded and are not informed to both the research director and the subjects. For the low-risk group, after attaching the wearable electrocardiogram to the subject, the electrocardiogram recorded a week later is analyzed to confirm the occurrence of atrial fibrillation.
MobiCare
It is a 9.2g wearable electrocardiogram device, mobiCARE, in the form of a patch, and the model name is MC200M.
High risk group for paroxysmal atrial fibrillation
Subject patients are above 20 in age who are hospitalized in our hospital or outpatients with arrhythmia symptoms after the clinical research approval. The sinus rhythm electrocardiogram at the time of the patient's participation in the study is put into the artificial intelligence prediction algorithm, and the risk stratification results are blinded and are not informed to both the research director and the subjects. For the highrisk group, after attaching the wearable electrocardiogram to the subject, the electrocardiogram recorded a week later is analyzed to confirm the occurrence of atrial fibrillation.
MobiCare
It is a 9.2g wearable electrocardiogram device, mobiCARE, in the form of a patch, and the model name is MC200M.
Interventions
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MobiCare
It is a 9.2g wearable electrocardiogram device, mobiCARE, in the form of a patch, and the model name is MC200M.
Eligibility Criteria
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Inclusion Criteria
* Participants are patients with symptom of arrhythmia who visited outpatient clinic or who have been hospitalized
Exclusion Criteria
* Excluding pregnant women and lactating women.
20 Years
ALL
Yes
Sponsors
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Ewha Womans University Seoul Hospital
OTHER
Ewha Womans University Mokdong Hospital
OTHER
Responsible Party
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Principal Investigators
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Sumi Jung
Role: STUDY_DIRECTOR
Ewha Womans University Mokdong Hospital
Locations
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Chonnam National University Hospital
Gwangju, , South Korea
Yongin Severance Hospital
Gyeonggi-do, , South Korea
Gachon University Gil Medical Center
Incheon, , South Korea
Chungbuk National University Hospital
Jungbuk, , South Korea
Kyung Hee University Hospital
Seoul, , South Korea
Korea University Anam Hospital
Seoul, , South Korea
Hanyang University Seoul Hospital
Seoul, , South Korea
Chung-Ang University Hospital
Seoul, , South Korea
Ewha Womans University Seoul Hospital
Seoul, , South Korea
Ewha Womans University Mokdong Hospital
Seoul, , South Korea
Korea University Guro Hospital
Seoul, , South Korea
Countries
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References
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Ribeiro AH, Ribeiro MH, Paixao GMM, Oliveira DM, Gomes PR, Canazart JA, Ferreira MPS, Andersson CR, Macfarlane PW, Meira W Jr, Schon TB, Ribeiro ALP. Automatic diagnosis of the 12-lead ECG using a deep neural network. Nat Commun. 2020 Apr 9;11(1):1760. doi: 10.1038/s41467-020-15432-4.
Willems S, Borof K, Brandes A, Breithardt G, Camm AJ, Crijns HJGM, Eckardt L, Gessler N, Goette A, Haegeli LM, Heidbuchel H, Kautzner J, Ng GA, Schnabel RB, Suling A, Szumowski L, Themistoclakis S, Vardas P, van Gelder IC, Wegscheider K, Kirchhof P. Systematic, early rhythm control strategy for atrial fibrillation in patients with or without symptoms: the EAST-AFNET 4 trial. Eur Heart J. 2022 Mar 21;43(12):1219-1230. doi: 10.1093/eurheartj/ehab593.
Park J, Shim J, Lee JM, Park JK, Heo J, Chang Y, Song TJ, Kim DH, Lee HA, Yu HT, Kim TH, Uhm JS, Kim YD, Nam HS, Joung B, Lee MH, Heo JH, Pak HN; RAFAS Investigators*. Risks and Benefits of Early Rhythm Control in Patients With Acute Strokes and Atrial Fibrillation: A Multicenter, Prospective, Randomized Study (the RAFAS Trial). J Am Heart Assoc. 2022 Feb;11(3):e023391. doi: 10.1161/JAHA.121.023391. Epub 2022 Jan 19.
Noseworthy PA, Attia ZI, Behnken EM, Giblon RE, Bews KA, Liu S, Gosse TA, Linn ZD, Deng Y, Yin J, Gersh BJ, Graff-Radford J, Rabinstein AA, Siontis KC, Friedman PA, Yao X. Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial. Lancet. 2022 Oct 8;400(10359):1206-1212. doi: 10.1016/S0140-6736(22)01637-3. Epub 2022 Sep 27.
Attia ZI, Noseworthy PA, Lopez-Jimenez F, Asirvatham SJ, Deshmukh AJ, Gersh BJ, Carter RE, Yao X, Rabinstein AA, Erickson BJ, Kapa S, Friedman PA. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction. Lancet. 2019 Sep 7;394(10201):861-867. doi: 10.1016/S0140-6736(19)31721-0. Epub 2019 Aug 1.
Other Identifiers
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PROVISION-AF
Identifier Type: -
Identifier Source: org_study_id
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