Prospective Validation Study of AI-based Prediction Algorithm for the Prediction of Paroxysmal Atrial Fibrillation

NCT05725187 | Enrolling By Invitation DMC

• 1 other identifier: PROVISION-AF
• Study Type: observational
• Target: 600
• Locations: 1 country
• Sites: 11

Brief Summary

The purpose of this study is to predict the occurrence of paroxysmal atrial fibrillation by finding high-risk group from normal sinus rhythm ECG through artificial intelligence-based prediction algorithm.

Conditions

Atrial Fibrillation Paroxysmal

Keywords

artificial intelligence; electrocardiogram

Outcome Measures

Primary Outcomes (1)

• Occurrence of paroxysmal AF

  The AI prediction algorithm classifies patients into high-risk and low-risk categories for predicting paroxysmal atrial fibrillation within a week, based on ECG recordings of those with normal sinus rhythm. The accuracy of the prediction will be assessed through the use of a wearable device that records occurrence of paroxysmal atrial fibrillation over the course of a week.

  1 week

Secondary Outcomes (1)

• Performance verification of AI prediction model

  1 week

Other Outcomes (1)

• Predictive capabilities of AI prediction model compared to expert cardiologists

  10 minute

Study Arms (2)

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.

Device: MobiCare

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.

Device: MobiCare

Interventions

MobiCare DEVICE

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; Low risk group for paroxysmal atrial fibrillation

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Participants are selected from adults above age of 20 with their consent with a target for patients who come to the hospital with arrhythmia symptoms from an outpatient clinic or who are admitted to a hospital.

You may qualify if:

• Participants must be above 20 in age
• Participants are patients with symptom of arrhythmia who visited outpatient clinic or who have been hospitalized

You may not qualify if:

• Excluding patients with cardiac implantable electronic device such as pacemakers, implantable defibrillators (ICD), or cardiac resynchronization therapy (CRT).
• Excluding pregnant women and lactating women.

Sponsors & Collaborators

• Ewha Womans University Mokdong Hospital: lead
• Ewha Womans University Seoul Hospital: collaborator

Study Sites (11)

Chonnam National University Hospital

Gwangju, 61469, South Korea

Location

Yongin Severance Hospital

Gyeonggi-do, 16995, South Korea

Location

Gachon University Gil Medical Center

Incheon, 21565, South Korea

Location

Chungbuk National University Hospital

Jungbuk, 28644, South Korea

Location

Kyung Hee University Hospital

Seoul, 02447, South Korea

Location

Korea University Anam Hospital

Seoul, 02841, South Korea

Location

Hanyang University Seoul Hospital

Seoul, 04763, South Korea

Location

Chung-Ang University Hospital

Seoul, 06973, South Korea

Location

Ewha Womans University Seoul Hospital

Seoul, 07804, South Korea

Location

Ewha Womans University Mokdong Hospital

Seoul, 07985, South Korea

Location

Korea University Guro Hospital

Seoul, 08308, South Korea

Location

Related Publications (5)

• 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.

  PMID: 32273514 BACKGROUND

• 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.

  PMID: 34447995 BACKGROUND

• 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.

  PMID: 35043663 BACKGROUND

• 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.

  PMID: 36179758 BACKGROUND

• 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.

  PMID: 31378392 BACKGROUND

MeSH Terms

Conditions

Atrial Fibrillation

Condition Hierarchy (Ancestors)

Arrhythmias, Cardiac; Heart Diseases; Cardiovascular Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Sumi Jung

  Ewha Womans University Mokdong Hospital

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 20, 2023
• First Posted: February 13, 2023
• Study Start: October 14, 2022
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2025
• Last Updated: September 26, 2024

Record last verified: 2024-09

Data Sharing

• IPD Sharing: Will not share

Locations

KR (11)