Clinical trial NCT05725187: Prospective Validation Study of AI-based Prediction Algorithm for the Prediction of Paroxysmal Atrial Fibrillation
Official title: Prospective Validation Study of Artificial Intelligence-based Prediction Algorithm for the Prediction of Paroxysmal Atrial Fibrillation
Study type: OBSERVATIONAL
Overall status: ENROLLING_BY_INVITATION
Conditions: Atrial Fibrillation Paroxysmal
Keywords: artificial intelligence
electrocardiogram
Lead sponsor: Ewha Womans University Mokdong Hospital
Sponsor class: OTHER
Collaborators: name: Ewha Womans University Seoul Hospital
First posted: 2023-02-13
Enrollment: 600
Sex: ALL
Minimum age (years): 20
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
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.

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.

Detailed description: This study is a multi-center, prospective observational validation study. Patients aged 18 or above who are hospitalized at our hospital or who visited the outpatient clinic with arrhythmia symptoms (such as palpitation) after the clinical research approval will be enrolled. The normal sinus rhythm electrocardiogram (ECG) at the time of participation in the study is recorded and put into the artificial intelligence prediction algorithm. The result of risk stratification is blinded and will not be informed to both the research director and subjects. After applying wearable devices to the subject, the ECG recorded for the first week is analyzed to confirm the occurrence of paroxysmal atrial fibrillation (the gold standard for diagnosis of atrial fibrillation). When the wearable devices are removed, the 12 lead electrocardiogram will be taken again, and if it shows normal sinus rhythm electrocardiogram, then it will be put into the artificial intelligence prediction algorithm to calculate the result as well.

Eligibility criteria: Inclusion Criteria:

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

Exclusion Criteria:

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

Primary outcomes:
measure: Occurrence of paroxysmal AF
timeFrame: 1 week
Secondary outcomes:
measure: Performance verification of AI prediction model
timeFrame: 1 week
Other outcomes:
measure: Predictive capabilities of AI prediction model compared to expert cardiologists
timeFrame: 10 minute
Locations:
city: Chungbuk
country: Korea, Republic of
facility: Chungbuk National University Hospital
city: Gwangju
country: Korea, Republic of
facility: Chonnam National University Hospital
city: Gyeonggi-do
country: Korea, Republic of
facility: Yongin Severance Hospital
city: Incheon
country: Korea, Republic of
facility: Gachon University Gil Medical Center
city: Seoul
country: Korea, Republic of
facility: Kyung Hee University Hospital
city: Seoul
country: Korea, Republic of
facility: Korea University Anam Hospital
city: Seoul
country: Korea, Republic of
facility: Hanyang University Seoul Hospital
city: Seoul
country: Korea, Republic of
facility: Chung-Ang University Hospital
city: Seoul
country: Korea, Republic of
facility: Ewha Womans University Seoul Hospital
city: Seoul
country: Korea, Republic of
facility: Ewha Womans University Mokdong Hospital
city: Seoul
country: Korea, Republic of
facility: Korea University Guro Hospital
Study officials:
affiliation: Ewha Womans University Mokdong Hospital
name: Sumi Jung
role: STUDY_DIRECTOR
References:
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