Atrial Fibrillation (AF)
Conditions
Keywords
atrial fibrillation, artificial intelligence, structural heart disease, electrocardiogram
Brief summary
The objective of this study is to evaluate whether an AI-ECG based screening strategy for detecting cardiac functional and structural abnormalities preserves clinical effectiveness and safety, compared with a conventional strategy of routine echocardiography in patients with AF, thereby demonstrating the non-inferiority of AI-ECG guided care.
Detailed description
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, with its prevalence having more than doubled over the past decade. AF is associated with an increased risk of stroke, heart failure, and mortality, thereby imposing a substantial burden on both patients and healthcare systems. Accordingly, contemporary clinical guidelines emphasize accurate diagnosis and early, integrated management of AF. In this context, transthoracic echocardiography has become a standard diagnostic tool for the assessment of structural heart disease and cardiac function. Despite being non-invasive and relatively low-cost, echocardiography is subject to several system-level limitations in routine clinical practice, including dependence on specialized equipment and trained personnel, scheduling delays, and inefficiencies related to repeated examinations. These constraints may create bottlenecks in the timely initiation and optimization of AF management. In real-world practice, a considerable proportion of patients with AF undergo echocardiography primarily to confirm the absence of significant structural heart disease or impaired function. A uniform strategy of performing echocardiography in all patients with AF may not be optimal from the perspectives of patient convenience and healthcare resource utilization. Moreover, depending on healthcare system capacity, access to echocardiography may delay the timely selection of optimal AF management. Conversely, selectively performing echocardiography in patients with a higher likelihood of structural or functional cardiac abnormalities may allow for a more efficient, timely, and targeted diagnostic approach. Artificial intelligence-enabled electrocardiography (AI-ECG) offers several practical advantages, including very short acquisition time, patients' convenience, substantially lower cost, and feasibility for repeated assessments during follow-up. AI-ECG may enable sensitive detection of changes in a patient's cardiac status over time. Positioning AI-ECG as an initial screening tool to identify patients with suspected structural or functional heart disease could facilitate a "screening-confirmation" diagnostic pathway, in which echocardiography is reserved for patients with abnormal or suspicious findings on AI-ECG. Such an approach has the potential to streamline initial and follow-up evaluations while maintaining patient safety.
Interventions
DIAGNOSTIC_TESTArtificial intelligence-enabled electrocardiography
An artificial intelligence algorithm applied to standard 12-lead electrocardiography designed to predict cardiac structural or functional abnormalities. This tool guides the decision to perform or withhold downstream echocardiography.
DIAGNOSTIC_TESTTransthoracic Echocardiography-Guided Assessment
Standard Transthoracic Echocardiography used to assess cardiac structure and function, serving as the reference standard for guiding clinical management in this study arm.
Sponsors
Seoul National University Hospital
Medical AI
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
19 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. AF documented by electrocardiography within the past 12 months * AF documented on a 12-lead electrocardiogram or recorded for ≥30 seconds on a single-lead or multi-lead electrocardiogram. 2. Patients for whom an initial or repeat transthoracic echocardiographic evaluation is clinically indicated. 3. A CHA₂DS₂-VA score of ≥2. 4. Aged ≥19 years at the time of enrollment and able to provide written informed consent voluntarily.
Exclusion criteria
1. Transthoracic echocardiography performed within the past 6 months. 2. Ventricular rate ≥110 beats per minute during atrial fibrillation. 3. Atrial fibrillation due to a reversible cause. 4. New York Heart Association (NYHA) functional class IV or European Heart Rhythm Association (EHRA) class IV symptoms. 5. Known history of structural heart disease or clinical findings suggestive of structural heart disease based on medical history and physical examination. (e.g., presence of a cardiac murmur of Levine scale grade 3 or higher on auscultation, or murmurs suggestive of moderate to severe mitral stenosis, such as an opening snap or diastolic rumbling murmur). 6. Baseline electrocardiographic conduction abnormalities or significant electrocardiographic findings suggestive of clinically meaningful structural heart disease (e.g., Mobitz type II second-degree atrioventricular block, third-degree atrioventricular block, or QTc ≥480 ms). 7. History of prior cardiac surgery. 8. History of acute coronary syndrome or coronary revascularization within the past 90 days. 9. History of intracardiac thrombosis or systemic thromboembolism within the past 90 days. 10. History of transient ischemic attack, ischemic stroke, or intracranial hemorrhage within the past 90 days. 11. History of ventricular tachycardia or ventricular fibrillation. 12. Severe liver disease associated with coagulopathy (e.g., AST or ALT \>3× the upper limit of normal, or total bilirubin \>2× the upper limit of normal). 13. Severe chronic kidney disease (stage V), requiring or imminently requiring dialysis. 14. Contraindication to anticoagulation therapy. 15. Pregnancy, breastfeeding, or planning pregnancy during the study period. 16. Life expectancy of less than 1 year. 17. Current participation in another randomized clinical trial.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Composite of all-cause Mortality, Stroke, CV Hospitalization, and AAD-Related SAEs | up to 10 years | Evaluation of the effectiveness of the strategy based on a composite endpoint comprising the following clinical events: 1. All-cause mortality; 2. Stroke or systemic thromboembolism; 3. Hospitalization due to worsening heart failure or acute coronary syndrome; 4. Serious adverse events related to antiarrhythmic drug therapy. The endpoint is defined as the time to the first occurrence of any of these components. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| All-cause mortality | up to 10 years | — |
| Stroke or systemic thromboembolism | up to 10 years | — |
| Heart failure worsening | up to 10 years | Heart failure worsening: An outpatient heart failure episode requiring intravenous diuretic therapy or initiation or escalation of oral diuretics, or hospitalization for heart failure (defined as heart failure being the primary reason for admission or requiring treatment in a healthcare facility for ≥12 hours with intravenous diuretics). |
| Hospitalization due to acute coronary syndrome | up to 10 years | — |
| Serious adverse events related to antiarrhythmic drug therapy | up to 10 years | Serious adverse events related to antiarrhythmic drug therapy: Hypotension, symptomatic drug-induced bradycardia, atrioventricular block, drug-induced atrial flutter or atrial tachycardia, torsade de pointes, ventricular tachycardia, ventricular fibrillation, or syncope. |
| Proportion of patients receiving rhythm control therapyc after the initial diagnosis of AF | up to 10 years | Rhythm control therapy: Use of antiarrhythmic drugs, electrical cardioversion, or catheter ablation for AF. |
| Time from initial diagnosis of AF to first rhythm control therapy | up to 10 years | Rhythm control therapy: Use of antiarrhythmic drugs, electrical cardioversion, or catheter ablation for AF. |
| Changes in oral anticoagulation from warfarin to a DOAC or vice versa, based on the reassessment of cardiac function and structure | up to 10 years | — |
| Changes in the class of antiarrhythmic drugs (AADs) prescribed, based on the reassessment of cardiac function and structure | up to 10 years | i.e., modification of Class Ic AAD to Class III AAD. Changes in antiarrhythmic drug therapy due solely to inadequate AF rate or rhythm control are not included. |
| Changes in heart failure medications resulting from reassessment of cardiac function and structure | up to 10 years | Initiation, dose escalation, or dose reduction of heart failure medication classes including beta-blockers, mineralocorticoid receptor antagonists (MRAs), renin-angiotensin-aldosterone system (RAAS) inhibitors or angiotensin receptor-neprilysin inhibitors (ARNIs), sodium-glucose cotransporter 2 inhibitors (SGLT2i), or other agents (e.g., ivabradine, vericiguat, hydralazine/nitrate |
| The proportion of patients maintaining sinus rhythm | up to 10 years | — |
| Quality of life assessed by European Quality of Life-5 Dimensions (EQ-5D) at baseline, 12 months, and 24 months | up to 10 years | EQ-5D scores range from 0 to 100, with higher scores indicating better health status. |
| NT-proBNP levels at baseline, 12 months, and 24 months | up to 10 years | — |
| Diagnostic performance of the AI-ECG algorithm for detecting cardiac functional and structural abnormalities | up to 10 years | Assessment of the AI-ECG algorithm's ability to detect functional and structural cardiac abnormalities. Performance metrics will include Accuracy, Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value. |
| Investigator satisfaction with the use of AI-ECG | up to 10 years | — |
Countries
South Korea
Contacts
CONTACTEue-Keun Choi, MD, PhD
PRINCIPAL_INVESTIGATOREue-Keun Choi, M.D. Ph.D.
Seoul National University Hospital
Outcome results
None listed