Functional And STructural Assesment of the Heart by Artificial Intelligence-enabled Electrocardiogram for the Management of Atrial Fibrillation
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 1,724
- 试验地点
- 28
- 主要终点
- Composite of all-cause Mortality, Stroke, CV Hospitalization, and AAD-Related SAEs
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Treatment
- 盲法
- None
入排标准
- 年龄范围
- 19 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
- •Patients for whom an initial or repeat transthoracic echocardiographic evaluation is clinically indicated.
- •A CHA₂DS₂-VA score of ≥
- •Aged ≥19 years at the time of enrollment and able to provide written informed consent voluntarily.
排除标准
- •Transthoracic echocardiography performed within the past 6 months.
- •Ventricular rate ≥110 beats per minute during atrial fibrillation.
- •Atrial fibrillation due to a reversible cause.
- •New York Heart Association (NYHA) functional class IV or European Heart Rhythm Association (EHRA) class IV symptoms.
- •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).
- •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).
- •History of prior cardiac surgery.
- •History of acute coronary syndrome or coronary revascularization within the past 90 days.
- •History of intracardiac thrombosis or systemic thromboembolism within the past 90 days.
- •History of transient ischemic attack, ischemic stroke, or intracranial hemorrhage within the past 90 days.
- •History of ventricular tachycardia or ventricular fibrillation.
- •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).
- •Severe chronic kidney disease (stage V), requiring or imminently requiring dialysis.
- •Contraindication to anticoagulation therapy.
- •Pregnancy, breastfeeding, or planning pregnancy during the study period.
- •Life expectancy of less than 1 year.
- •Current participation in another randomized clinical trial.
研究组 & 干预措施
Transthoracic Echocardiography-Guided Assessment Group (TTE group)
Participants in this group will receive a standard-of-care evaluation. Cardiac function and structure will be evaluated using Transthoracic Echocardiography (TTE) regardless of ECG findings. Management (anticoagulation, rate/rhythm control) is initiated or adjusted based on TTE parameters. TTE is performed at least once annually during follow-up.
干预措施: Transthoracic Echocardiography-Guided Assessment (Diagnostic Test)
AI-ECG-Guided Assessment Group (AI-ECG group)
Participants in this group will undergo a conditional diagnostic strategy. Cardiac function and structure are initially screened using an AI-enabled ECG.
- Predicted Normal: TTE is withheld. Management is based on clinical evaluation and AI-ECG results.
- Predicted Abnormal: Verification TTE is performed. Management is guided by TTE findings.
Safety Note: Protocol-defined rescue TTE is permitted at the investigator's discretion for worsening symptoms or prior to procedures (cardioversion, ablation), regardless of AI-ECG results.
干预措施: Artificial intelligence-enabled electrocardiography (Diagnostic Test)
结局指标
主要结局
Composite of all-cause Mortality, Stroke, CV Hospitalization, and AAD-Related SAEs
时间窗: 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.
次要结局
- Investigator satisfaction with the use of AI-ECG(up to 10 years)
- The proportion of patients maintaining sinus rhythm(up to 10 years)
- All-cause mortality(up to 10 years)
- Stroke or systemic thromboembolism(up to 10 years)
- Heart failure worsening(up to 10 years)
- Hospitalization due to acute coronary syndrome(up to 10 years)
- Serious adverse events related to antiarrhythmic drug therapy(up to 10 years)
- Proportion of patients receiving rhythm control therapyc after the initial diagnosis of AF(up to 10 years)
- Time from initial diagnosis of AF to first rhythm control therapy(up to 10 years)
- 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)
- Changes in heart failure medications resulting from reassessment of cardiac function and structure(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)
- 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)
- Investigator satisfaction with AI-ECG use at 12 months and 24 months reported by a self-reported questionnaire(up to 10 years)
研究者
Eue-Keun Choi
Professor
Seoul National University Hospital