An AI-ECG-Based Approach for Dynamic Assessment of Heart Failure Risk and Myocardial Recovery Following Atrial Fibrillation Ablation

Официальное название

DYNAMIC-AF HF Study: An AI-ECG-Based Approach for Dynamic Assessment of Heart Failure Risk and Myocardial Recovery Following Atrial Fibrillation Ablation

Обзор

Background Artificial intelligence-enabled electrocardiography (AI-ECG) has emerged as a promising digital biomarker for detecting latent myocardial dysfunction and predicting cardiovascular risk. However, whether serial AI-derived risk estimates reflect myocardial recovery following therapeutic intervention remains unknown. Objective The DYNAMIC-AF HF Study aims to evaluate longitudinal changes in AI-ECG-derived heart failure (HF) risk after catheter ablation in patients with atrial fibrillation (AF) and heart failure with mildly reduced ejection fraction (HFmrEF), and to determine their association with conventional markers of reverse remodeling. Methods The DYNAMIC-AF HF Study is a prospective multicenter observational cohort study enrolling 1,000 patients with symptomatic AF and HFmrEF undergoing first-time catheter ablation. Eligible participants must have a left ventricular ejection fraction of 41-49% and at least one predefined HF-related feature suggestive of latent myocardial dysfunction. Serial 12-lead electrocardiograms, echocardiography, biomarker assessments, and clinical follow-up will be performed at baseline and at 3, 6, and 12 months. AI-based ECG analysis will generate continuous HF-risk scores, enabling construction of longitudinal AI-derived HF risk trajectories. The primary endpoint is the change in AI-derived HF risk from baseline to 12 months. Secondary endpoints include changes in left ventricular ejection fraction, global longitudinal strain, N-terminal pro-B-type natriuretic peptide levels, AF recurrence, HF hospitalization, and mortality. Conclusions This study will evaluate whether serial AI-ECG assessment can serve as a dynamic digital biomarker of myocardial recovery following AF ablation and support future AI-enabled monitoring and clinical decision-support strategies in cardiovascular care.

Первичные конечные точки

• Change in AI-derived Heart Failure Risk Score [Срок оценки: Baseline to 12 months after catheter ablation]

Вторичные конечные точки (9)

• Change in Left Ventricular Ejection Fraction [Срок оценки: Baseline to 12 months after catheter ablation]
• Change in Global Longitudinal Strain [Срок оценки: Baseline to 12 months after catheter ablation]
• Change in Left Atrial Volume Index [Срок оценки: Baseline to 12 months after catheter ablation]
• Change in E/e' Ratio [Срок оценки: Baseline to 12 months after catheter ablation]
• Change in NT-proBNP [Срок оценки: Baseline to 12 months after catheter ablation]
• Atrial Fibrillation Recurrence [Срок оценки: Up to 12 months after catheter ablation]
• Heart Failure Hospitalization [Срок оценки: Up to 12 months after catheter ablation]
• Cardiovascular Hospitalization [Срок оценки: Up to 12 months after catheter ablation]
• All-cause Mortality [Срок оценки: Up to 12 months after catheter ablation]

Критерии участия

Критерии включения

• Age ≥18 years
• Symptomatic paroxysmal or persistent atrial fibrillation
• Scheduled for first-time catheter ablation
• Left ventricular ejection fraction between 41% and 49% measured by transthoracic echocardiography within 3 months before ablation
• At least one analyzable sinus rhythm 12-lead electrocardiogram before ablation
• At least one latent heart failure substrate feature:

• Elevated NT-proBNP
• Increased left atrial volume index (>34 mL/m²)
• Average E/e' ≥14
• Reduced global longitudinal strain
• Mild pulmonary hypertension
• Exertional intolerance suggestive of early heart failure
• Ability to provide written informed consent

Критерии исключения

• Left ventricular ejection fraction ≤40%
• Previous atrial fibrillation catheter ablation
• Significant valvular heart disease requiring intervention
• Hypertrophic or infiltrative cardiomyopathy
• Acute coronary syndrome, coronary revascularization, or myocarditis within 3 months
• Severe renal dysfunction requiring dialysis
• Active malignancy with life expectancy <1 year
• Inadequate electrocardiographic or echocardiographic image quality
• Pregnancy
• Inability or unwillingness to provide written informed consent

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

South Korea · 1 центр

• Ewha Womans University Mokdong Hospital — Seoul

Публикации

• Kwon JM, Kim KH, Eisen HJ, Cho Y, Jeon KH, Lee SY, Park J, Oh BH. Artificial intelligence assessment for early detection of heart failure with preserved ejection fraction based on electrocardiographic features. Eur Heart J Digit Health. 2020 Dec 10;2(1):106-116. doi: 10.1093/ehjdh/ztaa015. eCollection 2021 Mar. PMID 36711179
• Kwon JM, Kim KH, Jeon KH, Kim HM, Kim MJ, Lim SM, Song PS, Park J, Choi RK, Oh BH. Development and Validation of Deep-Learning Algorithm for Electrocardiography-Based Heart Failure Identification. Korean Circ J. 2019 Jul;49(7):629-639. doi: 10.4070/kcj.2018.0446. Epub 2019 Mar 21. PMID 31074221
• Marrouche NF, Brachmann J, Andresen D, Siebels J, Boersma L, Jordaens L, Merkely B, Pokushalov E, Sanders P, Proff J, Schunkert H, Christ H, Vogt J, Bansch D; CASTLE-AF Investigators. Catheter Ablation for Atrial Fibrillation with Heart Failure. N Engl J Med. 2018 Feb 1;378(5):417-427. doi: 10.1056/NEJMoa1707855. PMID 29385358
• Van Gelder IC, Rienstra M, Bunting KV, Casado-Arroyo R, Caso V, Crijns HJGM, De Potter TJR, Dwight J, Guasti L, Hanke T, Jaarsma T, Lettino M, Lochen ML, Lumbers RT, Maesen B, Molgaard I, Rosano GMC, Sanders P, Schnabel RB, Suwalski P, Svennberg E, Tamargo J, Tica O, Traykov V, Tzeis S, Kotecha D; ESC Scientific Document Group. 2024 ESC Guidelines for the management of atrial fibrillation develope PMID 39210723
• Joglar JA, Chung MK, Armbruster AL, Benjamin EJ, Chyou JY, Cronin EM, Deswal A, Eckhardt LL, Goldberger ZD, Gopinathannair R, Gorenek B, Hess PL, Hlatky M, Hogan G, Ibeh C, Indik JH, Kido K, Kusumoto F, Link MS, Linta KT, Marcus GM, McCarthy PM, Patel N, Patton KK, Perez MV, Piccini JP, Russo AM, Sanders P, Streur MM, Thomas KL, Times S, Tisdale JE, Valente AM, Van Wagoner DR; Peer Review Committe PMID 38033089
• Heidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, Deswal A, Drazner MH, Dunlay SM, Evers LR, Fang JC, Fedson SE, Fonarow GC, Hayek SS, Hernandez AF, Khazanie P, Kittleson MM, Lee CS, Link MS, Milano CA, Nnacheta LC, Sandhu AT, Stevenson LW, Vardeny O, Vest AR, Yancy CW; ACC/AHA Joint Committee Members. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of t PMID 35363499
• Bozkurt B, Coats AJ, Tsutsui H, Abdelhamid M, Adamopoulos S, Albert N, Anker SD, Atherton J, Bohm M, Butler J, Drazner MH, Felker GM, Filippatos G, Fonarow GC, Fiuzat M, Gomez-Mesa JE, Heidenreich P, Imamura T, Januzzi J, Jankowska EA, Khazanie P, Kinugawa K, Lam CSP, Matsue Y, Metra M, Ohtani T, Francesco Piepoli M, Ponikowski P, Rosano GMC, Sakata Y, SeferoviC P, Starling RC, Teerlink JR, Varden PMID 33663906

Идентификаторы

NCT: NCT07708818 · DYNAMIC-AF HF

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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