Atrial Fibrillation (AF)NCT07708818
An AI-ECG-Based Approach for Dynamic Assessment of Heart Failure Risk and Myocardial Recovery Following Atrial Fibrillation Ablation
An observational study of Atrial Fibrillation (AF) and Heart Failure With Mildly Reduced Ejection Fraction (HFmrEF), run by Ewha Womans University Mokdong Hospital at 1 site in South Korea.
Trial summary
Background Artificial intelligence-enabled electrocardiography (AI-ECG) has emerged as a promising digital biomarker for detecting latent myocardial dysfunction and predicting cardiovascular risk. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Atrial Fibrillation (AF), Heart Failure With Mildly Reduced Ejection Fraction (HFmrEF)
- How many people
- 1,000 participants
- Where
- 1 siteSouth Korea
- Study dates
- 1 Jan 2027to 31 Dec 2029
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The study population consists of adults with symptomatic paroxysmal or persistent atrial fibrillation and heart failure with mildly reduced ejection fraction (left ventricular ejection fraction 41-49%) who are scheduled to undergo first-time catheter ablation. Participants are prospectively enrolled at five tertiary referral centers and are additionally required to have at least one feature suggestive of latent heart failure substrate, including elevated natriuretic peptide levels, impaired global longitudinal strain, increased left atrial volume index, elevated E/e' ratio, or exertional intolerance. All participants undergo standardized longitudinal follow-up with serial 12-lead electrocardiography, echocardiography, biomarker assessment, and clinical evaluation for 12 months after catheter ablation.
Who may be able to join
- 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:
Show all 13Show fewer
- 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
Who cannot join
- 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
Show all 10Show fewer
- Active malignancy with life expectancy <1 year
- Inadequate electrocardiographic or echocardiographic image quality
- Pregnancy
- Inability or unwillingness to provide written informed consent
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
South Korea1 site
Ewha Womans University Mokdong Hospital
Seoul, 07804
Yeji Kim, PhD, +82-10-8680-9542, lexie6169@gmail.com
About this study
Official title: DYNAMIC-AF HF Study: An AI-ECG-Based Approach for Dynamic Assessment of Heart Failure Risk and Myocardial Recovery Following Atrial Fibrillation Ablation
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.
Read more
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.
- Keywords
- artificial intelligence, electrocardiography, digital biomarker, heart failure with mildly reduced ejection fraction, atrial fibrillation, catheter ablation
- Medical subject headings
- Atrial Fibrillation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| AF-HFmrEF Cohort | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in AI-derived Heart Failure Risk Score
Difference in the AI-enabled electrocardiography (AI-ECG)-derived heart failure risk score (continuous probability ranging from 0 to 1) between baseline and 12 months after first-time catheter ablation. Higher values indicate a greater predicted probability of underlying heart failure.
Measured: Baseline to 12 months after catheter ablation
Secondary outcomes (9)
Change in Left Ventricular Ejection Fraction
Absolute change in left ventricular ejection fraction measured by transthoracic echocardiography.
Measured: Baseline to 12 months after catheter ablation
Change in Global Longitudinal Strain
Change in left ventricular global longitudinal strain assessed by speckle-tracking echocardiography.
Measured: Baseline to 12 months after catheter ablation
Change in Left Atrial Volume Index
Change in left atrial volume index measured by transthoracic echocardiography.
Measured: Baseline to 12 months after catheter ablation
Change in E/e' Ratio
Change in echocardiographic estimate of left ventricular filling pressure.
Measured: Baseline to 12 months after catheter ablation
Change in NT-proBNP
Change in serum N-terminal pro-B-type natriuretic peptide concentration.
Measured: Baseline to 12 months after catheter ablation
Atrial Fibrillation Recurrence
Documented atrial fibrillation, atrial flutter, or atrial tachycardia lasting at least 30 seconds after the 3-month blanking period.
Measured: Up to 12 months after catheter ablation
Heart Failure Hospitalization
Hospitalization primarily related to worsening heart failure requiring medical treatment.
Measured: Up to 12 months after catheter ablation
Cardiovascular Hospitalization
Hospitalization due to cardiovascular causes including arrhythmia, heart failure, ischemic events, or procedure-related complications.
Measured: Up to 12 months after catheter ablation
All-cause Mortality
Death from any cause during study follow-up.
Measured: Up to 12 months after catheter ablation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Jul 2026
- Study start1 Jan 2027 (estimated)
- Primary completion31 Dec 2028 (estimated)
- Study completion31 Dec 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for Atrial Fibrillation (AF)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ewha Womans University Mokdong Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07708818
- Sponsor's protocol ID
- DYNAMIC-AF HF
- Status last verified
- Jul 2026
- First submitted
- 11 Jul 2026
- Last updated
- 20 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: The decision regarding sharing de-identified individual participant data has not yet been finalized. Data sharing will be considered after completion of the study, publication of the primary results, and in accordance with institutional policies, participant consent, and applicable ethical and regulatory requirements.
Publications
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.
PubMed 36711179Kwon 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.
PubMed 31074221Marrouche 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.
PubMed 29385358Van 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 developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2024 Sep 29;45(36):3314-3414. doi: 10.1093/eurheartj/ehae176. No abstract available.
PubMed 39210723Joglar 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 Committee Members. 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2024 Jan 2;149(1):e1-e156. doi: 10.1161/CIR.0000000000001193. Epub 2023 Nov 30.
PubMed 38033089Heidenreich 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 the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022 May 3;145(18):e895-e1032. doi: 10.1161/CIR.0000000000001063. Epub 2022 Apr 1.
PubMed 35363499Bozkurt 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, Vardeny O, Yamamoto K, Yancy C, Zhang J, Zieroth S. Universal Definition and Classification of Heart Failure: A Report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure. J Card Fail. 2021 Apr;27(4):387-413. doi: 10.1016/j.cardfail.2021.01.022. Epub 2021 Mar 1.
PubMed 33663906
Study at a glance
From the registry record, last updated by the sponsor on 20 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- DYNAMIC-AF HF Study: An AI-ECG-Based Approach for Dynamic Assessment of Heart Failure Risk and Myocardial Recovery Following Atrial Fibrillation Ablation
- ClinicalTrials.gov ID
- NCT07708818
- Acronym / sponsor ID
- DYNAMIC-AF HF
- Keywords
- artificial intelligence, electrocardiography, digital biomarker, heart failure with mildly reduced ejection fraction, atrial fibrillation, catheter ablation
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Ewha Womans University Mokdong HospitalUniversity, hospital or other
- Study start
- 1 Jan 2027 (estimated)
- Primary completion
- 31 Dec 2028 (estimated)
- Study completion
- 31 Dec 2029 (estimated)
- First posted
- 16 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| AF-HFmrEF Cohort | – | – |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of adults with symptomatic paroxysmal or persistent atrial fibrillation and heart failure with mildly reduced ejection fraction (left ventricular ejection fraction 41-49%) who are scheduled to undergo first-time catheter ablation. Participants are prospectively enrolled at five tertiary referral centers and are additionally required to have at least one feature suggestive of latent heart failure substrate, including elevated natriuretic peptide levels, impaired global longitudinal strain, increased left atrial volume index, elevated E/e' ratio, or exertional intolerance. All participants undergo standardized longitudinal follow-up with serial 12-lead electrocardiography, echocardiography, biomarker assessment, and clinical evaluation for 12 months after catheter ablation.
Key inclusion criteria (13 listed)
- 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
Key exclusion criteria (10 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Change in AI-derived Heart Failure Risk Score
Time frame: Baseline to 12 months after catheter ablation
Difference in the AI-enabled electrocardiography (AI-ECG)-derived heart failure risk score (continuous probability ranging from 0 to 1) between baseline and 12 months after first-time catheter ablation. Higher values indicate a greater predicted probability of underlying heart failure.
9 secondary outcomes
Change in Left Ventricular Ejection Fraction
Time frame: Baseline to 12 months after catheter ablation
Change in Global Longitudinal Strain
Time frame: Baseline to 12 months after catheter ablation
Change in Left Atrial Volume Index
Time frame: Baseline to 12 months after catheter ablation
Change in E/e' Ratio
Time frame: Baseline to 12 months after catheter ablation
Change in NT-proBNP
Time frame: Baseline to 12 months after catheter ablation
Atrial Fibrillation Recurrence
Time frame: Up to 12 months after catheter ablation
Heart Failure Hospitalization
Time frame: Up to 12 months after catheter ablation
Cardiovascular Hospitalization
Time frame: Up to 12 months after catheter ablation
All-cause Mortality
Time frame: Up to 12 months after catheter ablation
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Jul 2026.
- Background: PubMed 36711179Kwon 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.
- Background: PubMed 31074221Kwon 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.
- Background: PubMed 29385358Marrouche 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.
- Background: PubMed 39210723Van 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 developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2024 Sep 29;45(36):3314-3414. doi: 10.1093/eurheartj/ehae176. No abstract available.
- Background: PubMed 38033089Joglar 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 Committee Members. 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2024 Jan 2;149(1):e1-e156. doi: 10.1161/CIR.0000000000001193. Epub 2023 Nov 30.
- Background: PubMed 35363499Heidenreich 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 the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022 May 3;145(18):e895-e1032. doi: 10.1161/CIR.0000000000001063. Epub 2022 Apr 1.
- Background: PubMed 33663906Bozkurt 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, Vardeny O, Yamamoto K, Yancy C, Zhang J, Zieroth S. Universal Definition and Classification of Heart Failure: A Report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure. J Card Fail. 2021 Apr;27(4):387-413. doi: 10.1016/j.cardfail.2021.01.022. Epub 2021 Mar 1.
- Individual participant dataSharing planned: Undecided. The decision regarding sharing de-identified individual participant data has not yet been finalized. Data sharing will be considered after completion of the study, publication of the primary results, and in accordance with institutional policies, participant consent, and applicable ethical and regulatory requirements.
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ATRIAL APPENDAGE CLOSURE for ATRIAL FIBRILLATION, Atrial Fibrillation (AF)
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Atrial Fibrillation (AF) and Heart Failure With Mildly Reduced Ejection Fraction (HFmrEF), run by Ewha Womans University Mokdong Hospital at 1 site in South Korea.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 13 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 20 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in South Korea. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Yeji Kim, PhD (+82-10-8680-9542, lexie6169@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in AI-derived Heart Failure Risk Score (time frame: Baseline to 12 months after catheter ablation). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07708818, which also lists 7 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Jul 2026.