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Atrial FibrillationCOMPARE_AFNCT02997254

COMparison of Physiological Algorithms for Real-time Evaluation of Atrial Fibrillation

An observational study of Atrial Fibrillation and Abnormal Heart Rhythms, run by Stanford University at 1 site in United States.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts
Official record
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Trial summary

This is a cohort study to evaluate algorithms for mapping atrial fibrillation by mapping atrial structure and mapping electrical activity to detect physiologically important areas. Read more about this study

Who is it for?
Ages 21 to 90 years
Conditions the study is for
Atrial Fibrillation, Abnormal Heart Rhythms
How many people
1,000 participants
Where
1 siteUnited States
Study dates
1 Dec 2016to 30 Jun 2027
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 21 to 90 years
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: The investigators will study adults aged 21-90 years who have undergone electrophysiology study for ablation of Atrial Fibrillation. De-identified datasets will be made available for comparisons of mapping approaches.

Who may be able to join

  • aged 21-80 yrs who underwent electrophysiology study for ablation of Atrial Fibrillation

Who cannot join

  • Poor data quality of recordings of AF

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

Sanjiv M Narayan, MD, PhD contact

(650) 723-9363

sanjiv1@stanford.edu

Kathleen C Mills, BA contact

(650) 723-9363

kmills2@stanford.edu

United States1 site, 1 recruiting

  • Stanford University

    Stanford, California, 94305

    Gerri O'Riordan, RN, 650/725-5597, GORiordan@stanfordhealthcare.org

    Recruiting

Other trials in United States

About this study

This is a cohort study to evaluate algorithms for mapping atrial fibrillation by mapping atrial structure and mapping electrical activity to detect physiologically important areas.

A key innovation of the observation study is to assess tracking of physiological activity in AF, in relation to tissue activity (MAP recordings), and in relation to AF waves of activity.

This observational work extends prior studies that focused on focal and rotational activity, dispersion of electrical activity, low voltage activity and others.

Read the detailed description

In this study, the investigators will compare mapping approaches for atrial fibrillation ablation.

First, investigators will compare approaches to map atrial structure from collected computed tomography (CT) scans or magnetic resonance imaging (MRI) scans acquired routinely in patients undergoing ablation for atrial fibrillation. Imaging will be acquired from a variety of clinically approved

Second, investigators will compare approaches to analyze electrograms collected routinely at clinical electrophysiology study (EPS) in patients undergoing ablation for atrial fibrillation. Electrograms will be recorded from a variety of clinically approved catheters under standard of care conditions, and will be analyzed to better understand the mechanisms for atrial fibrillation and its relationship to outcomes. Electrograms include unipolar recordings, bipolar recordings and, monophasic action potential recordings using FDA-cleared catheters.

The investigators anticipate analyzing data from 1000 patients from inception of the study.

Keywords
atrial fibrillation, ablation, abnormal heart rhythm
Medical subject headings
Atrial Fibrillation, Arrhythmias, Cardiac

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Diagnostic Accuracy

    Comparing electrogram analysis systems to diagnose sites of importance in Atrial Fibrillation

    Measured: At the time of procedure

  2. Diagnostic Accuracy

    Comparing algorithms to segment atrial structures from computed tomography or Magnetic resonance images.

    Measured: At time of procedure.

Secondary outcomes (1)

  1. Analysis Time

    Comparing time required to segment atrial structures from computed tomography or magnetic resonance images.

    Measured: At time of procedure.

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted20 Dec 2016 (estimated)
  2. Study start1 Dec 2016
  3. Primary completion31 Dec 2026 (estimated)
  4. Study completion30 Jun 2027 (estimated)

Resources

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
Retrospective
Enrolment
1,000 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT02997254
Sponsor's protocol ID
COMPARE_AF
Acronym
COMPARE_AF
Status last verified
Nov 2025
First submitted
12 Dec 2016
Last updated
14 Nov 2025
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • Alhusseini M, Vidmar D, Meckler GL, Kowalewski CA, Shenasa F, Wang PJ, Narayan SM, Rappel WJ. Two Independent Mapping Techniques Identify Rotational Activity Patterns at Sites of Local Termination During Persistent Atrial Fibrillation. J Cardiovasc Electrophysiol. 2017 Jun;28(6):615-622. doi: 10.1111/jce.13177. Epub 2017 Mar 20.

    PubMed 28185348

  • Alhusseini MI, Abuzaid F, Rogers AJ, Zaman JAB, Baykaner T, Clopton P, Bailis P, Zaharia M, Wang PJ, Rappel WJ, Narayan SM. Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation: Machine Learning of Atrial Fibrillation. Circ Arrhythm Electrophysiol. 2020 Aug;13(8):e008160. doi: 10.1161/CIRCEP.119.008160. Epub 2020 Jul 6.

    PubMed 32631100

  • Tang S, Razeghi O, Kapoor R, Alhusseini MI, Fazal M, Rogers AJ, Rodrigo Bort M, Clopton P, Wang PJ, Rubin DL, Narayan SM, Baykaner T. Machine Learning-Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes. Circ Arrhythm Electrophysiol. 2022 Aug;15(8):e010850. doi: 10.1161/CIRCEP.122.010850. Epub 2022 Jul 22.

    PubMed 35867397

  • Svennberg E, Han JK, Caiani EG, Engelhardt S, Ernst S, Friedman P, Garcia R, Ghanbari H, Hindricks G, Man SH, Millet J, Narayan SM, Ng GA, Noseworthy PA, Tjong FVY, Ramirez J, Singh JP, Trayanova N, Duncker D, Tfelt Hansen J, Barker J, Casado-Arroyo R, Chatterjee NA, Conte G, Diederichsen SZ, Linz D, Mahtani AU, Zorzi A. State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology. Europace. 2025 May 7;27(5):euaf071. doi: 10.1093/europace/euaf071.

    PubMed 40163651

  • Armoundas AA, Narayan SM, Arnett DK, Spector-Bagdady K, Bennett DA, Celi LA, Friedman PA, Gollob MH, Hall JL, Kwitek AE, Lett E, Menon BK, Sheehan KA, Al-Zaiti SS; American Heart Association Institute for Precision Cardiovascular Medicine; Council on Cardiovascular and Stroke Nursing; Council on Lifelong Congenital Heart Disease and Heart Health in the Young; Council on Cardiovascular Radiology and Intervention; Council on Hypertension; Council on the Kidney in Cardiovascular Disease; and Stroke Council. Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association. Circulation. 2024 Apr 2;149(14):e1028-e1050. doi: 10.1161/CIR.0000000000001201. Epub 2024 Feb 28.

    PubMed 38415358

  • Narayan SM, Wan EY, Andrade JG, Avari Silva JN, Bhatia NK, Deneke T, Deshmukh AJ, Chon KH, Erickson L, Ghanbari H, Noseworthy PA, Pathak RK, Roelle L, Seiler A, Singh JP, Srivatsa UN, Trela A, Tsiperfal A, Varma N, Yousuf OK. Visions for digital integrated cardiovascular care: HRS Digital Health Committee perspectives. Cardiovasc Digit Health J. 2024 Feb 24;5(2):37-49. doi: 10.1016/j.cvdhj.2024.02.003. eCollection 2024 Apr. No abstract available.

    PubMed 38765620

  • Armoundas AA, Ahmad FS, Bennett DA, Chung MK, Davis LL, Dunn J, Narayan SM, Slotwiner DJ, Wiley KK Jr, Khera R; American Heart Association Data Science and Precision Medicine Committee of the Council on Genomic and Precision Medicine and Council on Clinical Cardiology; Council on Cardiopulmonary, Critical Care, Perioperative and Resuscitation; Council on Cardiovascular and Stroke Nursing; Council on Lifestyle and Cardiometabolic Health; Council on Peripheral Vascular Disease; Council on Quality of Care and Outcomes Research; and Stroke Council. Data Interoperability for Ambulatory Monitoring of Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circ Genom Precis Med. 2024 Jun;17(3):e000095. doi: 10.1161/HCG.0000000000000095. Epub 2024 May 23.

    PubMed 38779844

  • de Groot NMS, Kleber A, Narayan SM, Ciaccio EJ, Doessel O, Bernus O, Berenfeld O, Callans D, Fedorov V, Hummel J, Haissaguerre M, Natale A, Trayanova N, Spector P, Vigmond E, Anter E. Atrial fibrillation nomenclature, definitions, and mechanisms: Position paper from the international Working Group of the Signal Summit. Heart Rhythm. 2025 Jun;22(6):1480-1491. doi: 10.1016/j.hrthm.2024.11.012. Epub 2024 Nov 17.

    PubMed 39561931

  • Goldberger JJ, Mitrani RD, Zaatari G, Narayan SM. Mechanistic Insights From Trials of Atrial Fibrillation Ablation: Charting a Course for the Future. Circ Arrhythm Electrophysiol. 2024 Aug;17(8):e012939. doi: 10.1161/CIRCEP.124.012939. Epub 2024 Jul 23.

    PubMed 39041221

  • Sillett C, Razeghi O, Baptiste TMG, Lee AWC, Solis Lemus JA, Rodero C, Roney CH, Feng R, Ganesan P, Chang HJ, Clopton P, Linton N, Rajani R, Rogers AJ, Narayan SM, Niederer SA. Identification of atrial myopathy and atrial fibrillation recurrence after ablation using 3D left atrial phasic strain from retrospective gated computed tomography. Eur Heart J Imaging Methods Pract. 2025 Mar 6;3(1):qyaf027. doi: 10.1093/ehjimp/qyaf027. eCollection 2025 Jan.

    PubMed 40171523

  • Ganesan P, Deb B, Feng R, Rodrigo M, Ruiperez-Campillo S, Rogers AJ, Clopton P, Wang PJ, Zeemering S, Schotten U, Rappel WJ, Narayan SM. Quantifying a spectrum of clinical response in atrial tachyarrhythmias using spatiotemporal synchronization of electrograms. Europace. 2023 May 19;25(5):euad055. doi: 10.1093/europace/euad055.

    PubMed 36932716

  • Feng R, Deb B, Ganesan P, Tjong FVY, Rogers AJ, Ruiperez-Campillo S, Somani S, Clopton P, Baykaner T, Rodrigo M, Zou J, Haddad F, Zahari M, Narayan SM. Segmenting computed tomograms for cardiac ablation using machine learning leveraged by domain knowledge encoding. Front Cardiovasc Med. 2023 Oct 2;10:1189293. doi: 10.3389/fcvm.2023.1189293. eCollection 2023.

    PubMed 37849936

  • Ganesan P, Pedron M, Feng R, Rogers AJ, Deb B, Chang HJ, Ruiperez-Campillo S, Srivastava V, Brennan KA, Giles WR, Baykaner T, Clopton P, Wang PJ, Schotten U, Krummen DE, Narayan SM. Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning. Circ Arrhythm Electrophysiol. 2025 Feb;18(2):e012860. doi: 10.1161/CIRCEP.124.012860. Epub 2025 Feb 10.

    PubMed 39925268

  • Narayan SM, Krummen DE, Shivkumar K, Clopton P, Rappel WJ, Miller JM. Treatment of atrial fibrillation by the ablation of localized sources: CONFIRM (Conventional Ablation for Atrial Fibrillation With or Without Focal Impulse and Rotor Modulation) trial. J Am Coll Cardiol. 2012 Aug 14;60(7):628-36. doi: 10.1016/j.jacc.2012.05.022. Epub 2012 Jul 18.

    PubMed 22818076

  • Narayan SM, Krummen DE, Enyeart MW, Rappel WJ. Computational mapping identifies localized mechanisms for ablation of atrial fibrillation. PLoS One. 2012;7(9):e46034. doi: 10.1371/journal.pone.0046034. Epub 2012 Sep 26.

    PubMed 23049929

Questions about this trial

What is this clinical trial studying?

An observational study of Atrial Fibrillation and Abnormal Heart Rhythms, run by Stanford University at 1 site in United States.

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 1 inclusion and 1 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: looking for participants now, as of the sponsor's last update on 14 Nov 2025. 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 United States. 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 Sanjiv M Narayan, MD, PhD ((650) 723-9363, sanjiv1@stanford.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Diagnostic Accuracy (time frame: At the time of procedure). The study lists 2 primary outcomes in all. 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 NCT02997254, which also lists 21 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 14 Nov 2025.

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