Recruiting

Machine Learning

Sponsor:

Stanford University

Code:

NCT05371405

Conditions

Atrial Fibrillation

Arrhythmias, Cardiac

Eligibility Criteria

Sex: All

Age: 22 - 70+

Healthy Volunteers: Not accepted

Study Details

Brief summary:

Atrial fibrillation is a serious public health issue that affects over 5 million Americans (Miyazaka, Circulation 2006) in whom it may cause skipped beats, dizziness, stroke and even death. Therapy for AF is currently suboptimal, in part because AF represents several disease states of which few have been delineated or used to successfully guide management. This study seeks to clarify this delineation of AF types using machine learning (ML).

Conditions

Atrial Fibrillation

Arrhythmias, Cardiac

Study ID

NCT05371405

Start date

Feb 12, 2020

Status verified date

Nov, 2025

Completion date

Dec, 2027

Anticipated

Primary completion date

Dec, 2026

Anticipated

Eligibility Criteria

Eligibility Criteria

Sex: All

Age: 22 - 70+

Healthy Volunteers: Not accepted

Inclusion Criteria:

  • undergoing ablation at Stanford of (a) paroxysmal AF (self-terminates < 7 days), or (b) persistent AF (requires cardioversion to terminate).
  • Per our clinical practice and guidelines (Calkins et al, Heart Rhythm 2012), patients will have failed or be intolerant of ≥ 1 anti-arrhythmic drug.

Exclusion Criteria:

  • active coronary ischemia or decompensated heart failure
  • atrial or ventricular clot on trans-esophageal echocardiography
  • pregnancy (to minimize fluoroscopic exposure)
  • inability or unwillingness to provide informed consent
  • rheumatic valve disease (results in a unique AF phenotype)
  • thrombotic disease or venous filters

Study Design

Enrollment

120 participants

Anticipated

Interventions and Outcome Measures

Primary outcome measure

  • Machine Learning Prediction of Ablation Outcome [ Time Frame: 1 year. ]

Central Contacts and Locations

Central contacts

Sanjiv Narayan, MD

650-724-1850sanjiv1@stanford.edu

Kathleen Mills, BA

kmills2@stanford.edu

Locations

Stanford University

Recruiting

Stanford, California, United States, 94305

Contacts

Sanjiv Narayan, MD

(650) 724-1850sanjiv1@stanford.edu

Kathleen Mills, BA

kmills2@stanford.edu

More Information

Sponsor

Stanford University

Last update posted

Nov 14, 2025

Last verified

Nov, 2025

Keywords

  • machine learning
  • ablation
  • atrial fibrillation

Trial information was received from ClinicalTrials.gov and was last updated on 2026-09-10. This information was provided to ClinicalTrials.gov by Stanford University on 2025-11-14.