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AI could predict which heart ablations work best

NCT ID NCT05371405

Knowledge-focused Sponsor: Stanford University Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now This study
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 24, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This Stanford study is testing whether machine learning can help predict which patients with atrial fibrillation will benefit from a heart ablation procedure. Researchers will collect data from 120 people undergoing ablation and use it to train an algorithm that forecasts success. The goal is to personalize treatment and identify the best targets for ablation.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this could lead to more personalized and effective ablation procedures for atrial fibrillation patients.
What could go wrong
This is an early-stage observational study focused on developing a prediction tool, not testing a new treatment. The algorithm may not improve outcomes in practice.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 120 people

The number the study aims to enrol. It can still change while the study runs.

Started

Feb 2020

Expected to finish

Dec 2027

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Subjects will be men and women of any ethnicity aged 22-80 years 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.

Ages

22 to 80 years

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

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

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Conditions

The condition(s) this trial relates to.

Arrhythmias, Cardiac atrial fibrillation cardiac rhythm disease

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Arrhythmias, cardiac Atrial fibrillation

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Stanford University

    RECRUITING

    Stanford, California, 94305, United States

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