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AI could predict strokes before they happen in heart patients

NCT ID NCT07441759

Knowledge-focused Sponsor: Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 27, 2026 · Last updated Jun 27, 2026

Summary

This study will test whether an artificial intelligence (AI) tool can better predict stroke risk in 1,000 people aged 65-95 with atrial fibrillation, compared to current methods. The AI analyzes health records and heart data to identify high-risk individuals early. The goal is to prevent strokes and heart attacks by guiding earlier treatment.

What this could mean

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

Active substance
AI-driven risk prediction model (MATHIAS strategy)
What this could lead to
If successful, this could lead to a more accurate way to predict stroke risk in people with atrial fibrillation, potentially preventing strokes and saving healthcare costs.
What could go wrong
This is a model-based evaluation, not a clinical trial testing a treatment. The AI tool may not work as well in real-world settings, and the study hasn't started recruiting yet.

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 1,000 people

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

Expected to start

Jul 2026

An estimate. Start dates often move.

Expected to finish

Dec 2028

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

This study will use routinely collected data from the SAP Terres de l'Ebre primary-care database (Catalonia, Spain) covering 178,112 inhabitants (49.6% women) managed in 11 primary-care health centers. The region is characterized by advanced population aging \[19\] (aging index 159.5 vs 131.3 in Catalonia and 118.4 in Spain) and lower average per-capita income \[20\] (77.4% of the Catalan mean). Adults aged 65-95 years without prior AF and with active records in the HCC3/CMBD systems at baseline. This cohort is characterized by multimorbidity and high-predicted risk of AF and related complications reflecting patients typically managed in primary care in European health systems, providing a real-world setting with high cardiovascular burden and constrained resources.

Ages

65 to 95 years

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

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 (PREFATE study): assessed at baseline * Adults aged 65-95 years without prior AF and at High risk of AF, according to the risk score validated in the AFRICAT (Atrial Fibrilation Research in CATalonia) study. This scale considers the following variables for risk calculation: sex, age, weight, cardiac rate and CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 (doubled), diabetes mellitus, prior stroke or transient ischemic attack (doubled), vascular disease, age 65-74, female) score. * with active records in the HCC3/CMBD systems * CHA2DS2-VASc score≥2. * Ability to use a smart phone (or at least the caregiver). Exclusion Criteria: Patients with the following conditions will be excluded (exclusion criteria): * Previous diagnosis of AF. * Previous diagnosis of stroke. * Severe cognitive impairment, with a score on the Global Deterioration Scale (GDS)≥3. * Severe functional impairment, with a Barthel score ≤60, or modified Rankin score≥4. * Active anticoagulant treatment at the inclusion. * Vital prognosis less than 1 year. * Pacemaker carriers.

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Conditions

The condition(s) this trial relates to.

atrial fibrillation cardiovascular disorder stroke disorder

As listed by the trial registrant

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

Artificial intelligence (AI) Atrial fibrillation (AF) Cardio vascular disease Cardio-cerebrovascular disease Cost-effectiveness analysis Electronic health records MACE Quality-adjusted life-years Thromboembolic risk

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

  • EAP Tortose est. Servei d'Atencio Primaria i Comunitària. Institut Catala de la Salit

    Tortosa, Tarragona, 43500, Spain

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