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AI could help ER doctors spot the cause of chest pain faster

NCT ID NCT06196307

Knowledge-focused Sponsor: Xiao-nan He 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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study is testing whether machine learning can help doctors quickly and accurately figure out what is causing chest pain in emergency patients. Researchers will collect data from 10,000 adults with non-traumatic chest pain, including test results and medical history. The goal is to create a tool that reduces misdiagnosis and speeds up treatment decisions.

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 a machine-learning tool that helps doctors quickly and accurately diagnose the cause of chest pain in the emergency room.
What could go wrong
This is an observational study, not a treatment trial. The model may not work as well in real-world settings or for all types of chest pain.

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 10,000 people

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

Started

Aug 2022

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

The study population included patients admitted to the chest pain center of the pilot hospital from August 2022 to December 2027 with chest pain (including tingling, burning pain, pressure, tightness, heartburn and similar discomfort) as the main manifestations. Screening of patients with chest pain is intended from the following sources: 1. outpatients with chest pain; 2. outpatients with a history of cardiovascular disease; 3. patients from other departments of the hospital referred to the cardiology outpatient clinic due to acute chest pain.

Ages

18 years and older

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: 1. Age ≥ 18 years 2. Symptom onset or worsening within 24 hours before presentation, with a chief complaint of acute chest pain meeting the broad definition of chest pain (2021 AHA) 3. Presentation to the emergency department, with a clinical diagnosis consistent with non-traumatic chest pain 4. Signed informed consent Exclusion Criteria: 1. traumatic chest pain 2. systemic pain caused by malignant tumors or rheumatic diseases involving the chest 3. Patients were lost to follow-up

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Conditions

The condition(s) this trial relates to.

Chest Pain

As listed by the trial registrant

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

Chest pain

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

  • Xiaonan He

    RECRUITING

    Beijing, Chaoyang, 100029, China

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