Chest PainALERTNCT06493175
The Application of Large Language Model in Emergency Chest Pain Triage
A study testing Application of large language model in emergency chest pain triage. and According to the normal procedures to receive medical treatment in people with Chest Pain, run by Peking University Third Hospital at 1 site in China.
Trial summary
This study will evaluate the accuracy and efficiency of large language model in emergency triage. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Chest Pain
- What is being tested?
- Application of large language model in emergency chest pain triage. and According to the normal procedures to receive medical treatment
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,189 participants
- Where
- 1 siteChina
- Study dates
- 20 Dec 2023to 20 Aug 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- All patients with chest pain entered the emergency triage procedure.
- patients aged 18 and above.
Who cannot join
- Patients with severe cognitive impairment or inability to communicate.
- There are patients who have been explicitly referred to specific departments (for example, some of the 120 transfer patients, who may go directly to the green channel) .
- Patients with unstable vital signs .
- Patients with potential medical problems.
- Is participating in other clinical trials.
- Failure to follow test procedures.
- Those who refuse to sign the informed consent form.
Trial locations and contacts
1 site in 1 country.
About this study
This study will evaluate the accuracy and efficiency of large language model in emergency triage.
Read the detailed description
The study is to evaluate the value of large language model in emergency triage, their accuracy and efficiency were evaluated and compared with traditional triage. To explore whether the model can effectively reduce the workload of medical staff, while improving the speed and quality of triage. In addition, the ability of the model to predict serious medical events such as acute heart events and strokes was evaluated. It also included surveys of patients; acceptance and satisfaction with the use of the artificial intelligence-assisted triage system. Analyze the economic benefits of adopting this technology, including cost saving and optimal allocation of resources.
- Conditions
- Chest Pain
- Being tested
- Application of large language model in emergency chest pain triage., According to the normal procedures to receive medical treatment
- Keywords
- large language model, Chest Pain
- Medical subject headings
- Chest Pain
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Application of large language model in emergency chest pain triage.Diagnostic test
The large language model MedGuide-V5 is able to quickly extract key information from a patients description, and by analyzing these descriptions, it provides physicians with a possible initial diagnosis to help them quickly prioritize the treatment of patients.
According to the normal procedures to receive medical treatmentDiagnostic test
After the artificial intelligence system evaluation, the patients will receive the diagnosis and treatment according to the normal procedure. The overall time of artificial triage, the triage of patients, and other data will be recorded. Patient visits should not be delayed by the use of artificial intelligence systems for evaluation.
| Study group | Role | What they receive |
|---|---|---|
| Large Language Model Diagnostic | Experimental | Patients interacted with the large-language model triage system MedGuide-V5 during the waiting period before or after routine triage in the emergency department. During this phase, MedGuide-V5 will automatically record data and metrics during communication with patients. Receives: Diagnostic Test: Application of large language model in emergency chest pain triage. |
| Routine diagnostic and therapeutic procedure | Active comparator | After the artificial intelligence system evaluation, the patients will receive the diagnosis and treatment according to the normal procedure. The overall time of artificial triage, the triage of patients, and other data will be recorded. Patient visits should not be delayed by the use of artificial intelligence systems for evaluation. Receives: Diagnostic Test: According to the normal procedures to receive medical treatment |
What is being measured
The primary outcome is the main question the study is designed to answer.
The Diagnostic Accuracy Rate of MedGuide-V5
To assess the consistency of the diagnosis of chest pain made by physicians with the assistance of large language models with the actual diagnosis made by patients after all examinations were completed.
Measured: through study completion, an average of 10 months
Secondary outcomes (3)
The Satisfaction of Medical Personnel
To evaluate the satisfaction and acceptance of medical personnel with the use of large language models in assisting triage systems through methods such as questionnaire surveys. The name of this questionnaire is: Researcher Evaluation Form, with scores ranging from 1 to 10. The higher the score, the more helpful the large language model is to researchers.
Measured: during evaluation
Medical Personnel Treatment Plan Adjustment Rate
The number of times medical personnel adjust treatment plans after receiving feedback from MedGuide V5's results and referring to the suggestions provided by the large language model.
Measured: during evaluation
Emergency Department Revisit Rate within 30 Days
Evaluate the occurrence of patients revisiting the emergency department or being readmitted within 30 days after large language model-assisted triage and traditional triage.
Measured: during evaluation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jul 2024
- Study start20 Dec 2023
- Primary completion20 Aug 2026
- Study completion20 Aug 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Chest PainStudies of the same condition, open and under way.
- More trials run by Peking University Third HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 1,189 participants (actual)
Sponsor and investigators
- Lead sponsor
- Peking University Third Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Beijing Friendship Hospital
- Responsible party
- Principal investigator, Tang Yida, Peking University Third Hospital
- Investigators
- Yi-Da Tang, MD, PhD, Principal investigator, Peking University Third HospitalWen-Yao Wang, MD, PhD, Principal investigator, Peking University Third Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06493175
- Sponsor's protocol ID
- M2023828
- Acronym
- ALERT
- Status last verified
- Aug 2026
- First submitted
- 22 Dec 2023
- Last updated
- 24 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Wang X, Wang W, Li L, Wang J, Yan X, Li PP, Lv J, Yu C, Liu D, Shao C, Chen J, Zhang K, Xu H, Wang G, Zheng M, Miao M, Xin S, Wu C, Wu Y, Luo H, Meng X. Large language models for acute coronary syndrome triage at first medical contact in emergency departments. NPJ Digit Med. 2026 Jun 17. doi: 10.1038/s41746-026-02904-y. Online ahead of print.
PubMed 42310091
Study at a glance
From the registry record, last updated by the sponsor on 24 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Application of Large Language Model in Emergency Chest Pain Triage
- ClinicalTrials.gov ID
- NCT06493175
- Acronym / sponsor ID
- ALERT / M2023828
- Conditions
- Chest Pain
- Keywords
- large language model, Chest Pain
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 1,189 participants (actual)
- Lead sponsor
- Peking University Third HospitalUniversity, hospital or other
- Collaborators
- Beijing Friendship Hospital
- Study start
- 20 Dec 2023 (actual)
- Primary completion
- 20 Aug 2026 (actual)
- Study completion
- 20 Aug 2026 (actual)
- First posted
- 9 Jul 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study will evaluate the accuracy and efficiency of large language model in emergency triage.
Detailed description
The study is to evaluate the value of large language model in emergency triage, their accuracy and efficiency were evaluated and compared with traditional triage. To explore whether the model can effectively reduce the workload of medical staff, while improving the speed and quality of triage. In addition, the ability of the model to predict serious medical events such as acute heart events and strokes was evaluated. It also included surveys of patients; acceptance and satisfaction with the use of the artificial intelligence-assisted triage system. Analyze the economic benefits of adopting this technology, including cost saving and optimal allocation of resources.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Large Language Model Diagnostic | Experimental | Diagnostic Test: Application of large language model in emergency chest pain triage.Patients interacted with the large-language model triage system MedGuide-V5 during the waiting period before or after routine triage in the emergency department. During this phase, MedGuide-V5 will automatically record data and metrics during communication with patients. |
| Routine diagnostic and therapeutic procedure | Active comparator | Diagnostic Test: According to the normal procedures to receive medical treatmentAfter the artificial intelligence system evaluation, the patients will receive the diagnosis and treatment according to the normal procedure. The overall time of artificial triage, the triage of patients, and other data will be recorded. Patient visits should not be delayed by the use of artificial intelligence systems for evaluation. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- All patients with chest pain entered the emergency triage procedure.
- patients aged 18 and above.
Key exclusion criteria (7 listed)
- Patients with severe cognitive impairment or inability to communicate.
- There are patients who have been explicitly referred to specific departments (for example, some of the 120 transfer patients, who may go directly to the green channel) .
- Patients with unstable vital signs .
- Patients with potential medical problems.
- Is participating in other clinical trials.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Application of large language model in emergency chest pain triage.The large language model MedGuide-V5 is able to quickly extract key information from a patients description, and by analyzing these descriptions, it provides physicians with a possible initial diagnosis to help them quickly prioritize the treatment of patients. | Diagnostic test | Large Language Model Diagnostic |
| According to the normal procedures to receive medical treatmentAfter the artificial intelligence system evaluation, the patients will receive the diagnosis and treatment according to the normal procedure. The overall time of artificial triage, the triage of patients, and other data will be recorded. Patient visits should not be delayed by the use of artificial intelligence systems for evaluation. | Diagnostic test | Routine diagnostic and therapeutic procedure |
Primary outcome
The Diagnostic Accuracy Rate of MedGuide-V5
Time frame: through study completion, an average of 10 months
To assess the consistency of the diagnosis of chest pain made by physicians with the assistance of large language models with the actual diagnosis made by patients after all examinations were completed.
3 secondary outcomes
The Satisfaction of Medical Personnel
Time frame: during evaluation
Medical Personnel Treatment Plan Adjustment Rate
Time frame: during evaluation
Emergency Department Revisit Rate within 30 Days
Time frame: during evaluation
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Aug 2026.
- Derived from this study: PubMed 42310091Wang X, Wang W, Li L, Wang J, Yan X, Li PP, Lv J, Yu C, Liu D, Shao C, Chen J, Zhang K, Xu H, Wang G, Zheng M, Miao M, Xin S, Wu C, Wu Y, Luo H, Meng X. Large language models for acute coronary syndrome triage at first medical contact in emergency departments. NPJ Digit Med. 2026 Jun 17. doi: 10.1038/s41746-026-02904-y. Online ahead of print.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Yi-Da Tang, MD, PhD principal investigator
Peking University Third Hospital
Wen-Yao Wang, MD, PhD principal investigator
Peking University Third Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Application of large language model in emergency chest pain triage. and According to the normal procedures to receive medical treatment in people with Chest Pain, run by Peking University Third Hospital at 1 site in China.
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 2 inclusion and 7 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: finished, as of the sponsor's last update on 24 Aug 2026. 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 China. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The Diagnostic Accuracy Rate of MedGuide-V5 (time frame: through study completion, an average of 10 months). 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 NCT06493175, which also lists 1 linked publication.
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 24 Aug 2026.