Acute Myocardial Infarction (AMI)NCT07496931
Construction and Analysis of a Risk Prediction Model for Acute Myocardial Infarction Based on Spatiotemporal Heterogeneous Data
An observational study of Acute Myocardial Infarction (AMI), run by Beijing Anzhen Hospital.
Trial summary
Acute myocardial infarction (AMI), as the leading cause of death among cardiovascular diseases, has its diagnosis and treatment efficiency directly affecting survival. Although the current diagnosis and treatment system has significantly improved in-hospital outcomes, delays in seeking medical care due to patients'… Read more about this study
- Who is it for?
- Ages 18 to 85 years
- Conditions the study is for
- Acute Myocardial Infarction (AMI)
- What is being tested?
- Acute Myocardial Infarction Risk Prediction Model
- How many people
- 3,000 participants
- Where
- No sites listed yet
- Study dates
- 25 Mar 2026to 31 May 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 to 85 years
- All sexes
- Adult, Older adult
Study population: The integrated team covers preliminary cohorts with multi-dimensional data, including multi-center clinical, imaging, and sample information (total cases >300,000). Based on cohort quality and risk factors, multi-dimensional data is collected on high-risk patients (such as those with previous myocardial infarction, multi-vessel disease, CKD, DM, etc.) to complete the data. The primary endpoint is the time to the first occurrence of acute myocardial infarction within one year after enrollment. Follow-up points are set according to myocardial reinfarction characteristics and needs, and a long-term follow-up plan is formulated (including: frequency of follow-up, follow-up methods, laboratory tests, wearable device data, etc.). Regular follow-up and supplementation of multi-modal data are conducted, ultimately completing a 3,000-case multi-dimensional AMI cohort.
Who may be able to join
- High-risk population for acute myocardial infarction, previously confirmed by cardiac imaging to have coronary artery disease and at least one of the following risk factors:
- Multivessel coronary artery disease (defined as ≥50% stenosis in at least 2 coronary artery regions, including the left main coronary artery)
- Previous myocardial infarction
- Patients with diabetes currently undergoing glucose-lowering treatment
- Chronic kidney disease (CKD) defined as an estimated glomerular filtration rate <60 mL/min/1.73 m² with a known history of chronic kidney disease or biomarkers indicating chronic kidney damage
- Peripheral artery disease, defined as any of the following: ankle-brachial index <0.85; >50% stenosis in lower limb arteries confirmed by angiography (invasive or non-invasive) or duplex ultrasound; limb amputation, peripheral artery bypass, or vascular surgery (such as angioplasty or endarterectomy) secondary to ischemia
- Age ≥18 years
- Ability to understand and comply with the study protocol and sign the informed consent form
Who cannot join
- Researchers consider diseases or conditions that are not suitable for participation in this study (such as mental illness, significant cognitive impairment, neurodegenerative diseases, advanced malignant tumors) or situations (such as inability to communicate well with researchers in the local language, unwillingness to comply with study procedures/instructions, inability to understand study-specific training, physically fragile and vulnerable subjects).
- Participation in a clinical trial involving drugs or devices within 3 months prior to enrollment.
- Women who are pregnant, planning to become pregnant, or breastfeeding.
- Known life-threatening diseases with an expected survival of less than 12 months.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Acute myocardial infarction (AMI), as the leading cause of death among cardiovascular diseases, has its diagnosis and treatment efficiency directly affecting survival. Although the current diagnosis and treatment system has significantly improved in-hospital outcomes, delays in seeking medical care due to patients' insufficient awareness and out-of-hospital deaths are common, representing the biggest bottleneck in improving diagnostic and treatment capabilities. This study takes intelligent-assisted diagnosis of AMI as the entry point and proposes a technical approach that combines a deep learning algorithm based on 12-lead electrocardiograms with wearable monitoring devices. By utilizing morphological feature extraction and deep learning models, it aims to achieve early identification and warning of AMI. The study plans to build a multi-center AMI long-term follow-up cohort covering the Beijing area based on spatiotemporal heterogeneous data. By integrating and forming a precise high-risk cohort of 3,000 acute myocardial infarction cases, it seeks to construct an AMI risk prediction model that combines deep learning with a retrieval-augmented generative expert system, breaking through bottlenecks in ECG recognition and temporal prediction, enhancing model generalization and transferability. Ultimately, it will support the application of wearable devices, shorten pre-hospital delays, achieve early warning and precise diagnosis of AMI, reduce reinfarction and cardiac-related mortality, and carry significant clinical and public health importance.
- Conditions
- Acute Myocardial Infarction (AMI)
- Being tested
- Acute Myocardial Infarction Risk Prediction Model
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Acute Myocardial Infarction Risk Prediction ModelDiagnostic test
For high-risk patients with myocardial infarction, screen and integrate relevant previous prospective, multicenter AMI cohorts, and establish a multicenter, multi-treatment precise high-risk acute myocardial infarction cohort in the Beijing region, with long-term follow-up and supplementation of multidimensional data. Subsequently, based on semantic knowledge-guided cross-modal and cross-timepoint data alignment, use domain adaptation methods to perform fusion modeling of spatiotemporal and modal heterogeneous AMI cohorts. Through multimodal interpretable artificial intelligence models, mine the fused models to complete the construction and validation of an AMI risk prediction model based on spatiotemporally heterogeneous data.
What is being measured
The primary outcome is the main question the study is designed to answer.
The time of the first occurrence of acute myocardial infarction (AMI) within 1 year after enrollment.
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Mar 2026
- Study start25 Mar 2026 (estimated)
- Primary completion31 May 2026 (estimated)
- Study completion31 May 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Myocardial Infarction (AMI)Studies of the same condition, open and under way.
- More trials run by Beijing Anzhen 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Beijing Anzhen Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07496931
- Sponsor's protocol ID
- KS2026022
- Status last verified
- Mar 2026
- First submitted
- 23 Mar 2026
- Last updated
- 27 Mar 2026
- Results posted
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 27 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Construction and Analysis of a Risk Prediction Model for Acute Myocardial Infarction Based on Spatiotemporal Heterogeneous Data
- ClinicalTrials.gov ID
- NCT07496931
- Acronym / sponsor ID
- KS2026022
- Conditions
- Acute Myocardial Infarction (AMI)
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Beijing Anzhen HospitalUniversity, hospital or other
- Study start
- 25 Mar 2026 (estimated)
- Primary completion
- 31 May 2026 (estimated)
- Study completion
- 31 May 2027 (estimated)
- First posted
- 27 Mar 2026 (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.
Acute myocardial infarction (AMI), as the leading cause of death among cardiovascular diseases, has its diagnosis and treatment efficiency directly affecting survival. Although the current diagnosis and treatment system has significantly improved in-hospital outcomes, delays in seeking medical care due to patients' insufficient awareness and out-of-hospital deaths are common, representing the biggest bottleneck in improving diagnostic and treatment capabilities. This study takes intelligent-assisted diagnosis of AMI as the entry point and proposes a technical approach that combines a deep learning algorithm based on 12-lead electrocardiograms with wearable monitoring devices. By utilizing morphological feature extraction and deep learning models, it aims to achieve early identification and warning of AMI. The study plans to build a multi-center AMI long-term follow-up cohort covering the Beijing area based on spatiotemporal heterogeneous data. By integrating and forming a precise high-risk cohort of 3,000 acute myocardial infarction cases, it seeks to construct an AMI risk prediction model that combines deep learning with a retrieval-augmented generative expert system, breaking through bottlenecks in ECG recognition and temporal prediction, enhancing model generalization and transferability. Ultimately, it will support the application of wearable devices, shorten pre-hospital delays, achieve early warning and precise diagnosis of AMI, reduce reinfarction and cardiac-related mortality, and carry significant clinical and public health importance.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- The integrated team covers preliminary cohorts with multi-dimensional data, including multi-center clinical, imaging, and sample information (total cases >300,000). Based on cohort quality and risk factors, multi-dimensional data is collected on high-risk patients (such as those with previous myocardial infarction, multi-vessel disease, CKD, DM, etc.) to complete the data. The primary endpoint is the time to the first occurrence of acute myocardial infarction within one year after enrollment. Follow-up points are set according to myocardial reinfarction characteristics and needs, and a long-term follow-up plan is formulated (including: frequency of follow-up, follow-up methods, laboratory tests, wearable device data, etc.). Regular follow-up and supplementation of multi-modal data are conducted, ultimately completing a 3,000-case multi-dimensional AMI cohort.
Key inclusion criteria (8 listed)
- High-risk population for acute myocardial infarction, previously confirmed by cardiac imaging to have coronary artery disease and at least one of the following risk factors:
- Age ≥18 years
- Ability to understand and comply with the study protocol and sign the informed consent form
Key exclusion criteria (4 listed)
- Researchers consider diseases or conditions that are not suitable for participation in this study (such as mental illness, significant cognitive impairment, neurodegenerative diseases, advanced malignant tumors) or situations (such as inability to communicate well with researchers in the local language, unwillingness to comply with study procedures/instructions, inability to understand study-specific training, physically fragile and vulnerable subjects).
- Participation in a clinical trial involving drugs or devices within 3 months prior to enrollment.
- Women who are pregnant, planning to become pregnant, or breastfeeding.
- Known life-threatening diseases with an expected survival of less than 12 months.
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 |
|---|---|---|
| Acute Myocardial Infarction Risk Prediction ModelFor high-risk patients with myocardial infarction, screen and integrate relevant previous prospective, multicenter AMI cohorts, and establish a multicenter, multi-treatment precise high-risk acute myocardial infarction cohort in the Beijing region, with long-term follow-up and supplementation of multidimensional data. Subsequently, based on semantic knowledge-guided cross-modal and cross-timepoint data alignment, use domain adaptation methods to perform fusion modeling of spatiotemporal and modal heterogeneous AMI cohorts. Through multimodal interpretable artificial intelligence models, mine the fused models to complete the construction and validation of an AMI risk prediction model based on spatiotemporally heterogeneous data. | Diagnostic test | – |
Primary outcome
The time of the first occurrence of acute myocardial infarction (AMI) within 1 year after enrollment.
Time frame: 1 year
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Mar 2026.
- 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.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Myocardial Infarction (AMI), run by Beijing Anzhen Hospital.
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 8 inclusion and 4 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: opening soon, as of the sponsor's last update on 27 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Yan Yan (+861064456782, eva3321@sina.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The time of the first occurrence of acute myocardial infarction (AMI) within 1 year after enrollment. (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 27 Mar 2026.