Ignite Creation Date:
2026-03-26 @ 3:20 PM
Ignite Modification Date:
2026-04-01 @ 2:49 AM
Study NCT ID:
NCT07457320
Status:
NOT_YET_RECRUITING
Last Update Posted:
2026-03-09
First Post:
2026-03-04
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Development and Validation of a Multimodal Artificial Intelligence Model for Early Prediction of Acute Myocardial Infarction
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}, 'conditionBrowseModule': {'meshes': [{'id': 'D009203', 'term': 'Myocardial Infarction'}], 'ancestors': [{'id': 'D017202', 'term': 'Myocardial Ischemia'}, {'id': 'D006331', 'term': 'Heart Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D007238', 'term': 'Infarction'}, {'id': 'D007511', 'term': 'Ischemia'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D009336', 'term': 'Necrosis'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D062645', 'term': 'Percutaneous Coronary Intervention'}], 'ancestors': [{'id': 'D057510', 'term': 'Endovascular Procedures'}, {'id': 'D014656', 'term': 'Vascular Surgical Procedures'}, {'id': 'D013504', 'term': 'Cardiovascular Surgical Procedures'}, {'id': 'D013514', 'term': 'Surgical Procedures, Operative'}, {'id': 'D019060', 'term': 'Minimally Invasive Surgical Procedures'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 1500}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2026-04-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-11', 'completionDateStruct': {'date': '2028-12-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-03-04', 'studyFirstSubmitDate': '2026-03-04', 'studyFirstSubmitQcDate': '2026-03-04', 'lastUpdatePostDateStruct': {'date': '2026-03-09', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-03-09', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-09-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Diagnostic performance', 'timeFrame': '6 months', 'description': 'the diagnostic performance (AUC) for predicting the risk of acute myocardial infarction (AMI) within 6 months'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Myocardial Infarction']}, 'descriptionModule': {'briefSummary': 'Acute myocardial infarction (AMI) remains a leading cause of mortality worldwide. Although early revascularization has markedly improved short-term outcomes, the incidence of major adverse cardiovascular events after the index event remains unacceptably high, posing a formidable clinical challenge. Contemporary risk-stratification instruments rely predominantly on a restricted set of conventional clinical variables and therefore fail to capture the full spectrum of individual pathophysiological complexity. To overcome these limitations, the present investigation aims to develop a post-AMI prognostic model that integrates comprehensive multimodal data.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients with myocardial infarction', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Age ≥18 years old\n2. Presented with myocardial infarction, including NSTEMI and STEMI\n3. Undergoing successful percutaneous coronary intervention.\n\nExclusion Criteria:\n\n1.Poor imaging quality or a data missing rate \\>30%'}, 'identificationModule': {'nctId': 'NCT07457320', 'briefTitle': 'Development and Validation of a Multimodal Artificial Intelligence Model for Early Prediction of Acute Myocardial Infarction', 'organization': {'class': 'OTHER', 'fullName': 'Second Affiliated Hospital, School of Medicine, Zhejiang University'}, 'officialTitle': 'Development and Validation of a Multimodal Artificial Intelligence Model for Early Prediction of Acute Myocardial Infarction', 'orgStudyIdInfo': {'id': '2025-1233'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'MI group', 'description': 'Patients who present with myocardial infarction and undergo successful percutaneous coronary intervention will be eligible for enrollment.', 'interventionNames': ['Procedure: Percutaneous coronary intervention']}], 'interventions': [{'name': 'Percutaneous coronary intervention', 'type': 'PROCEDURE', 'description': 'Percutaneous coronary intervention', 'armGroupLabels': ['MI group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '310000', 'city': 'Hangzhou', 'state': 'Zhejiang', 'country': 'China', 'contacts': [{'name': 'Jun Jiang, MD', 'role': 'CONTACT', 'email': '21918219@zju.edu.cn', 'phone': '+86 15657125311'}], 'facility': 'The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009', 'geoPoint': {'lat': 30.29365, 'lon': 120.16142}}], 'centralContacts': [{'name': 'Jun Jiang, MD', 'role': 'CONTACT', 'email': '21918219@zju.edu.cn', 'phone': '+86 15657125311'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Second Affiliated Hospital, School of Medicine, Zhejiang University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}