Ignite Creation Date:
2025-12-25 @ 12:22 AM
Ignite Modification Date:
2026-03-01 @ 11:43 AM
Study NCT ID:
NCT01870258
Status:
COMPLETED
Last Update Posted:
2013-06-06
First Post:
2013-05-24
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Myocardial Infarction Prediction
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, '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'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NON_RANDOMIZED', 'maskingInfo': {'masking': 'QUADRUPLE', 'whoMasked': ['PARTICIPANT', 'CARE_PROVIDER', 'INVESTIGATOR', 'OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 1100}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2011-01'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2013-06', 'completionDateStruct': {'date': '2012-06', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2013-06-04', 'studyFirstSubmitDate': '2013-05-24', 'studyFirstSubmitQcDate': '2013-06-04', 'lastUpdatePostDateStruct': {'date': '2013-06-06', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2013-06-06', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2012-04', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'myocardial infarction', 'timeFrame': '2 weeks'}], 'secondaryOutcomes': [{'measure': 'hospital admission due to cardiac events', 'timeFrame': '2 weeks', 'description': 'may be includes unstable angina, cardiac arrest or PCIor CABG'}]}, 'oversightModule': {'oversightHasDmc': True}, 'conditionsModule': {'keywords': ['Myocardial infarction', 'artificial neural networks', 'Electrocardiography'], 'conditions': ['Myocardial Infarction', 'Artificial Neural Network']}, 'descriptionModule': {'briefSummary': 'prediction of MI in patients with chest pain and nondiagnostic ECG was done in 2 weeks', 'detailedDescription': 'Myocardial infarction remains one the leading causes of mortality and morbidity and involves a high cost of care. Early prediction can be helpful in preventing the development of myocardial infarction with appropriate diagnosis and treatment. Artificial neural networks have opened new horizons in learning about the natural history of diseases and predicting cardiac disease.\n\nMethods: A total of 935 cardiac patients with chest pain and nondiagnostic electrocardiogram (ECG) were enrolled and followed for 2 weeks in two groups based on the appearance of myocardial infarction. Two types of data were used for all patients: nominal (clinical data) and quantitative (ECG findings). Two different artificial neural networks - radial basis function (RBF) and multi-layer perceptron (MLP) - were used.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '72 Years', 'minimumAge': '40 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* patient with chest pain refered to ER with nondiagnostic ECG\n\nExclusion Criteria:\n\n* 1\\) Absence of a history of myocardial infarction\n* 2\\) Absence of bundle branch block, Wolf-Parkinson-White abnormality, ventricular hypertrophy or previous ECG signs of myocardial infarction,\n* 3\\) Absence of a history of percutaneous coronary surgery or coronary artery bypass grafting,\n* 4\\) Absence of ECG abnormalities attributable to drugs such as digoxin or tricyclic antidepressants.'}, 'identificationModule': {'nctId': 'NCT01870258', 'briefTitle': 'Myocardial Infarction Prediction', 'organization': {'class': 'OTHER', 'fullName': 'Shiraz University of Medical Sciences'}, 'officialTitle': 'Prediction of Acute Myocardial Infarction With Artificial Neural Networks in Patients With Nondiagnostic Electrocardiogram', 'orgStudyIdInfo': {'id': '90-8037'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'PLACEBO_COMPARATOR', 'label': 'those without MI in 2 weeks', 'description': 'patient without MI in 2 weeks', 'interventionNames': ['Other: ANN prediction of myocardial infarction']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'patient with MI', 'description': 'group with MI in 2 weeks', 'interventionNames': ['Other: ANN prediction of myocardial infarction']}], 'interventions': [{'name': 'ANN prediction of myocardial infarction', 'type': 'OTHER', 'otherNames': ['sofware detected risk of new myocardial infraction'], 'armGroupLabels': ['patient with MI', 'those without MI in 2 weeks']}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Shiraz University of Medical Sciences', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'professor', 'investigatorFullName': 'Javad Kojuri', 'investigatorAffiliation': 'Shiraz University of Medical Sciences'}}}}