Ignite Creation Date:
2025-12-24 @ 3:41 PM
Ignite Modification Date:
2025-12-25 @ 1:51 PM
Study NCT ID:
NCT07079592
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-12-08
First Post:
2025-07-14
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D006976', 'term': 'Hypertension, Pulmonary'}], 'ancestors': [{'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}, {'id': 'D006973', 'term': 'Hypertension'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Participants undergo screening using the AI-ECG system. Those identified as high-risk for pulmonary hypertension receive echocardiography to confirm the diagnosis and guide subsequent management.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 8666}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-12', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2026-06-15', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-12-01', 'studyFirstSubmitDate': '2025-07-14', 'studyFirstSubmitQcDate': '2025-07-14', 'lastUpdatePostDateStruct': {'date': '2025-12-08', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-07-23', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-06-15', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Pulmonary arterial pressure > 50 mmHg', 'timeFrame': '90 days', 'description': 'The composite endpoint is defined as detecting pulmonary hypertension \\> 50mmHg by echocardiography, indicating high risk for pulmonary hypertension.'}], 'secondaryOutcomes': [{'measure': 'Left atrial enlargement on a parasternal long axis view', 'timeFrame': 'Within 90 days after randomization.', 'description': 'The endpoint measures the size of left atrium \\> 40mm on a parasternal long axis view by echocardiography.'}, {'measure': 'Left atrial enlargement by left atrium volume index', 'timeFrame': 'Within 90 days after randomization.', 'description': 'The endpoint measures the size of left atrium volume index \\> 29 mL/m2 in sinus rhythm or \\> 40 mL/m2 in AF by echocardiography.'}, {'measure': 'Right ventricular enlargement on a parasternal long axis view', 'timeFrame': 'Within 90 days after randomization.', 'description': 'The endpoint measures the size of right ventricular basal dimension \\> 27mm by echocardiography.'}, {'measure': 'New onset of left ventricular dysfunction', 'timeFrame': 'Within 90 days after randomization.', 'description': 'The endpoint measures the number and proportion of LVEF \\< 50%.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Artificial intelligence', 'electrocardiogram', 'deep learning', 'pulmonary hypertension'], 'conditions': ['Artificial Intelligence (AI)', 'Artificial Intelligence (AI) in Diagnosis', 'Hypertension, Pulmonary']}, 'referencesModule': {'references': [{'pmid': '39136826', 'type': 'BACKGROUND', 'citation': 'Liu PY, Hsing SC, Tsai DJ, Lin C, Lin CS, Wang CH, Fang WH. A Deep-Learning-Enabled Electrocardiogram and Chest X-Ray for Detecting Pulmonary Arterial Hypertension. J Imaging Inform Med. 2025 Apr;38(2):747-756. doi: 10.1007/s10278-024-01225-4. Epub 2024 Aug 13.'}]}, 'descriptionModule': {'briefSummary': 'This study aims to validate the use of an artificial intelligence-enabled electrocardiogram (AI-ECG) to screen for elevated PAP. We hypothesize that the AI-ECG model can early identify patients with pulmonary hypertension in high-risk patients, prompting further evaluation through echocardiography, potentially resulting in improving cardiovascular outcomes.', 'detailedDescription': 'Pulmonary hypertension is often underdiagnosed due to extensive category of etiology. The diagnosis and treatment of pulmonary hypertension have changed dramatically through the re-defined diagnostic criteria and advanced drug development in the past decade. The application of Artificial Intelligence for the detection of elevated pulmonary arterial pressure (ePAP) was reported recently. An AI model based on electrocardiograms (ECG) has shown promise in not only detecting ePAP but also in predicting future risks related to cardiovascular mortality.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '85 Years', 'minimumAge': '50 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Men or women, ≥ 50 to 85 years of age\n* At least one 12-lead ECG within 12 months\n\nExclusion Criteria:\n\n* A diagnosis of PH WHO Groups 1, 2, 3, 4, or 5\n* A diagnosis of hypertrophic cardiomyopathy, restrictive cardiomyopathy, constrictive pericarditis, cardiac amyloidosis, or infiltrative cardiomyopathy\n* Prior heart, lung, or heart-lung transplants\n* Any systolic pulmonary artery pressure \\>50 mmHg by echocardiography before\n* No echocardiography in 3 months before index ECG'}, 'identificationModule': {'nctId': 'NCT07079592', 'acronym': 'ADDPH', 'briefTitle': 'A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension', 'organization': {'class': 'OTHER', 'fullName': 'National Defense Medical Center, Taiwan'}, 'officialTitle': 'A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension: A Randomized Controlled Trial', 'orgStudyIdInfo': {'id': 'AI-PH'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'AI-ECG guidance', 'description': 'Participants in this arm undergo screening using the AI-ECG system. Those identified as high-risk for pulmonary hypertension receive echocardiography to confirm the diagnosis and guide subsequent management.', 'interventionNames': ['Diagnostic Test: AI-ECG Guidance']}, {'type': 'NO_INTERVENTION', 'label': 'Standard clinical care', 'description': 'Participants in this arm are screened using the AI-ECG system, but diagnosis and management follow the usual clinical practice without echocardiography.'}], 'interventions': [{'name': 'AI-ECG Guidance', 'type': 'DIAGNOSTIC_TEST', 'description': 'Participants undergo screening using the AI-ECG system. Those identified as high-risk for pulmonary hypertension receive echocardiography to confirm the diagnosis and guide subsequent management.', 'armGroupLabels': ['AI-ECG guidance']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Chin Lin, Associate Professor', 'role': 'CONTACT', 'email': 'up6fup0629@gmail.com', 'phone': '886+2-87923311', 'phoneExt': '16118'}], 'overallOfficials': [{'name': 'Chin Lin, associate professor', 'role': 'STUDY_DIRECTOR', 'affiliation': 'National Defense Medical Center, Taiwan'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'National Defense Medical Center, Taiwan', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Assistant professor', 'investigatorFullName': 'Pang-Yen, Liu', 'investigatorAffiliation': 'National Defense Medical Center, Taiwan'}}}}