Ignite Creation Date:
2025-12-25 @ 1:46 AM
Ignite Modification Date:
2026-03-11 @ 11:39 AM
Study NCT ID:
NCT05847894
Status:
RECRUITING
Last Update Posted:
2025-05-23
First Post:
2023-04-20
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Assisting Pulmonary Disease Diagnosis With Ophthalmic Artificial Intelligence Technology
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D008171', 'term': 'Lung Diseases'}], 'ancestors': [{'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 10000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2020-06-29', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2026-05', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-05-19', 'studyFirstSubmitDate': '2023-04-20', 'studyFirstSubmitQcDate': '2023-05-05', 'lastUpdatePostDateStruct': {'date': '2025-05-23', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-05-08', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-05', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Area Under the Receiver Operating Characteristic curve', 'timeFrame': 'Through study completion, an average of 1 year', 'description': 'Determining the accuracy of diagnosing pulmonary disease with ophthalmic examination'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Pulmonary Diseases', 'Ophthalmological Diagnostic Techniques', 'Artificial intelligence'], 'conditions': ['Pulmonary Diseases', 'Ophthalmological Diagnostic Techniques', 'Artificial Intelligence']}, 'descriptionModule': {'briefSummary': 'This study intends to collect ophthalmologic examination results, pulmonary examination results and related indexes from patients with pulmonary disease and control populations, and combine big data analysis and artificial intelligence technology to explore whether new methods can be provided for early screening strategies for pulmonary disease with the aid of ophthalmologic examination, and thus assist in identifying the types of pulmonary disease and determining disease prognosis.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The study population was recruited from people who visited the cooperative medical unit for lung screening, and from people who were recruited through publicity at the unit and in the community.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Those aged ≥18 years; or those aged \\<18 years who can cooperate with the relevant examination and are accompanied and informed by a guardian;\n* People with respiratory-related diseases who were to undergo pulmonary examination, or those who volunteered to participate in the trial through publicity recruitment;\n* expected survival time of 3 months or more;\n* Those with no previous serious underlying disease and no history of serious eye disease;\n* Those who can cooperate with ophthalmologic and pulmonary-related examinations and have regular follow-up examinations;\n* Those who gave informed consent to the study prior to the trial and voluntarily signed the informed consent form;\n* Other conditions that can be included in the study as judged by the investigator.\n\nExclusion Criteria:\n\n* Patients who are unable to complete ophthalmology or pulmonary-related examinations and regular follow-ups due to serious diseases, trauma or surgery (serious ophthalmology diseases such as extremely poor vision that cannot be fixed, ocular atrophy, severe refractive interstitial clouding that prevents fundus photography, etc.);\n* People with poor compliance due to various reasons such as alcohol or drug dependence, or mental disorders;\n* Those without informed consent;\n* Other conditions judged by the investigator to be unsuitable for participation in the trial.'}, 'identificationModule': {'nctId': 'NCT05847894', 'briefTitle': 'Assisting Pulmonary Disease Diagnosis With Ophthalmic Artificial Intelligence Technology', 'organization': {'class': 'OTHER', 'fullName': 'Zhongshan Ophthalmic Center, Sun Yat-sen University'}, 'officialTitle': 'Assisting Pulmonary Disease Diagnosis With Ophthalmic Artificial Intelligence Technology', 'orgStudyIdInfo': {'id': '2023KYPJ111'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Test group', 'description': 'Individuals with one or more pulmonary diseases', 'interventionNames': ['Diagnostic Test: Ophthalmic examination', 'Diagnostic Test: Pulmonary Examination']}, {'label': 'Control group', 'description': 'Individuals who do not suffer from pulmonary diseases', 'interventionNames': ['Diagnostic Test: Ophthalmic examination', 'Diagnostic Test: Pulmonary Examination']}], 'interventions': [{'name': 'Ophthalmic examination', 'type': 'DIAGNOSTIC_TEST', 'description': 'Various ophthalmic examination modalities, including slit lamp photography, fundus photography, optical coherence tomography imaging and optical coherence tomography angiography, etc.', 'armGroupLabels': ['Control group', 'Test group']}, {'name': 'Pulmonary Examination', 'type': 'DIAGNOSTIC_TEST', 'description': 'Various pulmonary examination modalities, including radiography, chest CT, pulmonary function measurement, etc.', 'armGroupLabels': ['Control group', 'Test group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '510060', 'city': 'Guangzhou', 'state': 'Guangdong', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Haotian Lin, M.D., Ph.D', 'role': 'CONTACT', 'email': 'haot.lin@hotmail.com', 'phone': '8613802793086'}, {'name': 'Xun Wang, M.D., Ph.D', 'role': 'CONTACT', 'email': 'wangx48@mail2.sysu.edu.cn', 'phone': '8615017541549'}], 'facility': 'Zhongshan Ophthalmic Center, Sun Yat-sen University', 'geoPoint': {'lat': 23.11667, 'lon': 113.25}}, {'city': 'Guangzhou', 'state': 'Guangdong', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Bin Xu', 'role': 'CONTACT', 'phone': '+86 13925155511'}], 'facility': 'Guangzhou Kindness Health Care Center (Guangzhou Jiubang Shanxin Clinic Ltd)', 'geoPoint': {'lat': 23.11667, 'lon': 113.25}}, {'city': 'Guangzhou', 'state': 'Guangdong', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Wenhua Liang, M.D.', 'role': 'CONTACT', 'email': 'liangwh1987@163.com'}], 'facility': 'the First Affiliated Hospital of Guangzhou Medical University', 'geoPoint': {'lat': 23.11667, 'lon': 113.25}}, {'city': 'Shenzhen', 'state': 'Guangdong', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Weiyi Lai', 'role': 'CONTACT', 'email': 'zsyLaiwy@163.com', 'phone': '+86 13556125580'}], 'facility': "Shenzhen Third People's Hospital", 'geoPoint': {'lat': 22.54554, 'lon': 114.0683}}], 'centralContacts': [{'name': 'Weixing Zhang, M.D.', 'role': 'CONTACT', 'email': 'zhangwx98@mail2.sysu.edu.cn', 'phone': '8615602211660'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Zhongshan Ophthalmic Center, Sun Yat-sen University', 'class': 'OTHER'}, 'collaborators': [{'name': 'The First Affiliated Hospital of Guangzhou Medical University', 'class': 'OTHER'}, {'name': "Shenzhen Third People's Hospital", 'class': 'OTHER'}, {'name': 'Guangzhou Kindness Health Care Center (Guangzhou Jiubang Shanxin Clinic Ltd), Guangzhou, China', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR'}}}}