Ignite Creation Date:
2026-03-26 @ 3:17 PM
Ignite Modification Date:
2026-03-31 @ 8:54 AM
Study NCT ID:
NCT07378956
Status:
NOT_YET_RECRUITING
Last Update Posted:
2026-02-10
First Post:
2026-01-23
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Clinical Efficacy of Implementing an AI-SaMD for Funduscopy Analysis in Patients With Diabetes
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003930', 'term': 'Diabetic Retinopathy'}, {'id': 'D003920', 'term': 'Diabetes Mellitus'}], 'ancestors': [{'id': 'D012164', 'term': 'Retinal Diseases'}, {'id': 'D005128', 'term': 'Eye Diseases'}, {'id': 'D003925', 'term': 'Diabetic Angiopathies'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D048909', 'term': 'Diabetes Complications'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'SCREENING', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 340}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2026-02-20', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2026-02', 'completionDateStruct': {'date': '2027-08-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-02-05', 'studyFirstSubmitDate': '2026-01-23', 'studyFirstSubmitQcDate': '2026-01-23', 'lastUpdatePostDateStruct': {'date': '2026-02-10', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-01-30', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-08-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'True Referral Rate', 'timeFrame': 'within 6 months', 'description': 'The true referral rate is defined as the proportion of subjects who were diagnosed with diabetic retinopathy by an ophthalmologist among those referred to ophthalmology with suspected diabetic retinopathy. The true referral rate will be compared between the intervention and control groups.'}], 'secondaryOutcomes': [{'measure': 'Diabetic Retinopathy (DR) Diagnosis Rate', 'timeFrame': 'Within 6 months', 'description': 'Proportion of subjects diagnosed with diabetic retinopathy among all enrolled subjects will be compared between the intervention group and the control group.'}, {'measure': 'Odds Ratio', 'timeFrame': 'Within 6 months', 'description': 'Odds ratio between the diagnosis of diabetic retinopathy and the application of the AI system among subjects referred to ophthalmology will be calculated.'}, {'measure': 'Referral Rate', 'timeFrame': 'Within 6 months', 'description': 'Proportion of subjects referred to ophthalmology for suspected diabetic retinopathy among all enrolled subjects will be compared between the intervention group and the control group.'}, {'measure': 'Time to Diabetic Retinopathy Diagnosis', 'timeFrame': 'Within 6 months', 'description': 'Time interval from the diagnosis of diabetes mellitus to confirmed diagnosis of diabetic retinopathy based on ophthalmologic evaluation among referred subjects will be compared between the intervention group and the control group.'}, {'measure': 'Performance of the AI System in Detecting Diabetic Retinopathy', 'timeFrame': 'Within 6 months', 'description': 'Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of the AI system will be calculated in comparison with ophthalmologist-confirmed diagnoses.'}, {'measure': 'Accuracy of Referral for Diabetic Retinopathy', 'timeFrame': 'Within 6 months', 'description': 'Proportion of subjects whose referral decisions (referral or non-referral) are concordant with ophthalmologist-confirmed DR status will be compared between the intervention group and the control group.'}, {'measure': 'Adherence Rate', 'timeFrame': 'Within 6 months', 'description': 'Proportion of referred subjects who attend an ophthalmology department will be compared between the intervention group and the control group.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Diabetic Retinopathy (DR)', 'Diabete Mellitus', 'Fundus Photography']}, 'descriptionModule': {'briefSummary': 'The objective of this study is to investigate the efficacy of implementing the AI-SaMD(VUNO Med®-Fundus AI™) alongside routine clinical practice for the detection of diabetic retinopathy.', 'detailedDescription': 'The primary objective of this study is to compare the true referral rate between patients with VUNO Med®-Fundus AI™-assisted screening (intervention group) and those receiving usual clinical care without AI assistance (control group) among patients with diabetes mellitus.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '19 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Adults aged 19 years or older.\n* A documented diagnosis of type 2 diabetes mellitus.\n* Ability to communicate adequately and provide written informed consent for participation in the study.\n\nExclusion Criteria:\n\n* A prior diagnosis of diabetic retinopathy at the time of screening.\n* A history of ophthalmic surgery within 6 months prior to the screening date.\n* A diagnosis of type 1 diabetes mellitus.\n* Pregnancy at the time of screening.\n* Any condition that, in the opinion of the investigator, would make participation in the study infeasible or inappropriate.'}, 'identificationModule': {'nctId': 'NCT07378956', 'acronym': 'SAFE-DM', 'briefTitle': 'Clinical Efficacy of Implementing an AI-SaMD for Funduscopy Analysis in Patients With Diabetes', 'organization': {'class': 'INDUSTRY', 'fullName': 'VUNO Inc.'}, 'officialTitle': 'Clinical Efficacy of Implementing an AI-Driven Software as a Medical Device (SaMD) for Funduscopy Analysis in Patients With Diabetes Mellitus: A Randomized Controlled Trial Protocol', 'orgStudyIdInfo': {'id': 'VN-M-03 PR'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Intervention group', 'description': 'For participants assigned to the intervention group, VUNO Med®-Fundus AI™ will be applied to the acquired fundus images, and the AI-generated outputs will be shown to clinicians during routine care.', 'interventionNames': ['Device: VUNO Med®-Fundus AI™']}, {'type': 'NO_INTERVENTION', 'label': 'Control group', 'description': 'For participants assigned to the control group, fundus images will be interpreted according to usual clinical care without AI assistance.'}], 'interventions': [{'name': 'VUNO Med®-Fundus AI™', 'type': 'DEVICE', 'description': 'VUNO Med®-Fundus AI™ is an artificial intelligence-based fundus image detection and diagnostic support software. The software automatically identifies abnormal retinal findings and provides information on the type and location of detected abnormalities to aid clinical decision-making.', 'armGroupLabels': ['Intervention group']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Hee Jun Park', 'role': 'CONTACT', 'email': 'heejun.park@vuno.co', 'phone': '82-10-7101-2844'}]}, 'ipdSharingStatementModule': {'infoTypes': ['STUDY_PROTOCOL', 'SAP', 'ICF'], 'ipdSharing': 'YES', 'description': 'The institutional dataset used in this study, along with de-identified results, is available upon reasonable request for purposes such as systematic review or meta-analysis, only with approval from the corresponding author and the official approval of local IRB.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'VUNO Inc.', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}