[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100611675":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":37,"centralContacts":41,"locations":51,"responsibleParty":74,"collaborators":76,"id":81,"slug":82,"hasResults":83,"nctId":84,"briefTitle":85,"officialTitle":86,"acronym":87,"eligibilityCriteria":88,"healthyVolunteers":83,"sex":89,"minAge":90,"maxAge":45,"enrollmentInfo":91,"targetDuration":45,"studyType":94,"phases":95,"briefSummary":97,"conditions":98,"keywords":100,"overallStatus":54,"whyStopped":45,"lastUpdateSubmitDate":106,"lastUpdatePostDateStruct":107,"startDateStruct":110,"completionDateStruct":112,"leadSponsor":114,"locationsCount":115},{"fullName":5,"class":6},"Singapore Eye Research Institute","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Artificial Intelligence Assisted Arm","ACTIVE_COMPARATOR","In this arm, human graders will review fundus photographs for glaucomatous features with the aid of output generated by an AI model trained to detect glaucoma. The AI output will be available during grading to support decision-making.",[13],"Diagnostic Test: Artificial Intelligence model to detect glaucoma",{"label":15,"type":16,"description":17,"interventionNames":18},"Current practice arm","PLACEBO_COMPARATOR","Graders will assess fundus photographs for glaucoma following standard clinical practice, using a pre-specified and established set of diagnostic criteria without access to AI-generated outputs.",[19],"Other: No intervention",[21,30],{"type":22,"name":23,"description":24,"armGroupLabels":25,"otherNames":26},"DIAGNOSTIC_TEST","Artificial Intelligence model to detect glaucoma","A Vision Transformer model to detect glaucoma from fundus photos",[9],[27,28,29],"Deep learning model","Vision Transformer","RetiGON",{"type":6,"name":31,"description":32,"armGroupLabels":33,"otherNames":34},"No intervention","Control group with current practice model by human graders",[15],[35,36],"Control group","Current practice model",[38],{"name":39,"affiliation":5,"role":40},"Ching-Yu Cheng, MD, PhD","PRINCIPAL_INVESTIGATOR",[42,47],{"name":39,"role":43,"phone":44,"phoneExt":45,"email":46},"CONTACT","65767277",null,"chingyu.cheng@duke-nus.edu.sg",{"name":48,"role":43,"phone":49,"phoneExt":45,"email":50},"Lavanya Raghavan, MD","65767201","raghavan.lavanya@seri.com.sg",[52],{"facility":53,"status":54,"city":55,"state":55,"zip":56,"country":55,"countryCode":57,"cosmosGeoPoint":58,"geoPoint":63,"contacts":64},"Singapore National Eye Centre","RECRUITING","Singapore","168751","SG",{"type":59,"coordinates":60},"Point",[61,62],103.85007,1.28967,{"lat":62,"lon":61},[65,66,67,70,72],{"name":39,"role":43,"phone":44,"phoneExt":45,"email":45},{"name":48,"role":43,"phone":49,"phoneExt":45,"email":45},{"name":68,"role":69,"phone":45,"phoneExt":45,"email":45},"Lavanya Raghavan","SUB_INVESTIGATOR",{"name":71,"role":40,"phone":45,"phoneExt":45,"email":45},"Hong Chang Tan",{"name":73,"role":40,"phone":45,"phoneExt":45,"email":45},"Shiwaza Aminath Moosa",{"type":75,"investigatorFullName":45,"investigatorTitle":45,"investigatorAffiliation":45,"oldNameTitle":45,"oldOrganization":45},"SPONSOR",[77,79],{"name":78,"class":6},"Singapore General Hospital",{"name":80,"class":6},"SingHealth Polyclinics","100611675","glaucoma-screening-using-artificial-intelligence-assisted-clinical-model-in-singapores-diabetic-eye-screening-program-100611675",false,"NCT07243665","Glaucoma Screening Using Artificial Intelligence Assisted Clinical Model in Singapore's Diabetic Eye Screening Program","A Pragmatic Randomized Controlled Trial of a New Artificial Intelligence-Assisted Clinical Model in Opportunistic Screening for Glaucoma in the Singapore Integrated Diabetic Retinopathy Program","AIGS","Inclusion Criteria: We aim to recruit all eligible patients who attend Singapore General Hospital (SGH) Diabetes \\& Metabolism Centre's (DMC) clinics and SingHealth Polyclinics (SHP)-Bukit Merah under the Singapore Integrated Diabetic Retinopathy Programme (SiDRP). Patients are eligible for the study if\n\n1. Aged 21 years old and above, with diabetes, including type 1 and type 2,\n2. Retinal photos of the patients can be taken with the fundus camera in the clinics, regardless of photos' quality, and\n3. They are willing and capable of providing a written informed consent form.\n\nExclusion Criteria: Patients meeting any of the exclusion criteria will be excluded from participation:\n\n1. Patients who have difficulty in having retinal photos taken or have difficulties in completing the ocular examination protocols according to investigator's decision.\n2. Any other contraindication(s) as indicated by the endocrinologists responsible for the patients.\n\n   \\-","ALL","21 Years",{"count":92,"type":93},1040,"ESTIMATED","INTERVENTIONAL",[96],"NA","Glaucoma is major cause of irreversible blindness and is characterized by optic nerve damage and visual field loss. Screening for glaucoma is challenging due to lack of a simple, accurate, cost-efficient and standardized process. Artificial intelligence, (AI) especially deep learning (DL) algorithms have potential to automate glaucoma detection, but have to be evaluated in real world settings, before public deployment. This study aims to evaluate the screening accuracy of a DL algorithm for glaucoma detection using colour fundus photographs (CFP) in a pragmatic randomised control trial (RCT). The algorithm will be tested in 1040 eligible patients with diabetes, recruited from the Diabetes \\& Metabolism Centre's clinics under the Singapore Integrated Diabetic Retinopathy Program (SiDRP) and randomized to 2 arms: AI-assisted model vs current standard of care (grader assessment). The performance of both arms will be compared to performance of study ophthalmologist in diagnosing glaucoma. We hypothesize that the DL model has better screening performance in detecting glaucoma in the community, compared to the current practice method.",[99],"Glaucoma",[99,101,102,103,104,105],"deep learning","fundus photos","artificial intelligence","randomised controlled trial","screening","2026-01-27",{"date":108,"type":109},"2026-01-29","ACTUAL",{"date":111,"type":109},"2025-11-17",{"date":113,"type":93},"2027-03",{"name":5,"class":6},1]