GlaucomaGATESNCT07917741
AI-Assisted vs Conventional Teleglaucoma Referral
A study testing AI-Assisted Teleglaucoma Referral Pathway and Conventional Teleglaucoma Referral Pathway in people with Glaucoma, run by University of Southern California.
Trial summary
This randomized controlled trial will compare an artificial intelligence (AI)-assisted teleglaucoma referral pathway with conventional referral among adults identified with referable glaucoma through the Los Angeles County Department of Health Services (LAC DHS) Teleretinal Screening Program. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Glaucoma
- What is being tested?
- AI-Assisted Teleglaucoma Referral Pathway and Conventional Teleglaucoma Referral Pathway
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,386 participants
- Where
- No sites listed yet
- Study dates
- 1 Jan 2027to 31 Dec 2034
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Provision of signed and dated informed consent
- Age ≥18 years
- Receiving routine teleretinal screening through the Los Angeles County Department of Health Services (LAC DHS) Teleretinal Screening Program
- Positive prediction for referable glaucoma by the validated AI algorithm at the time of screening
- No prior ophthalmology or optometry follow-up within the past year
- Willingness and ability to comply with study procedures and follow-up
Who cannot join
- Inability to tolerate fundus photography or ungradable fundus images
- Acute vision loss or major ocular complaints requiring immediate in-person evaluation
- Prior glaucoma diagnosis or treatment within the past year
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Artificial Intelligence-Assisted Teleophthalmology for Glaucoma Screening: A Randomized Controlled Trial
This randomized controlled trial will compare an artificial intelligence (AI)-assisted teleglaucoma referral pathway with conventional referral among adults identified with referable glaucoma through the Los Angeles County Department of Health Services (LAC DHS) Teleretinal Screening Program. The primary objective is to determine whether AI-assisted referral reduces time to in-office diagnosis of manifest glaucoma. Secondary outcomes include glaucoma severity, visual function, need for glaucoma surgery, patient-reported quality of life and satisfaction, health system resource utilization, and cost-effectiveness.
Read the detailed description
Participants identified with referable glaucoma during routine teleretinal screening will be randomized 1:1 to an AI-assisted referral pathway or a conventional referral pathway.
In the AI-assisted arm, fundus photographs will be analyzed using validated deep learning models integrated within the Eye-AI platform. AI outputs, together with intraocular pressure and other clinical information, will be used to stratify referral urgency. AI-generated recommendations will undergo review by glaucoma specialists before referral.
In the conventional referral arm, fundus images will undergo manual review by LAC DHS optometrists, with referral and prioritization performed according to current clinical practice.
Participants in both groups will undergo comprehensive in-office glaucoma evaluation following referral and will be followed for up to 36 months. The primary outcome is time from screening to in-office diagnosis of manifest glaucoma. Secondary outcomes will evaluate disease severity and visual function, need for glaucoma surgery, patient-reported quality of life and satisfaction, health system resource utilization, and cost-effectiveness.
- Conditions
- Glaucoma
- Being tested
- AI-Assisted Teleglaucoma Referral Pathway, Conventional Teleglaucoma Referral Pathway
- Keywords
- glaucoma, teleophthalmology, artificial intelligence, deep learning, glaucoma screening, teleglaucoma, clinical decision support
- Medical subject headings
- Glaucoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted Teleglaucoma Referral PathwayOther
Fundus photographs acquired during routine teleretinal screening will be analyzed using validated deep learning models integrated within the Eye-AI platform. For participants identified with referable glaucoma, AI outputs will be combined with intraocular pressure and other clinical information to stratify referral urgency. All AI-generated recommendations will undergo review by a glaucoma specialist before referral.
Conventional Teleglaucoma Referral PathwayOther
Fundus photographs will undergo conventional manual grading by LAC DHS optometrists, with referral and prioritization performed according to current clinical practice.
| Study group | Role | What they receive |
|---|---|---|
| AI-Assisted Teleglaucoma Referral | Experimental | Participants will undergo AI-assisted referral using validated deep learning models integrated within the Eye-AI platform. AI outputs, together with intraocular pressure and other clinical information, will be used to stratify referral urgency. AI-generated recommendations will be reviewed by glaucoma specialists before referral. Receives: Other: AI-Assisted Teleglaucoma Referral Pathway |
| Conventional Teleglaucoma Referral | Active comparator | Participants will undergo conventional teleglaucoma referral based on manual grading of fundus photographs by LAC DHS optometrists, with referral and prioritization performed according to current clinical practice. Receives: Other: Conventional Teleglaucoma Referral Pathway |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time to in-office diagnosis of glaucoma
Number of days from the initial teleophthalmology screening to the first in-office glaucoma evaluation at which manifest glaucoma is diagnosed.
Measured: From screening through 36 months
Secondary outcomes (3)
Visual field mean deviation (MD)
Glaucoma disease severity assessed using visual field mean deviation (MD), measured in decibels (dB), at baseline and 36 months.
Measured: Baseline and 36 months
Visual field index (VFI)
Glaucoma disease severity assessed using visual field index (VFI), expressed as a percentage (%), at baseline and 36 months.
Measured: Baseline and 36 months
Mean retinal nerve fiber layer (RNFL) thickness
Glaucoma disease severity assessed using mean retinal nerve fiber layer (RNFL) thickness measured by optical coherence tomography (OCT), expressed in micrometers (µm), at baseline and 36 months.
Measured: Time Frame: Baseline and 36 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Nov 2026
- Study start1 Jan 2027 (estimated)
- Primary completion31 Dec 2032 (estimated)
- Study completion31 Dec 2034 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for GlaucomaStudies of the same condition, open and under way.
- More trials run by University of Southern CaliforniaThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Participants will be randomized 1:1 to an AI-assisted teleglaucoma referral pathway or a conventional referral pathway, with randomization stratified by clinical site using permuted blocks of variable size.
- Masking
- None (open label)
- Enrolment
- 1,386 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Southern California
- Sponsor type
- University, hospital or other
- Collaborators
- Los Angeles County Department of Health Services (DHS), National Eye Institute (NEI)
- Responsible party
- Principal investigator, Benjamin Xu, University of Southern California
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07917741
- Sponsor's protocol ID
- APP-26-03722
- Acronym
- GATES
- Status last verified
- Nov 2026
- First submitted
- 26 Oct 2026
- Last updated
- 5 Nov 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared because patient-level health data from the Los Angeles County Department of Health Services (LAC DHS) are subject to HIPAA and LAC DHS data-sharing restrictions. Aggregate-level study results and derived analytic outputs will be shared in accordance with NIH policy and the approved Data Management and Sharing Plan.
Study at a glance
From the registry record, last updated by the sponsor on 5 Nov 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence-Assisted Teleophthalmology for Glaucoma Screening: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07917741
- Acronym / sponsor ID
- GATES / APP-26-03722
- Conditions
- Glaucoma
- Keywords
- glaucoma, teleophthalmology, artificial intelligence, deep learning, glaucoma screening, teleglaucoma, clinical decision support
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,386 participants (estimated)
- Lead sponsor
- University of Southern CaliforniaUniversity, hospital or other
- Collaborators
- Los Angeles County Department of Health Services (DHS), National Eye Institute (NEI)
- Study start
- 1 Jan 2027 (estimated)
- Primary completion
- 31 Dec 2032 (estimated)
- Study completion
- 31 Dec 2034 (estimated)
- First posted
- 5 Nov 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This randomized controlled trial will compare an artificial intelligence (AI)-assisted teleglaucoma referral pathway with conventional referral among adults identified with referable glaucoma through the Los Angeles County Department of Health Services (LAC DHS) Teleretinal Screening Program. The primary objective is to determine whether AI-assisted referral reduces time to in-office diagnosis of manifest glaucoma. Secondary outcomes include glaucoma severity, visual function, need for glaucoma surgery, patient-reported quality of life and satisfaction, health system resource utilization, and cost-effectiveness.
Detailed description
Participants identified with referable glaucoma during routine teleretinal screening will be randomized 1:1 to an AI-assisted referral pathway or a conventional referral pathway.
In the AI-assisted arm, fundus photographs will be analyzed using validated deep learning models integrated within the Eye-AI platform. AI outputs, together with intraocular pressure and other clinical information, will be used to stratify referral urgency. AI-generated recommendations will undergo review by glaucoma specialists before referral.
In the conventional referral arm, fundus images will undergo manual review by LAC DHS optometrists, with referral and prioritization performed according to current clinical practice.
Participants in both groups will undergo comprehensive in-office glaucoma evaluation following referral and will be followed for up to 36 months. The primary outcome is time from screening to in-office diagnosis of manifest glaucoma. Secondary outcomes will evaluate disease severity and visual function, need for glaucoma surgery, patient-reported quality of life and satisfaction, health system resource utilization, and cost-effectiveness.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Participants will be randomized 1:1 to an AI-assisted teleglaucoma referral pathway or a conventional referral pathway, with randomization stratified by clinical site using permuted blocks of variable size.
| Arm | Type | Receives |
|---|---|---|
| AI-Assisted Teleglaucoma Referral | Experimental | Other: AI-Assisted Teleglaucoma Referral PathwayParticipants will undergo AI-assisted referral using validated deep learning models integrated within the Eye-AI platform. AI outputs, together with intraocular pressure and other clinical information, will be used to stratify referral urgency. AI-generated recommendations will be reviewed by glaucoma specialists before referral. |
| Conventional Teleglaucoma Referral | Active comparator | Other: Conventional Teleglaucoma Referral PathwayParticipants will undergo conventional teleglaucoma referral based on manual grading of fundus photographs by LAC DHS optometrists, with referral and prioritization performed according to current clinical practice. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Provision of signed and dated informed consent
- Age ≥18 years
- Receiving routine teleretinal screening through the Los Angeles County Department of Health Services (LAC DHS) Teleretinal Screening Program
- Positive prediction for referable glaucoma by the validated AI algorithm at the time of screening
- No prior ophthalmology or optometry follow-up within the past year
Key exclusion criteria (3 listed)
- Inability to tolerate fundus photography or ungradable fundus images
- Acute vision loss or major ocular complaints requiring immediate in-person evaluation
- Prior glaucoma diagnosis or treatment within the past year
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted Teleglaucoma Referral PathwayFundus photographs acquired during routine teleretinal screening will be analyzed using validated deep learning models integrated within the Eye-AI platform. For participants identified with referable glaucoma, AI outputs will be combined with intraocular pressure and other clinical information to stratify referral urgency. All AI-generated recommendations will undergo review by a glaucoma specialist before referral. | Other | AI-Assisted Teleglaucoma Referral |
| Conventional Teleglaucoma Referral PathwayFundus photographs will undergo conventional manual grading by LAC DHS optometrists, with referral and prioritization performed according to current clinical practice. | Other | Conventional Teleglaucoma Referral |
Primary outcome
Time to in-office diagnosis of glaucoma
Time frame: From screening through 36 months
Number of days from the initial teleophthalmology screening to the first in-office glaucoma evaluation at which manifest glaucoma is diagnosed.
3 secondary outcomes
Visual field mean deviation (MD)
Time frame: Baseline and 36 months
Visual field index (VFI)
Time frame: Baseline and 36 months
Mean retinal nerve fiber layer (RNFL) thickness
Time frame: Time Frame: Baseline and 36 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Nov 2026.
- Individual participant dataSharing planned: No. Individual participant data will not be shared because patient-level health data from the Los Angeles County Department of Health Services (LAC DHS) are subject to HIPAA and LAC DHS data-sharing restrictions. Aggregate-level study results and derived analytic outputs will be shared in accordance with NIH policy and the approved Data Management and Sharing Plan.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Assisted Teleglaucoma Referral Pathway and Conventional Teleglaucoma Referral Pathway in people with Glaucoma, run by University of Southern California.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 5 Nov 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Benjamin Y. Xu, MD, PhD (323-442-6425, benjamix@usc.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time to in-office diagnosis of glaucoma (time frame: From screening through 36 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Nov 2026.