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AI-Assisted vs Conventional Teleglaucoma Referral (GATES)

4. november 2026 opdateret af: Benjamin Xu, University of Southern California

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.

Studieoversigt

Detaljeret beskrivelse

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.

Undersøgelsestype

Interventionel

Tilmelding (Anslået)

1386

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

  • Navn: Benjamin Y. Xu, MD, PhD
  • Telefonnummer: 323-442-6425
  • E-mail: benjamix@usc.edu

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

18 år og ældre (Voksen, Ældre voksen)

Tager imod sunde frivillige

Ja

Køn, der er berettiget til at studere

Alle

Beskrivelse

Inclusion Criteria:

  • 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

Exclusion Criteria:

  • 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

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Diagnostisk
  • Tildeling: Randomiseret
  • Interventionel model: Parallel tildeling
  • Maskning: Ingen (Åben etiket)

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Eksperimentel: AI-Assisted Teleglaucoma Referral

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.

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.

Aktiv komparator: Conventional Teleglaucoma Referral

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.

Fundus photographs will undergo conventional manual grading by LAC DHS optometrists, with referral and prioritization performed according to current clinical practice.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Time to in-office diagnosis of glaucoma
Tidsramme: 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.

From screening through 36 months

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Visual field mean deviation (MD)
Tidsramme: Baseline and 36 months

Glaucoma disease severity assessed using visual field mean deviation (MD), measured in decibels (dB), at baseline and 36 months.

Baseline and 36 months
Visual field index (VFI)
Tidsramme: Baseline and 36 months

Glaucoma disease severity assessed using visual field index (VFI), expressed as a percentage (%), at baseline and 36 months.

Baseline and 36 months
Mean retinal nerve fiber layer (RNFL) thickness
Tidsramme: Time Frame: Baseline and 36 months

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.

Time Frame: Baseline and 36 months

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Anslået)

1. januar 2027

Primær færdiggørelse (Anslået)

31. december 2032

Studieafslutning (Anslået)

31. december 2034

Datoer for studieregistrering

Først indsendt

26. oktober 2026

Først indsendt, der opfyldte QC-kriterier

4. november 2026

Først opslået (Faktiske)

5. november 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

5. november 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

4. november 2026

Sidst verificeret

1. november 2026

Mere information

Begreber relateret til denne undersøgelse

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

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.

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

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Ingen

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Ingen

Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

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