Non-emergency Ocular DiseasesNCT06824389
Evaluate the Performance of Large Language Models in Ophthalmologic Patient Consultation
A study testing Consultation Model of large language model in Ophthalmology Clinics in people with Non-emergency Ocular Diseases, run by Zhongshan Ophthalmic Center, Sun Yat-sen University at 1 site in China.
Trial summary
The intelligent image models lack an understanding of diagnostic and treatment logic, and have not considered textual information such as symptoms and signs. Large language models like ChatGPT, can learn medical knowledge, understand, and generate human natural language, offering new technologies for medical… Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Non-emergency Ocular Diseases
- What is being tested?
- Consultation Model of large language model in Ophthalmology Clinics
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 172 participants
- Where
- 1 siteChina
- Study dates
- 10 May 2025to 17 Jun 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- No age or gender restrictions for patients.
- Non-emergency ocular diseases including corneal diseases, lens disorders, and vitreoretinal diseases.
- Voluntary participation with signed informed consent.
Who cannot join
- Top 10 Ocular Emergencies: globe perforation, ocular chemical injury, corneal ulcer perforation, Pseudomonas aeruginosa keratitis, acute angle-closure glaucoma, acute panophthalmitis, central retinal artery occlusion, acute optic neuritis, endophthalmitis, and orbital cellulitis.
Trial locations and contacts
1 site in 1 country.
China1 site
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong
About this study
Official title: Evaluate the Performance of Large Language Models in Ophthalmologic Patient Consultation: A Randomized Clinical Trial
The intelligent image models lack an understanding of diagnostic and treatment logic, and have not considered textual information such as symptoms and signs. Large language models like ChatGPT, can learn medical knowledge, understand, and generate human natural language, offering new technologies for medical knowledge-based intelligent question answering and the creation of smart medical documents. Therefore, our team plan to verify large language models' feasibility and effectiveness in ophthalmology clinics for medical history collection and examination recommendations during consultations, comparing its performance with traditional methods.
- Conditions
- Non-emergency Ocular Diseases
- Being tested
- Consultation Model of large language model in Ophthalmology Clinics
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Consultation Model of large language model in Ophthalmology ClinicsOther
Large language model completes the medical history collection and recommends examinations.
| Study group | Role | What they receive |
|---|---|---|
| Large language models in consultation | Experimental | After the patient signs the informed consent form, the large language model completes the medical history collection and recommends examinations. Receives: Other: Consultation Model of large language model in Ophthalmology Clinics |
| Traditional consultation | No intervention | After the patient signs the informed consent form, doctor completes the medical history collection and recommends examinations. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Medical History Collection Scoring
The medical history collection is performed using the standard outpatient medical record form. The scoring criteria are developed collaboratively by clinical doctors from multiple specialties and researchers. Scoring is independently conducted in a blinded manner by higher-level specialists.
Measured: through study completion, up to 1 week.
Secondary outcomes (3)
Accuracy of Recommended Tests
The gold standard for both the experimental and control groups consists of test items independently selected by senior specialists, who are not involved in the study.
Measured: through study completion, up to 1 week.
Duration of Medical History Collection
The experimental group uses the developed system to record the consultation and medical record writing completion times, while the control group records the consultation time through audio recording and the medical record writing completion time through the developed system.
Measured: through study completion, up to 1 week.
Patient satisfaction
Collected through a questionnaire.
Measured: through study completion, up to 1 week.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Feb 2025
- Study start10 May 2025
- Primary completion10 Jun 2025
- Study completion17 Jun 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Non-emergency Ocular DiseasesStudies of the same condition, open and under way.
- More trials run by Zhongshan Ophthalmic Center, Sun Yat-sen UniversityThe 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
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 172 participants (actual)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06824389
- Sponsor's protocol ID
- 2025KYPJ004
- Status last verified
- Jan 2026
- First submitted
- 5 Feb 2025
- Last updated
- 8 Jan 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluate the Performance of Large Language Models in Ophthalmologic Patient Consultation: A Randomized Clinical Trial
- ClinicalTrials.gov ID
- NCT06824389
- Acronym / sponsor ID
- 2025KYPJ004
- Conditions
- Non-emergency Ocular Diseases
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 172 participants (actual)
- Lead sponsor
- Zhongshan Ophthalmic Center, Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 10 May 2025 (actual)
- Primary completion
- 10 Jun 2025 (actual)
- Study completion
- 17 Jun 2025 (actual)
- First posted
- 13 Feb 2025 (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.
The intelligent image models lack an understanding of diagnostic and treatment logic, and have not considered textual information such as symptoms and signs. Large language models like ChatGPT, can learn medical knowledge, understand, and generate human natural language, offering new technologies for medical knowledge-based intelligent question answering and the creation of smart medical documents. Therefore, our team plan to verify large language models' feasibility and effectiveness in ophthalmology clinics for medical history collection and examination recommendations during consultations, comparing its performance with traditional methods.
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Large language models in consultation | Experimental | Other: Consultation Model of large language model in Ophthalmology ClinicsAfter the patient signs the informed consent form, the large language model completes the medical history collection and recommends examinations. |
| Traditional consultation | No intervention | –After the patient signs the informed consent form, doctor completes the medical history collection and recommends examinations. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (3 listed)
- No age or gender restrictions for patients.
- Non-emergency ocular diseases including corneal diseases, lens disorders, and vitreoretinal diseases.
- Voluntary participation with signed informed consent.
Key exclusion criteria (1 listed)
- Top 10 Ocular Emergencies: globe perforation, ocular chemical injury, corneal ulcer perforation, Pseudomonas aeruginosa keratitis, acute angle-closure glaucoma, acute panophthalmitis, central retinal artery occlusion, acute optic neuritis, endophthalmitis, and orbital cellulitis.
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 |
|---|---|---|
| Consultation Model of large language model in Ophthalmology ClinicsLarge language model completes the medical history collection and recommends examinations. | Other | Large language models in consultation |
Primary outcome
Medical History Collection Scoring
Time frame: through study completion, up to 1 week.
The medical history collection is performed using the standard outpatient medical record form. The scoring criteria are developed collaboratively by clinical doctors from multiple specialties and researchers. Scoring is independently conducted in a blinded manner by higher-level specialists.
3 secondary outcomes
Accuracy of Recommended Tests
Time frame: through study completion, up to 1 week.
Duration of Medical History Collection
Time frame: through study completion, up to 1 week.
Patient satisfaction
Time frame: through study completion, up to 1 week.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Jan 2026.
- Individual participant dataSharing planned: No
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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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Consultation Model of large language model in Ophthalmology Clinics in people with Non-emergency Ocular Diseases, run by Zhongshan Ophthalmic Center, Sun Yat-sen University at 1 site in China.
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 3 inclusion and 1 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: finished, as of the sponsor's last update on 8 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Medical History Collection Scoring (time frame: through study completion, up to 1 week.). 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 8 Jan 2026.