EmergenciesNCT05680090
Artificial Intelligent System for Eye Emergency Triage and Primary Diagnosis
An observational study of Emergencies and Eye Diseases, run by Sun Yat-sen University at 1 site in China.
Trial summary
Ophthalmic emergencies are acute vision-threatening disorders, for which a delay in prompt emergency response could result in catastrophic vision loss. Triage is an effective process for ensuring that timely emergency care is provided despite limited resource by prioritizing patients to appropriate orders for visits. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Emergencies, Eye Diseases
- What is being tested?
- Artificial intelligent system for eye emergency triage and primary diagnosis
- How many people
- 100 participants
- Where
- 1 siteChina
- Study dates
- 10 Dec 2022to 20 Jan 2023
- Phase
- Observational
- 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
- No healthy volunteers
- Child, Adult, Older adult
Study population: Through the online popular science, news reports, and other channels, we will promote and inform patients about the relevant knowledge of ophthalmic emergencies, so that they can judge by themselves and freely decide whether to participate in this study or not.
Who may be able to join
- Suffering acute ophthalmic symptoms within one month
- Visiting the ocular emergency department for the first time
- Must be able to complete the triage form for ophthalmic emergency
- Must be able to cooperate either by submitting smartphone photographs or receiving slit-lamp examination
Who cannot join
- The image quality does not meet the clinical requirements.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity
Guangzhou, Guangdong, 510060
Haotian Lin, M.D., Ph.D, 8613802793086, linht5@mail.sysu.edu.cn
Xiaohang Wu, M.D., Ph.D, 8615913177657, wxhang@mail2.sysu.edu.cn
About this study
Official title: Prospective Validation of an Artificial Intelligent System for Eye Emergency Triage and Primary Diagnosis
Ophthalmic emergencies are acute vision-threatening disorders, for which a delay in prompt emergency response could result in catastrophic vision loss. Triage is an effective process for ensuring that timely emergency care is provided despite limited resource by prioritizing patients to appropriate orders for visits. Historically, registered nurses classify emergency patients based on personal experiences with high variation. Additionally, primary healthcare providers have been conventionally at the forefront of providing first aid care. However, most of ocular emergencies are wrongly diagnosed or referred due to non-eye specialists' limited knowledge and training in the ophthalmology.
Here, the investigators established and validated an artificial intelligence system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images. This system has been integrated into a website to be prospectively validated in the real world.
- Conditions
- Emergencies, Eye Diseases
- Being tested
- Artificial intelligent system for eye emergency triage and primary diagnosis
- Keywords
- Artificial intelligence, Ophthalmic emergency triage, Primary diagnosis, Multimodal data
- Medical subject headings
- Emergencies, Eye Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligent system for eye emergency triage and primary diagnosisDiagnostic test
An intelligent triage and diagnostic system for ophthalmic emergencies has been developed. In the prospective test, patients with acute ocular symptoms can achieve remote self-triage and primary diagnosis after uploading metadata and ocular images.
| Study group | Role | What they receive |
|---|---|---|
| Eligible participants for AI-based ophthalmic emergency triage and primary diagnosis | Not described Receives: Diagnostic Test: Artificial intelligent system for eye emergency triage and primary diagnosis |
What is being measured
The primary outcome is the main question the study is designed to answer.
The accuracy of the triage model
Use the triage model to classify patients with acute ocular symptoms, and count the proportion of correct classification.
Measured: 2023.1
Secondary outcomes (1)
The accuracy of the primary diagnostic model
Use the primary diagnostic model to diagnose patients with ophthalmic emergencies, and count the proportion of correct diagnosis in all patients.
Measured: 2023.1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Jan 2023
- Study start10 Dec 2022
- Primary completion13 Jan 2023 (estimated)
- Study completion20 Jan 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for EmergenciesStudies of the same condition, open and under way.
- More trials run by 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Sun Yat-sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Haotian Lin, Sun Yat-sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05680090
- Sponsor's protocol ID
- 2021KYPJ046
- Status last verified
- Dec 2022
- First submitted
- 13 Dec 2022
- Last updated
- 11 Jan 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 11 Jan 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Validation of an Artificial Intelligent System for Eye Emergency Triage and Primary Diagnosis
- ClinicalTrials.gov ID
- NCT05680090
- Acronym / sponsor ID
- 2021KYPJ046
- Conditions
- Emergencies, Eye Diseases
- Keywords
- Artificial intelligence, Ophthalmic emergency triage, Primary diagnosis, Multimodal data
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 10 Dec 2022 (actual)
- Primary completion
- 13 Jan 2023 (estimated)
- Study completion
- 20 Jan 2023 (estimated)
- First posted
- 11 Jan 2023 (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.
Ophthalmic emergencies are acute vision-threatening disorders, for which a delay in prompt emergency response could result in catastrophic vision loss. Triage is an effective process for ensuring that timely emergency care is provided despite limited resource by prioritizing patients to appropriate orders for visits. Historically, registered nurses classify emergency patients based on personal experiences with high variation. Additionally, primary healthcare providers have been conventionally at the forefront of providing first aid care. However, most of ocular emergencies are wrongly diagnosed or referred due to non-eye specialists' limited knowledge and training in the ophthalmology.
Here, the investigators established and validated an artificial intelligence system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images. This system has been integrated into a website to be prospectively validated in the real world.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Eligible participants for AI-based ophthalmic emergency triage and primary diagnosis | – | Diagnostic Test: Artificial intelligent system for eye emergency triage and primary diagnosis |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Through the online popular science, news reports, and other channels, we will promote and inform patients about the relevant knowledge of ophthalmic emergencies, so that they can judge by themselves and freely decide whether to participate in this study or not.
Key inclusion criteria (4 listed)
- Suffering acute ophthalmic symptoms within one month
- Visiting the ocular emergency department for the first time
- Must be able to complete the triage form for ophthalmic emergency
- Must be able to cooperate either by submitting smartphone photographs or receiving slit-lamp examination
Key exclusion criteria (1 listed)
- The image quality does not meet the clinical requirements.
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 |
|---|---|---|
| Artificial intelligent system for eye emergency triage and primary diagnosisAn intelligent triage and diagnostic system for ophthalmic emergencies has been developed. In the prospective test, patients with acute ocular symptoms can achieve remote self-triage and primary diagnosis after uploading metadata and ocular images. | Diagnostic test | Eligible participants for AI-based ophthalmic emergency triage and primary diagnosis |
Primary outcome
The accuracy of the triage model
Time frame: 2023.1
Use the triage model to classify patients with acute ocular symptoms, and count the proportion of correct classification.
1 secondary outcome
The accuracy of the primary diagnostic model
Time frame: 2023.1
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Jan 2023.
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Emergencies and Eye Diseases, run by 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 4 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: status not confirmed, as of the sponsor's last update on 11 Jan 2023. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Haotian Lin, M.D., Ph.D (8613802793086, haot.lin@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The accuracy of the triage model (time frame: 2023.1). 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 11 Jan 2023.