Diabetic RetinopathyNCT05527535
Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand
An observational study of Diabetic Retinopathy, run by Department of Medical Services Ministry of Public Health of Thailand.
Trial summary
Efficiency and effectiveness of real-world diabetic retinopathy screening by artificial intelligent (AI) are limited. Investigators will implement AI for diabetic retinopathy screening in 13 health districts in Thailand and investigate the efficiency, effectiveness as well as patients and health care personnel's… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Diabetic Retinopathy
- What is being tested?
- Diabetic retinopathy screening by artificial intelligence and Diabetic retinopathy screening by healthcare personnel
- How many people
- 34,500 participants
- Where
- No sites listed yet
- Study dates
- 3 Oct 2022to 30 Sep 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: All diabetes mellitus patients who visit for diabetic retinopathy screening at selected primary care units and hospitals in 13 health districts in Thailand
Who may be able to join
- Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record
- No full-time ophthalmologists in those primary hospital
- Age more than or equal to 18 years
- Eligible for fundus photo imaging at least 1 eye
Who cannot join
- Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record that have full-time ophthalmologists
- Patients who previously diagnosed with other causes of macular edema, for example, Age-related Macular Degeneration, Radiation Retinopathy, Retinal Vein Occlusion etc.
- History of retinal laser or surgery
- Other ocular diseases that require referral to ophthalmologists
- Not eligible for fundus photo imaging for both eyes (any causes)
Trial locations and contacts
No sites are listed yet.
About this study
Official title: Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand: An Implementation Research
Efficiency and effectiveness of real-world diabetic retinopathy screening by artificial intelligent (AI) are limited. Investigators will implement AI for diabetic retinopathy screening in 13 health districts in Thailand and investigate the efficiency, effectiveness as well as patients and health care personnel's satisfaction by an implementation research.
- Conditions
- Diabetic Retinopathy
- Being tested
- Diabetic retinopathy screening by artificial intelligence, Diabetic retinopathy screening by healthcare personnel
- Keywords
- Diabetic Retinopathy, Screening, Deep Learning Algorithm, Human Grader
- Medical subject headings
- Diabetic Retinopathy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Diabetic retinopathy screening by artificial intelligenceDiagnostic test
Screening diabetic patients' eyes with AI through digital health platform
Diabetic retinopathy screening by healthcare personnelDiagnostic test
Screening diabetic patients' eyes by conventional method (healthcare personnel)
| Study group | Role | What they receive |
|---|---|---|
| AI screening group | Diabetes mellitus patients undergo diabetic retinopathy screening by AI Receives: Diagnostic Test: Diabetic retinopathy screening by artificial intelligence | |
| Manual screening group | Diabetes mellitus patients undergo diabetic retinopathy screening by health care personnel Receives: Diagnostic Test: Diabetic retinopathy screening by healthcare personnel |
What is being measured
The primary outcome is the main question the study is designed to answer.
Effectiveness of AI in diabetic retinopathy screening
Referral adherance of patients in AI group in percentage
Measured: Throughout the whole period of screening, approximately 6 months
Efficiency of AI in diabetic retinopathy screening
Down time and failure rate of AI system
Measured: Throughout the whole period of screening, approximately 6 months
Efficiency of AI in diabetic retinopathy screening
Cost in development and implement of AI system in Thai baht unit
Measured: Throughout the whole period of screening, approximately 6 months
Secondary outcomes (1)
Satisfaction of patients and health care personnel in AI-based screening
Measurement of health care personnel's satisfaction by well-developed questionnaire
Measured: At the end of the screening, approximately at Month 6
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Sep 2022
- Study start3 Oct 2022 (estimated)
- Primary completion31 Mar 2023 (estimated)
- Study completion30 Sep 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetic RetinopathyStudies of the same condition, open and under way.
- 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
- Other
- Time perspective
- Prospective
- Enrolment
- 34,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Department of Medical Services Ministry of Public Health of Thailand
- Sponsor type
- Other government
- Collaborators
- Health Systems Research Institute,Thailand
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05527535
- Sponsor's protocol ID
- 65057
- Status last verified
- Aug 2022
- First submitted
- 25 Aug 2022
- Last updated
- 2 Sep 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Fear of inappropriate use of data
Study at a glance
From the registry record, last updated by the sponsor on 2 Sep 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand: An Implementation Research
- ClinicalTrials.gov ID
- NCT05527535
- Acronym / sponsor ID
- 65057
- Conditions
- Diabetic Retinopathy
- Keywords
- Diabetic Retinopathy, Screening, Deep Learning Algorithm, Human Grader
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 34,500 participants (estimated)
- Lead sponsor
- Department of Medical Services Ministry of Public Health of ThailandOther government
- Collaborators
- Health Systems Research Institute,Thailand
- Study start
- 3 Oct 2022 (estimated)
- Primary completion
- 31 Mar 2023 (estimated)
- Study completion
- 30 Sep 2023 (estimated)
- First posted
- 2 Sep 2022 (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.
Efficiency and effectiveness of real-world diabetic retinopathy screening by artificial intelligent (AI) are limited. Investigators will implement AI for diabetic retinopathy screening in 13 health districts in Thailand and investigate the efficiency, effectiveness as well as patients and health care personnel's satisfaction by an implementation research.
Study design
- Observational model
- Other
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI screening group | – | Diagnostic Test: Diabetic retinopathy screening by artificial intelligenceDiabetes mellitus patients undergo diabetic retinopathy screening by AI |
| Manual screening group | – | Diagnostic Test: Diabetic retinopathy screening by healthcare personnelDiabetes mellitus patients undergo diabetic retinopathy screening by health care personnel |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- All diabetes mellitus patients who visit for diabetic retinopathy screening at selected primary care units and hospitals in 13 health districts in Thailand
Key inclusion criteria (4 listed)
- Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record
- No full-time ophthalmologists in those primary hospital
- Age more than or equal to 18 years
- Eligible for fundus photo imaging at least 1 eye
Key exclusion criteria (5 listed)
- Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record that have full-time ophthalmologists
- Patients who previously diagnosed with other causes of macular edema, for example, Age-related Macular Degeneration, Radiation Retinopathy, Retinal Vein Occlusion etc.
- History of retinal laser or surgery
- Other ocular diseases that require referral to ophthalmologists
- Not eligible for fundus photo imaging for both eyes (any causes)
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 |
|---|---|---|
| Diabetic retinopathy screening by artificial intelligenceScreening diabetic patients' eyes with AI through digital health platform | Diagnostic test | AI screening group |
| Diabetic retinopathy screening by healthcare personnelScreening diabetic patients' eyes by conventional method (healthcare personnel) | Diagnostic test | Manual screening group |
Primary outcome
Effectiveness of AI in diabetic retinopathy screening
Time frame: Throughout the whole period of screening, approximately 6 months
Referral adherance of patients in AI group in percentage
Efficiency of AI in diabetic retinopathy screening
Time frame: Throughout the whole period of screening, approximately 6 months
Down time and failure rate of AI system
Efficiency of AI in diabetic retinopathy screening
Time frame: Throughout the whole period of screening, approximately 6 months
Cost in development and implement of AI system in Thai baht unit
1 secondary outcome
Satisfaction of patients and health care personnel in AI-based screening
Time frame: At the end of the screening, approximately at Month 6
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Sep 2022.
- Individual participant dataSharing planned: No. Fear of inappropriate use of data
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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.
Questions about this trial
What is this clinical trial studying?
An observational study of Diabetic Retinopathy, run by Department of Medical Services Ministry of Public Health of Thailand.
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 5 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 2 Sep 2022. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Paisan Ruamviboonsuk, Dr. (+6622062900 ext. 30731, paisan.trs@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Effectiveness of AI in diabetic retinopathy screening (time frame: Throughout the whole period of screening, approximately 6 months). The study lists 3 primary outcomes in all. 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 2 Sep 2022.