Diabetic RetinopathyNCT04631653
Verisee Software for Diabetic Retinopathy Screening
A study testing VeriSee® in people with Diabetic Retinopathy, run by Taichung Veterans General Hospital at 1 site in Taiwan.
Trial summary
The investigators aim to improve the diagnostic accuracy and the clinical referral rate for diabetic retinopathy by using a deep learning-based software. Read more about this study
- Who is it for?
- Ages 20 years and older
- Conditions the study is for
- Diabetic Retinopathy
- What is being tested?
- VeriSee®
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,000 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Dec 2020to 31 Dec 2023
- 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 20 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Adults
- Patients with diabetes
- Cooperation to fundal scopic examination
Who cannot join
- Diabetic duration < 5 years in patients with type 1 diabetes
- Pregnancy
Trial locations and contacts
1 site in 1 country.
Yu-Hsuan Li, MD contact
Taiwan1 site
Division of Endocrinology and Metabolism in Taichung Veterans General Hospital
Taichung, 407
About this study
Official title: The Clinical Benefit of an Artificial Intelligence Software Implementation on Diabetic Retinopathy Screening
The investigators aim to improve the diagnostic accuracy and the clinical referral rate for diabetic retinopathy by using a deep learning-based software.
Read the detailed description
Diabetic retinopathy (DR) is the leading cause of blindness among working-age patients with type 2 diabetes. According to previous studies, early screening and timely treatment can reduce the risk of worsening DR and blindness. International guidelines recommend that screening for DR be performed at least once every year for patients with type 2 diabetes. The investigators will implement a validated deep learning-based software, VeriSee®, in clinics, and evaluate the benefits on diagnostic accuracy and the clinical referral rate for diabetic retinopathy after implementation of this software.
- Conditions
- Diabetic Retinopathy
- Being tested
- VeriSee®
- Medical subject headings
- Diabetic Retinopathy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
VeriSee®Device
Screening of diabetic retinopathy using a validated deep learning-based software,VeriSee®
| Study group | Role | What they receive |
|---|---|---|
| Verisee | Experimental | Screening diabetic retinopathy using Verisee software Receives: Device: VeriSee® |
What is being measured
The primary outcome is the main question the study is designed to answer.
diagnostic accuracy
diagnostic accuracy compared to the baseline
Measured: 12 months
Secondary outcomes (3)
Screening rate of diabetic retinopathy
Screening rate of diabetic retinopathy in patients with diabetes
Measured: 12 months
Changes in HbA1c
Changes in HbA1c
Measured: 3 months
Referral rate of diabetic retinopathy
Successful referral rate for referrable diabetic retinopathy
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Nov 2020
- Study start1 Dec 2020 (estimated)
- Primary completion31 Dec 2023 (estimated)
- Study completion31 Dec 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.
- More trials run by Taichung Veterans General HospitalThe 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
- Not applicable
- Intervention model
- Single group
- Model description
- Examine the diagnostic accuracy in referred participants
- Masking
- None (open label)
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Taichung Veterans General Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- I-Te Lee, MD,PhD, Principal investigator, Taichung Veterans General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04631653
- Sponsor's protocol ID
- SE20294A
- Status last verified
- Nov 2020
- First submitted
- 18 Oct 2020
- Last updated
- 17 Nov 2020
- 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 17 Nov 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Clinical Benefit of an Artificial Intelligence Software Implementation on Diabetic Retinopathy Screening
- ClinicalTrials.gov ID
- NCT04631653
- Acronym / sponsor ID
- SE20294A
- Conditions
- Diabetic Retinopathy
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Taichung Veterans General HospitalUniversity, hospital or other
- Study start
- 1 Dec 2020 (estimated)
- Primary completion
- 31 Dec 2023 (estimated)
- Study completion
- 31 Dec 2023 (estimated)
- First posted
- 17 Nov 2020 (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 investigators aim to improve the diagnostic accuracy and the clinical referral rate for diabetic retinopathy by using a deep learning-based software.
Detailed description
Diabetic retinopathy (DR) is the leading cause of blindness among working-age patients with type 2 diabetes. According to previous studies, early screening and timely treatment can reduce the risk of worsening DR and blindness. International guidelines recommend that screening for DR be performed at least once every year for patients with type 2 diabetes. The investigators will implement a validated deep learning-based software, VeriSee®, in clinics, and evaluate the benefits on diagnostic accuracy and the clinical referral rate for diabetic retinopathy after implementation of this software.
Study design
- Primary purpose
- Screening
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- Examine the diagnostic accuracy in referred participants
| Arm | Type | Receives |
|---|---|---|
| Verisee | Experimental | Device: VeriSee®Screening diabetic retinopathy using Verisee software |
Who may qualify
- Ages
- 20 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Adults
- Patients with diabetes
- Cooperation to fundal scopic examination
Key exclusion criteria (2 listed)
- Diabetic duration < 5 years in patients with type 1 diabetes
- Pregnancy
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 |
|---|---|---|
| VeriSee®Screening of diabetic retinopathy using a validated deep learning-based software,VeriSee® | Device | Verisee |
Primary outcome
diagnostic accuracy
Time frame: 12 months
diagnostic accuracy compared to the baseline
3 secondary outcomes
Screening rate of diabetic retinopathy
Time frame: 12 months
Changes in HbA1c
Time frame: 3 months
Referral rate of diabetic retinopathy
Time frame: 12 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Nov 2020.
- 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.
Yu-Hsuan Li, MD contact
I-Te Lee, MD,PhD principal investigator
Taichung Veterans General Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing VeriSee® in people with Diabetic Retinopathy, run by Taichung Veterans General Hospital at 1 site in Taiwan.
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 2 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 17 Nov 2020. 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 Taiwan. 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 I-Te Lee, MD,PhD (+886-4-23592525 ext. 3070, itlee@vghtc.gov.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
diagnostic accuracy (time frame: 12 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 17 Nov 2020.