Diabetic Retinopathy
Conditions
Brief summary
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.
Interventions
Screening of diabetic retinopathy using a validated deep learning-based software,VeriSee®
Sponsors
Study design
Intervention model description
Examine the diagnostic accuracy in referred participants
Eligibility
Inclusion criteria
* Adults * Patients with diabetes * Cooperation to fundal scopic examination
Exclusion criteria
* Diabetic duration \< 5 years in patients with type 1 diabetes * Pregnancy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| diagnostic accuracy | 12 months | diagnostic accuracy compared to the baseline |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Screening rate of diabetic retinopathy | 12 months | Screening rate of diabetic retinopathy in patients with diabetes |
| Changes in HbA1c | 3 months | Changes in HbA1c |
| Referral rate of diabetic retinopathy | 12 months | Successful referral rate for referrable diabetic retinopathy |
Countries
Taiwan