The Clinical Benefit of an Artificial Intelligence Software Implementation on Diabetic Retinopathy Screening
试验速览
- 阶段
- 不适用
- 入组人数
- 1,000
- 试验地点
- 2
- 主要终点
- diagnostic accuracy
研究概览
简要总结
The investigators aim to improve the diagnostic accuracy and the clinical referral rate for diabetic retinopathy by using a deep learning-based software.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Screening
- 盲法
- None
入排标准
- 年龄范围
- 20 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients with diabetes
- •Cooperation to fundal scopic examination
排除标准
- •Diabetic duration < 5 years in patients with type 1 diabetes
- •Pregnancy
结局指标
主要结局
diagnostic accuracy
时间窗: 12 months
diagnostic accuracy compared to the baseline
次要结局
- Screening rate of diabetic retinopathy(12 months)
- Changes in HbA1c(3 months)
- Referral rate of diabetic retinopathy(12 months)