An Artificial Intelligence System for Anti-VEGF Treatment Decisions in Retinal Diseases: A Randomized Controlled Trial
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 200
- 试验地点
- 2
- 主要终点
- The prediction accuracy of anti-VEGF therapy interval
研究概览
简要总结
We developed an artificial intelligence system, called QiLin, which was designed to assist anti-VEGF treatment decisions in retinal diseases. QiLin was trained and validated via over 20,000 optical coherence tomography images from multicenter datasets, demonstrating strong performance on both internal and external validation. To evaluate its real-world clinical utility, we conducted a randomized controlled trial that rigorously compares the accuracy of treatment decisions between a physician-only arm and an AI-assisted physician arm.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 盲法
- Double (Participant, Outcomes Assessor)
入排标准
- 年龄范围
- 50 Years 至 85 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients with a diagnosis of nAMD, DME, and RVO; Patients who have completed the loading-dose treatment of anti-VEGF agents; Patients who were willing to participate and provided written informed consent.
排除标准
- •Refusal to undergo OCT testing; Refusal to complete the 3-month follow-up period; Screening for a history of intraocular surgery within the past 6 months; Subjects with severe systemic diseases, intellectual developmental disorders, psychiatric illnesses, etc.
结局指标
主要结局
The prediction accuracy of anti-VEGF therapy interval
时间窗: From enrollment to the end of follow-up at 6 months or to the next anti-VEGF therapy
次要结局
未报告次要终点
研究者
Xiaodong Sun
Professor
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine