新医学2025，Vol.56Issue(7)：638-644,7.DOI:10.12464/j.issn.0253-9802.2025-0076
基于真实环境的人工智能辅助免散瞳眼底照相筛查糖尿病视网膜病变的临床应用研究
Clinical study of the application of artificial intelligence-assisted non-dilated fundus photography for diabetic retinopathy screening in a real-world setting
摘要
Abstract
Objective To investigate the efficiency of artificial intelligence(AI)-assisted non-dilated fundus photography in diabetic retinopathy(DR)screening in a real-world clinical setting and evaluate its diagnostic consistency with ophthalmologists'assessments.Methods In this prospective observational study,14,305 type 2 diabetes mellitus(T2DM)patients who underwent non-dilated fundus examination at the Metabolic Disease Management Center(MMC)of Tianjin Fourth Central Hospital between October 2018 and December 2024 were enrolled.The AI system(VoxelCloud)was used to analyze images captured during non-dilated fundus photography.The weighted Kappa test was employed to assess the agreement between the AI system and expert ophthalmologists.Screening failure rates and causes were also analyzed.Results The overall DR prevalence was 21.4%(3,056/14,305),with a DR positivity rate of 17.2%among patients with T2DM duration of<1 year.The AI system demonstrated substantial agreement with ophthalmologists[Kappa=0.817(95%CI 0.797-0.838),P<0.001].For moderate-to-severe DR,the AI system achieved a sensitivity of 97.3%and specificity of 95.9%.The screening failure rate was 3.7%(115/3,085),primarily due to small pupil size(70.4%)and media opaque caused by conditions such as cataracts(24.3%).Conclusion Implementing non-dilated fundus photography in endocrine clinics facilitates early DR screening.AI-assisted non-dilated screening demonstrates high efficacy in real-world clinical practice.关键词
糖尿病视网膜病变/免散瞳眼底照相/人工智能/真实世界研究/眼底筛查Key words
Diabetic retinopathy/Non-dilated fundus photography/Artificial intelligence/Real-world study/Fundus screening引用本文复制引用
郝兆虎,赵小莹,姚俊鑫,徐荣,祁晓宇,邵海琳..基于真实环境的人工智能辅助免散瞳眼底照相筛查糖尿病视网膜病变的临床应用研究[J].新医学,2025,56(7):638-644,7.基金项目
天津市卫生健康科技项目(TJWJ2023MS019) （TJWJ2023MS019）
