医学
眼底摄影
糖尿病性视网膜病变
眼科
外围设备
视网膜
前瞻性队列研究
糖尿病
视网膜病变
生物标志物
眼底(子宫)
队列研究
内科学
队列
眼病
比例危险模型
纵向研究
视网膜
多元分析
试验预测值
心脏病学
病变
外科
血压
视力
检眼镜
黄斑变性
病理
疾病严重程度
作者
Dan Cao,Rose Tan,Rose Ann Goh,Qianhui Yang,Alan Fleming,Nishal Banu Binte Makdoom,Tien‐En Tan,Charles Ong,Joanne Ling,T WONG,Gavin Siew Wei Tan
标识
DOI:10.1136/bjo-2025-327940
摘要
AIMS: To evaluate whether predominantly peripheral lesions (PPLs) and other imaging biomarkers on ultra-widefield (UWF) photography can predict the progression of diabetic retinopathy (DR) in a multiethnic Asian cohort. METHODS: This was a prospective, longitudinal cohort study involving 282 participants (528 eyes) with diabetes and either no DR or non-proliferative DR, recruited from the Singapore National Eye Centre between July 2017 and May 2021. Participants underwent annual UWF colour fundus photography and systemic evaluations over a 2-year period. Images were graded at a centralised reading centre. An automated lesion detection algorithm was used for objective quantification of microaneurysms and retinal haemorrhages. Multivariate regression analysis was conducted to identify independent predictors of DR progression, adjusting for systemic and ocular risk factors. The primary outcome was DR progression, defined as a ≥2 step worsening on the Diabetic Retinopathy Severity Scale or development of proliferative DR within 2 years. RESULTS: The 2-year progression rate of DR was 9.85%. Independent predictors of progression included increased peripheral retinal haemorrhage density (OR=3.09; 95% CI 1.03 to 9.22; p=0.044), presence of PPLs (OR=4.00; 95% CI 1.07 to 15.0; p=0.040) and higher baseline diastolic blood pressure (OR=1.04; 95% CI 1.01 to 1.08; p=0.015). Eyes with PPLs had a 1.6-fold higher risk of progression compared with eyes with predominantly central lesions (15.3% vs 9.3%). CONCLUSION: Peripheral biomarkers on UWF imaging, including peripheral retinal haemorrhage density and PPLs, are independent predictors of DR progression. These findings support the clinical utility of peripheral retinal assessment and automated artificial intelligence-based imaging tools in DR risk stratification and management.
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