Open AccessAn online diabetic retinopathy screening tool for patients with type 2 diabetes
Author(s) -
Wan-Yue Li,
Ming Yang,
Yanan Song,
Ling Luo,
Chuang Nie,
Maonian Zhang
Publication year - 2021
Publication title -
international journal of ophthalmology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.634
H-Index - 29
eISSN - 2227-4898
pISSN - 2222-3959
DOI - 10.18240/ijo.2021.11.15
Subject(s) - medicine , diabetic retinopathy , type 2 diabetes , logistic regression , referral , diabetes mellitus , type 2 diabetes mellitus , machine learning , family medicine , computer science , endocrinology
AIM: To develop a useful diabetic retinopathy (DR) screening tool for patients with type 2 diabetes mellitus (T2DM).METHODS: A DR prediction model based on the Logistic regression algorithm was established on the development dataset containing 778 samples (randomly assigned to the training dataset and the internal validation dataset at a ratio of 7:3). The generalization capability of the model was assessed using an external validation dataset containing 128 samples. The DR risk calculator was developed through WeChat Developer Tools using JavaScript, which was embedded in the WeChat Mini Program.RESULTS: The model revealed risk factors (duration of diabetes, diabetic nephropathy, and creatinine level) and protective factors (annual DR screening and hyperlipidemia) for DR. In the internal and external validation, the recall ratios of the model were 0.92 and 0.89, respectively, and the area under the curve values were 0.82 and 0.70, respectively.CONCLUSION: The DR screening tool integrates education, risk prediction, and medical advice function, which could help clinicians in conducting DR risk assessments and providing recommendations for ophthalmic referral to increase the DR screening rate among patients with T2DM.