Application of non-mydriatic fundus examination and artificial intelligence to promote the screening of diabetic retinopathy in the endocrine clinic: an observational study of T2DM patients in Tianjin, China

BACKGROUND: We aimed to determine the role of non-mydriatic fundus examination and artificial intelligence (AI) in screening diabetic retinopathy (DR) in patients with diabetes in the Metabolic Disease Management Center (MMC) in Tianjin, China. METHODS: Adult patients with type 2 diabetes mellitus who were first treated by MMC in Tianjin First Central Hospital and Tianjin 4th Center Hospital were divided into two groups according to the time that MMC was equipped with the non-mydriatic ophthalmoscope and AI system and could complete fundus examination independently (the former was the control group, the latter was the observation group). The observation indices were as follows: the incidence of DR, the fundus screening rate of the two groups, and fundus screening of diabetic patients with different course of disease. RESULTS: A total of 5039 patients were enrolled in this study. The incidence rate of DR was 18.6%, 29.8%, and 49.6% in patients with diabetes duration of ⩽1 year, 1–5 years, and >5 years, respectively. The screening rate of fundus in the observation group was significantly higher compared with the control group (81.3% versus 28.4%, χ(2) = 1430.918, p < 0.001). The DR screening rate of the observation group was also significantly higher compared with the control group in patients with diabetes duration of ⩽1 year (77.3% versus 20.6%; χ(2) = 797.534, p < 0.001), 1–5 years (82.5% versus 31.0%; χ(2) = 197.124, p < 0.001) and ⩾5 years (86.9% versus 37.1%; χ(2) = 475.609, p < 0.001). CONCLUSIONS: In the case of limited medical resources, MMC can carry out one-stop examination, treatment, and management of DR through non-mydratic fundus examination and AI assistance, thus incorporating the DR screening process into the endocrine clinic, so as to facilitate early diagnosis.