Objective To systematically evaluate the risk factors for developing diabetic foot ulcers (DFU). Methods The Cochrane Library, PubMed, Web of Science, SinoMed, CNKI, VIP, and Wanfang Data were searched for relevant studies on DFU risk factors, and the search time frame was from database creation to March 2022. Meta-analysis was performed using RevMan 5.3. Results A total of 26 publications were included, including 3 cohort studies, 22 case–control studies, and one cross-sectional study. Meta-analysis showed that advanced age [MD = 6.04, 95% CI (3.92, 8.16)], male [OR = 1.84, 95% CI (1.48, 2.29)], elevated body mass index [MD = 1.58, 95% CI (0.47, 2.69)], prolonged duration of diabetes [MD = 2.72, 95% CI (2.33, 3.11)], comorbid nephropathy [OR = 3.15, 95% CI (2.68, 4.60)], comorbid neuropathy [OR = 4.80, 95% CI (2.79, 8.27)], comorbid retinopathy [OR = 3.37, 95% CI (2.26, 5.02)], elevated systolic blood pressure [OR = 8.19, 95% CI (6.33, 10.05)], elevated fasting glucose [MD = 1.60, 95% CI (0.21, 3.00)], elevated glycated hemoglobin [MD = 1.24, 95% CI (0.94, 1.54)], elevated triglycerides [MD = 0.44 (95% CI (0.15, 0.73)], elevated fibrinogen [MD = 1.35, 95% CI (0.62, 2.08)], elevated white blood cell count [MD = 2.56, 95% CI (2.24, 2.88)], elevated C-reactive protein [MD = 15.08, 95% CI (8.03, 22.13)], decreased ankle-brachial ratio [MD = −0.26, 95% CI (−0.36, −0.16)], and decreased total protein levels [MD = −4.58, 95% CI (−6.91, −2.25)] were risk factors for developing DFU ( p < 0.05), and increased HDL cholesterol levels [MD = −0.22, 95% CI (−0.36, −0.08)] were protective factor for developing DFU ( p < 0.05). Conclusion There are many risk factors for developing of ulcers in the diabetic feet, and early prevention and intervention should be performed as early as possible to assess the risk of developing diabetic foot patients.

As the only blood vessels that can directly be seen in the whole body, pathological changes in retinal vessels are related to the metabolic state of the whole body and many systems, which seriously affect the vision and quality of life of patients. Timely diagnosis and treatment are key to improving vision prognosis. In recent years, with the rapid development of artificial intelligence, the application of artificial intelligence in ophthalmology has become increasingly extensive and in-depth, especially in the field of retinal vascular diseases. Research study results based on artificial intelligence and fundus images are remarkable and provides a great possibility for early diagnosis and treatment. This paper reviews the recent research progress on artificial intelligence in retinal vascular diseases (including diabetic retinopathy, hypertensive retinopathy, retinal vein occlusion, retinopathy of prematurity, and age-related macular degeneration). The limitations and challenges of the research process are also discussed.