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Abstract Osteoporotic fractures impose a substantial burden on patients with diabetes due to their unique characteristics in bone metabolism, limiting the efficacy of conventional fracture prediction tools. Artificial intelligence (AI) algorithms have shown great promise in predicting osteoporotic fractures. This review aims to evaluate the application of traditional fracture prediction tools (FRAX, QFracture, and Garvan FRC) in patients with diabetes and osteoporosis, review AI-based fracture prediction achievements, and assess the potential efficiency of AI algorithms in this population. This comprehensive literature search was conducted in Pubmed and Web of Science. We found that conventional prediction tools exhibit limited accuracy in predicting fractures in patients with diabetes and osteoporosis due to their distinct bone metabolism characteristics. Conversely, AI algorithms show remarkable potential in enhancing predictive precision and improving patient outcomes. However, the utilization of AI algorithms for predicting osteoporotic fractures in diabetic patients is still in its nascent phase, further research is required to validate their efficacy and assess the potential advantages of their application in clinical practice.

Abstract Background and objectives Research suggests that diabetic peripheral neuropathy (DPN) is related to plasma fibrinogen (Fib) concentrations, although its correlation with Fib function has not been reported. Here, the k value and angle α, reflecting the plasma Fib function, were used to analyse its correlation with DPN, and their potential as biological indicators for diagnosing DPN was explored. Subjects and methods This prospective observational clinical study enrolled 561 type 2 diabetes mellitus (T2DM) patients, who were divided into the diabetes with symptomatic neuropathy (161 cases), diabetes with asymptomatic neuropathy (132 cases) and diabetes with no neuropathy (268 cases) groups. Meanwhile, 160 healthy unrelated subjects were recruited as controls. Results Fib levels increased slightly in diabetic subjects with neuropathy compared with those without. The angle α levels increased slightly in subjects with asymptomatic DPN compared with those with no neuropathy and increased greatly in subjects with symptomatic DPN compared with those without. The k value levels slightly decreased in subjects with asymptomatic DPN compared with those with no neuropathy and greatly decreased in subjects with symptomatic DPN compared with those without. The association of the k value and angle α with diabetic neuropathy was independent of the hyperglycaemic state and other potential confounders (odds ratio 0.080 [0.051–0.124], P