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Ying, L.P., Yin, O.X., Quan, O.W., Jain, N., Mayuren, J., Pandey, M., et al. (2024) Continuous Glucose Monitoring Data for Artificial Intelligence-Based Predictive Glycemic Event: A Potential Aspect for Diabetic Care. International Journal of Diabetes in Developing Countries, 45, 272-287.
https://doi.org/10.1007/s13410-024-01349-x

has been cited by the following article:

• TITLE: Research Progress on Blood Sugar Management in Diabetic Patients Undergoing Maintenance Hemodialysis

  AUTHORS: Qing Cai, Jimei Sun

  KEYWORDS: Maintenance Hemodialysis, Diabetes, Blood Glucose Management

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.13 No.9, September 2, 2025

  ABSTRACT: Maintenance hemodialysis (MHD) has a long treatment cycle, and the process is accompanied by complex metabolic changes. Blood glucose management has become a significant factor affecting treatment outcomes. During dialysis, diabetic patients are more prone to blood glucose fluctuations compared to non-diabetic patients. Optimizing blood glucose management in diabetic patients undergoing maintenance hemodialysis can reduce the occurrence of dialysis-related hypoglycemic events, improve metabolic disorders, lower the risk of diabetic complications, and enhance patients’ quality of life. This is particularly important for the long-term prognosis of patients with concomitant cardiovascular diseases. Currently, there is a lack of standardized blood glucose management protocols for diabetic patients on MHD. Future research should focus on optimizing more individualized blood glucose management plans to improve patient prognosis and reduce the risk of complications.