ArticleScientific reports2025
Predictive factors of hypoglycemia in type 2 diabetes: a prospective study using machine learning.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Electronic health record-derived machine learning model for hypoglycemia risk prediction in type 2 diabetes mellitus patients: development and validation.BMC endocrine disorders · 2026Article
- Effect of Motion Graphic-Based Education on Knowledge, Practice and Recurrence of Hypoglycemia in Patients with Type 2 Diabetes: A Quasi-Experimental Study.International journal of endocrinology and metabolism · 2026Article
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6 authors.
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Abstract
Hypoglycemia is a serious complication in individuals with type 2 diabetes mellitus. Identifying who is most at risk remains challenging due to the non-linear relationships between hypoglycemia and its associated risk factors. The objective of this study is to evaluate the importance and impact of risk factors related to the incidence of hypoglycemia through an explainable machine learning method. This prospective study enrolled 1306 adults with type 2 diabetes mellitus at a specialized diabetes center. Over three months, participants were asked to do self-monitoring blood glucose measurements and record hypoglycemic events. Nine clinically relevant features were analyzed using five machine learning models. The performance of the models was evaluated by different metrics. The SHapley Additive exPlanation method was used to elucidate how each covariate influenced the risk of hypoglycemia. Overall, 419 participants (32.08%) reported at least one hypoglycemic episode. Our findings highlight the non-linear nature of hypoglycemia risk in individuals with T2DM. Insulin therapy, Diabetes duration (> 13.7 years), and eGFR (< 60.2 mL/min/1.73 m
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