ArticleFrontiers in endocrinology2022
External validation and clinical application of the predictive model for severe hypoglycemia.
Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.Frontiers in public health · 2023Pooled it
- Risk factors and predictive models for perioperative acute kidney injury in children: a narrative review.Translational pediatrics · 2026Review
- Article
- Machine learning-based online prediction of nocturnal hypoglycemia in elderly patients with type 2 diabetes.Frontiers in endocrinology · 2025Article
- Artificial Intelligence to Diagnose Complications of Diabetes.Journal of diabetes science and technology · 2025Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: An internally validated, one-year risk prediction model for severe hypoglycemia (SH) in type 2 diabetes was evaluated in a general hospital setting to externally verify and validate its performance. Research design and methods: Between December 2017 to December 2019, 2,645 adult patients with type 2 diabetes who visited the diabetes center were enrolled. The receiver operating characteristics curve and Harrell C-statistics were compared to identify the discrimination of the model. The predicted and actual incidence of SH for one year in the development and validation cohorts were compared by ranking participants by deciles of predicted risk. Results: The concordance index was 0.878 in the external validation cohort. The sensitivity and specificity of the predictive model were 0.833 and 0.847, respectively. Based on the predicted risk, we stratified the groups into four categories: low (<0.05%), intermediate (0.05% to <0.5%), high (0.5% to <2.0%), and very high-risk group (≥2.0%). The actual annual incidence of SH gradually increased with the increased risk score level for the decile group ( Conclusion: On external validation, the novel one-year SH prediction model showed excellent discrimination in participants with type 2 diabetes and can effectively screen high-risk patients for SH, even in the general hospital setting.
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