Related Experiment Video
Updated: Aug 25, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
External validation and clinical application of the predictive model for severe hypoglycemia
Jae-Seung Yun1, Kyungdo Han2, Soo-Yeon Choi1
1Division of Endocrinology and Metabolism, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, South Korea.
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 (P for trend <0.001). The actual annual SH incidence significantly increased with increase in SH risk scores, which proportionately increased with age, duration of diabetes, glycated hemoglobin, and albuminuria and decreased with body mass index, renal function (p for trends <0.001 for all) in type 2 diabetes.
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.
Related Concept Videos
Hypoglycemia and Glucagon
Diabetes Mellitus: Type 2 and Gestational
Data Validation
Nursing assessment guides are generally based on holistic models rather than medical...
Diabetes Mellitus: Overview and Type I Subtype
Type 1 diabetes is an autoimmune disease in which the immune system mistakenly attacks and destroys the insulin-producing beta cells in the pancreas. As a result, the body is unable to produce sufficient insulin, and individuals with...
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...

