Objective: There is a scarcity of long-term prediction models for severe hypoglycemia (SH) in subjects with type 2 diabetes. A model was developed and validated to predict the risk of SH in adult patients with type 2 diabetes (T2DM).

Research Design and Methods: Baseline and follow-up data from patients with T2DM who received health evaluations from January 1, 2009, to December 31, 2010 (n = 1,676,885), were analyzed as development (n = 1,173,820) and validation (n = 503,065) cohorts using the National Health Insurance Database (DB) in Korea. New SH episodes were identified using ICD-10 codes until December 31, 2015. A Cox proportional hazards regression model and Cox model coefficients were used to derive a risk scoring system, and 14 predictive variables were selected. A risk score nomogram based on the risk prediction model was created to estimate the five-year risk of SH.

Results: In the development cohort, a total of 34,955 (2.98%) patients experienced SH episodes during the follow-up period of 5.7 years (5.22/1,000 person-years). After multivariable adjustment, older age, being female sex, being a current smoker, drinking, having a low body mass index, lack of exercise, previous SH events, insulin or multiple oral hypoglycemic agent use, presence of hypertension or chronic kidney disease, longer duration of diabetes, low or high glucose level, and high Charlson Comorbidity Index score were found to be significant risk factors for the development of SH and were incorporated into the risk model. The concordance indices were 0.822 (95% confidence interval, 0.81-0.83). In patients in the top decile, the incidence rate of SH was estimated to be 25.6/1,000 person-years. The calibration plot showed a nearly 45° line, which indicates that this model is a good predictor of an absolute SH event.

Conclusion: This 14-variable prediction model for SH events may be a useful tool to identify high-risk patients and guide prevention of SH in adult patients with T2DM.


S. Ko: None. J. Yun: None. K. Han: None. H. Kwon: None. K. Song: None. Y. Ahn: None.

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