374-P: External Validation and Clinical Application of the Risk Prediction Model for Severe Hypoglycemia in Type 2 Diabetes

Abstract

We previously developed and internally validated a one-year risk prediction model for SH in type 2 diabetes using the National Health Insurance Service database and analyzing data from 1,173,820 subjects with type 2 diabetes. In this study, we planned external validation to verify the performance of the previously-developed risk prediction model in a tertiary hospital setting. From January 2018 to December 2018, 2,724 patients over 30 years old who visited the diabetes center were enrolled. The Harrell C-statistics were compared to identify the discrimination of the developed model. The predicted incidence and actual incidence of SH at 1 year in the development and validation cohort were compared by ranking subjects into deciles of predicted risk. External validation was performed with a total of 2,757 patients. The incidence rate of severe hypoglycemia was 12.6 per 1000 patient-year. The concordance index for SH was 0.854 in the external validation cohort. The sensitivity and specificity of this model prediction in the external validation cohort were 0.714 and 0.853, respectively. However, compared with the model for the development cohort, the incidence rate of SH in each decile group was three times higher than the predicted value. SH risk scores increased in proportion to the age and the duration of diabetes (P for trends <0.001, respectively). The HbA1c distribution was distributed in the form of a J-shape according to the decile group of SH risk score. The risk score for SH was higher in the subjects with chronic kidney disease, heart failure, and dementia than those with other major comorbidities. Our SH prediction model showed excellent discrimination when applied to type 2 diabetes subjects in the tertiary hospital. The results of this study confirm that the risk of hypoglycemia can be accurately predicted using this model. The actual number of SH events is higher than expected, which might be due to the characteristics of the subjects in the tertiary hospital. Disclosure Y. Ahn: None. J. Yun: None. J. Lee: None. K. Song: None. S. Ko: None.