Article Document Academic Article Information Content Entity Continuant Continuant Journal Article Entity Entity Generically Dependent Continuant 2025-05-07T15:09:50 RDF description of Predicting the 6-month risk of severe hypoglycemia among adults with diabetes: development and external validation of a prediction model - http://repository.healthpartners.com/individual/document-rn1417 12008 Cohort Studies Medical Records Systems, Computerized Follow-Up Studies Diabetes Predicting the 6-month risk of severe hypoglycemia among adults with diabetes: development and external validation of a prediction model Journal of Diabetes and Its Complications Risk Factors 2022-02-21T22:48:57.408-06:00 10.1016/j.jdiacomp.2017.04.004 Models Forecasting public Blood document-rn1417 Drugs and Drug Therapy 31 18596 7 Comparative Studies <p>AIMS: To develop and externally validate a prediction model for the 6-month risk of a severe hypoglycemic event among individuals with pharmacologically treated diabetes. METHODS: The development cohort consisted of 31,674 Kaiser Permanente Colorado members with pharmacologically treated diabetes (2007-2015). The validation cohorts consisted of 38,764 Kaiser Permanente Northwest members and 12,035 ΏͺΤΖΜεΣύ members. Variables were chosen that would be available in electronic health records. We developed 16-variable and 6-variable models, using a Cox counting model process that allows for the inclusion of multiple 6-month observation periods per person. RESULTS: Across the three cohorts, there were 850,992 6-month observation periods, and 10,448 periods with at least one severe hypoglycemic event. The six-variable model contained age, diabetes type, HgbA1c, eGFR, history of a hypoglycemic event in the prior year, and insulin use. Both prediction models performed well, with good calibration and c-statistics of 0.84 and 0.81 for the 16-variable and 6-variable models, respectively. In the external validation cohorts, the c-statistics were 0.80-0.84. CONCLUSIONS: We developed and validated two prediction models for predicting the 6-month risk of hypoglycemia. The 16-variable model had slightly better performance than the 6-variable model, but in some practice settings, use of the simpler model may be preferred.<p>