Real-time CGM can predict severe hypoglycemia in people with type 1 diabetes: combined analysis of the HypoDE and DIAMOND trials.

OBJECTIVE: We combined data from two landmark trials (DIAMOND and HypoDE) to examine the diagnostic performance of low glucose measurements derived from open and masked continuous glucose monitoring (CGM) to predict the occurrence of future severe hypoglycemia (SH).

METHODS: We analyzed hypoglycemia parameters (Low Blood Glucose Index [LBGI], % < 70 mg/dl and < 54 mg/dl) from masked CGM over 14 days during baseline and from open CGM over 14 days after randomization. We used receiver operating characteristics (ROC) curves to evaluate the screening performance of these measures to predict future SH. Positive likelihood ratios were calculated to indicate the overall diagnostic performance of these parameters.

RESULTS: Data from 288 individuals with type 1 diabetes (mean age 45.6 ±12.8 years, diabetes duration 20.7 ±13.7 years, HbA1c 8.2 ±1.0 %, Hypoglycemia Unawareness Score 3.4 ± 2.1) were analyzed. Area under ROC-curve (AUC) for LBGI and % <70 mg/dl ranged between 0.68 to 0.75, indicating that LBGI and % <70 mg/dl could significantly predict future SH. Significance of AUC regarding % <54 mg/dl were mixed (0.63 to 0.72). Positive and negative likelihood ratios ranged between 1.82 to 3.20 and 0.56 to 0.32, respectively. Suggested optimal cut-off values were remarkedly lower in open CGM than in masked CGM.

CONCLUSION: These results indicate that CGM-derived hypoglycemic parameters have a good screening performance to significantly predict future clinical hypoglycemia. In addition, this analysis suggests that cut-off values to indicate elevated hypoglycemia risk in the future are substantially lower in open CGM than in masked CGM.