BACKGROUND: The objective of this study was to determine the risk factors of hypoglycemia by evaluating the glycemic profile using continuous glucose monitoring (CGM) in patients with type 2 diabetes mellitus (T2DM). METHODS: The participants were 294 patients with T2DM who received inpatient diabetes education. The mean blood glucose (MBG), coefficient of variation (CV), mean postprandial glucose excursion, low blood glucose index (LBGI), and percentage of time with blood glucose (BG) at <70 mg/dL were measured on admission using CGM. We predicted the risk of hypoglycemia utilizing transform to Gaussian model. The primary end point was the relationship between CGM parameters and hypoglycemia. RESULTS: Multivariate logistic regression analysis showed that disease duration, MBG, CV, LBGI, and Predicted% of BG correlated significantly with hypoglycemia. Receiver operating characteristic curve analysis showed that the optimal cutoff points for MBG and CV in predicting hypoglycemia were 152 mg/dL and 22%, respectively. The proportion of patients with hypoglycemia was 0% for the group with no hypoglycemia risk factors, 4.2% for the group with one risk factor, and 36.6% for the group with two risk factors, showing a linear increase across the groups (P < 0.001). LBGI was the best predictor of hypoglycemia; and Predicted% BG <70 mg/dL was very useful as an index to predict hypoglycemia. CONCLUSIONS: Patients with low MBG levels and large fluctuations in BG were more likely to develop hypoglycemia, suggesting that assessment of these two variables is useful for the prediction of hypoglycemia. To achieve good glycemic control free of hypoglycemia, approaches are needed that do not only lower BG level but also minimize fluctuations in blood and interstitial fluid glucose level.
BACKGROUND: The objective of this study was to determine the risk factors of hypoglycemia by evaluating the glycemic profile using continuous glucose monitoring (CGM) in patients with type 2 diabetes mellitus (T2DM). METHODS: The participants were 294 patients with T2DM who received inpatient diabetes education. The mean blood glucose (MBG), coefficient of variation (CV), mean postprandial glucose excursion, low blood glucose index (LBGI), and percentage of time with blood glucose (BG) at <70 mg/dL were measured on admission using CGM. We predicted the risk of hypoglycemia utilizing transform to Gaussian model. The primary end point was the relationship between CGM parameters and hypoglycemia. RESULTS: Multivariate logistic regression analysis showed that disease duration, MBG, CV, LBGI, and Predicted% of BG correlated significantly with hypoglycemia. Receiver operating characteristic curve analysis showed that the optimal cutoff points for MBG and CV in predicting hypoglycemia were 152 mg/dL and 22%, respectively. The proportion of patients with hypoglycemia was 0% for the group with no hypoglycemia risk factors, 4.2% for the group with one risk factor, and 36.6% for the group with two risk factors, showing a linear increase across the groups (P < 0.001). LBGI was the best predictor of hypoglycemia; and Predicted% BG <70 mg/dL was very useful as an index to predict hypoglycemia. CONCLUSIONS:Patients with low MBG levels and large fluctuations in BG were more likely to develop hypoglycemia, suggesting that assessment of these two variables is useful for the prediction of hypoglycemia. To achieve good glycemic control free of hypoglycemia, approaches are needed that do not only lower BG level but also minimize fluctuations in blood and interstitial fluid glucose level.
Authors: Juan P Frias; Guillermo Gonzalez-Galvez; Eva Johnsson; Jill Maaske; Marcia A Testa; Donald C Simonson; Nalina Dronamraju; Ricardo Garcia-Sanchez; Anne L Peters Journal: Diabetes Obes Metab Date: 2020-03-09 Impact factor: 6.577