THE ADDED AND INTERPRETATIVE VALUE OF CGM-DERIVED PARAMETERS IN TYPE 1 DIABETES DEPENDS ON THE LEVEL OF GLYCEMIC CONTROL.

In type 1 diabetes mellitus (T1DM) management, continuous glucose monitoring (CGM)-derived parameters can provide additional insights, with time in range (TIR) and other parameters reflecting glycemic control and variability being put forward. This study aimed to examine the added and interpretative value of the CGM-derived indices TIR and coefficient of variation (CV%) in T1DM patients stratified according to their level of glycemic control by means of HbA1C. T1DM patients with a minimum disease duration of 10 years and without known macrovascular disease were enrolled. Patients were equipped with a blinded CGM device for 7 days. TIR and time spent in hypoglycemia and hyperglycemia were determined, and CV% was used as a parameter for glycemic variability. Pearson (r) and Spearman correlations (rs) and a regression analysis were used to examine associations. Ninety-five patients (age: 45 ± 10 years; HbA1C level: 7.7% ± 0.8% [61 ± 7 mmol/mol]) were included (mean blood glucose [MBG]: 159 ± 31 mg/dL; TIR: 55.8% ± 14.9%; CV%: 43.5% ± 7.8%) and labeled as having good (HbA1C level ≤7% [≤53 mmol/mol]; n = 20), moderate (7%-8%; n = 44), or poor (>8% [>64 mmol/mol]; n = 31) glycemic control. HbA1C was significantly associated with MBG (rs = 0.48, P < .001) and time spent in hyperglycemia (total: rs = 0.52; level 2: r = 0.46; P < .001) but not with time spent in hypoglycemia and CV%, even after an analysis of the HbA1C subgroups. Similarly, TIR was negatively associated with HbA1C (r = -0.53; P < .001), MBG (rs = -0.81; P < .001), and time spent in hyperglycemia (total: rs = -0.90; level 2: rs = -0.84; P < .001) but not with time in hypoglycemia. The subgroup analyses, however, showed that TIR was associated with shorter time spent in level-2 hypoglycemia in patients with good (rs = -0.60; P = .007) and moderate (rs = -0.25; P = .047) glycemic control. In contrast, CV% was strongly positively associated with time in hypoglycemia (total: rs = 0.78; level 2: rs = 0.76; P < .001) but not with TIR or time in hyperglycemia in the entire cohort, although the subgroup analyses showed that TIR was negatively associated with CV% in patients with good glycemic control (r = -0.81, P < .001) and positively associated in patients with poor glycemic control (r = +0.47; P < .01). The CGM-derived metrics TIR and CV% are related to clinically important situations, TIR being strongly dependent on hyperglycemia and CV% being reflective of hypoglycemic risk. However, the interpretation and applicability of TIR and CV% and their relationship depends on the level of glycemic control of the individual patient, with CV% generally adding less clinically relevant information in those with poor control. This illustrates the need for further research and evaluation of composite measures of glycemic control in T1DM.

Helleputte S ，De Backer T ，Calders P ，Pauwels B ，Shadid S ，Lapauw B ... -  《Endocrine Practice》

Study of Glycemic Variability in Well-controlled Type 2 Diabetic Patients Using Continuous Glucose Monitoring System.

The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS). To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c. A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over a period of 7 days by using FreeStyle® Libre Pro™, which is a flash glucose monitoring system. The CGM sensor was attached to the left upper arm of the patient on day 0 and removed on day 7. The data recorded in the sensor was then retrieved using pre-installed computer software and analyzed using standard CGM metrics like standard deviation (SD), percentage coefficient of variation (%CV), time above range (TAR), time below range (TBR), and time in range (TIR), out of which %CV was used to quantify GV. %CV has been used to cluster patients into four cohorts from best to worst, namely: best/low CV ≤ 10%, intermediate CV from 10 to 20%, high CV from 20 to 30%, and very high CV of >30%. Scatterplots are used to establish correlations between various parameters. Data from a total of 30 patients were analyzed using CGMS and thus used for calculating standard CGM metrics; glucose readings every 15 minutes were recorded consecutively for 7-day periods, making it a total of 672 readings for each patient. Interpreting the CGM data of all 30 patients, the following results were found: the mean blood glucose of all cases is 134.925 ± 22.323 mg/dL, the mean SD of blood glucose of all cases is 35.348 ± 9.388 mg/dL, the mean of %CV of all cases is 26.376 ± 6.193%. CGM parameters of time are used in the form of percentages, and the following results were found: the mean of TAR, TBR, and TIR is 14.425 ± 13.211, 5.771 ± 6.808, and 82.594 ± 12.888%, respectively. Clustering the patients into cohorts, the proportion of patients exhibiting best/low %CV (10%) is 0, intermediate %CV (10-20%) is 16.67% (five out of 30 patients), high %CV (20-30%) is 50% (15 out of 30 patients) and very high %CV (>30%) is 33.33% (10 out of 30 patients). Also, there is no significant correlation found between HbA1c and %CV (ρ = 0.076, p-value = 0.690); a significant negative correlation was found between %CV and TIR (ρ = -0.604, p < 0.001S); a positive correlation of %CV with TAR and TBR is significant (ρ = 0.816, p-value of <0.001). Using a flash CGMS device and considering %CV as the parameter and primary measure of GV, the study demonstrated the overall instability of a person's glycemic control, making note of unrecognized events of hypoglycemia and hyperglycemia in asymptomatic well-controlled T2DM patients, revealing the overall volatile glycemic control. The most important finding of this study is that even those diabetics who are considered well-controlled experience a great degree of GV as assessed by CGM-derived metrics. This study also demonstrated that there is no significant correlation between HbA1c and GV, suggesting that patients may not have optimal control of their diabetes despite having "normal HbA1c" values; hence, GV can be considered an HbA1c-independent danger factor, having more harmful effects than sustained hyperglycemia in the growth of diabetic complications. So, by using CGM-derived metrics, the measurement of GV has the potential to complement HbA1c data. In this manner, a more comprehensive assessment of glycemic excursions can be provided for better treatment decisions, thereby facilitating optimal glycemic control, which is essential for reducing overall complications and promoting good quality of life.

Swami V ，Yadav SK ，Saxena P ，Sharma A ，Dash CK ，Gupta A ... -  《-》

Factors associated with glycemic variability in children with type 1 diabetes mellitus based on flash glucose monitoring system.

Zhang L ，Guo K ，Xu Y ，Bai J ，Ma Y ，Fu L ，Liu J ，Hu K ，Li X ，Jiang H ，Yang L ... -  《-》

High Glycemic Variability Is Associated with Worse Continuous Glucose Monitoring Metrics in Children and Adolescents with Type 1 Diabetes.

The primary aim of this study was to quantify the prevalence of children and adolescents with type 1 diabetes (T1D) who achieve the recommended target for coefficient of variation (CV) identifying the determining factors to reach this target. The secondary aim was to examine the relationship between CV, the other metrics derived from continuous glucose monitoring (CGM) data and clinical parameters. CGM data were collected from 805 children/adolescents with T1D. Several CGM metrics and patients' characteristics were evaluated. Participants were stratified by CV ≤36% and CV >36%. Binary logistic regression analysis was run to identify the determining factors of high CV. CV was positively correlated with %TBR <70 mg/dL, %TBR <54 mg/dL, %TAR >250 mg/dL, low blood glucose index, and high blood glucose index and negatively with %TIR. CV ≤36% was found in 31.4% of the subjects. The CV >36% group spent less time in %TIR, more time in hypoglycemia and hyperglycemia with lower proportion of subjects using real-time CGM and continuous subcutaneous insulin infusion. Percentage of TBR <70 mg/dL and TAR >250 mg/dL were significant predictors of CV >36%, whereas age, gender, BMI, duration of diabetes, type of CGM device, type of insulin therapy administration and %TIR were not significant predictors (p < 0.001, R2 Nagelkerke = 0.48). CV identifies children and adolescents with worse glycemic control at higher risk of both hypoglycemia and hyperglycemia.

Piona C ，Marigliano M ，Mozzillo E ，Di Candia F ，Zanfardino A ，Iafusco D ，Maltoni G ，Zucchini S ，Delvecchio M ，Maffeis C ... -  《-》

Association between continuous glucose monitoring metrics and clinical outcomes in adults with type 1 diabetes in a real-world setting.

Brett McQueen R ，Perez-Nieves M ，Todd Alonso G ，Fan L ，Hankosky ER ，Shah VN ，Yan Y ，Ellis SL ，Juneja R ... -  《-》