Continuous Glucose Monitoring Parameters Research Articles

Assessing the risk of ketoacidosis due to sodium-glucose cotransporter (SGLT)-2 inhibitors in patients with type 1 diabetes: A meta-analysis and meta-regression.

BackgroundSodium-glucose cotransporter-2 (SGLT2) inhibitors (SGLT2i) showed benefits in type 1 diabetes mellitus (T1DM), but the risk of diabetic ketoacidosis (DKA) limits their use. Ability to predict DKA risk and therapeutic responses would enable appropriate patient selection for SGLT2i. We conducted a meta-analysis and meta-regression of randomized controlled trials (RCTs) evaluating SGLT2i in T1DM to assess moderators of the relative risk (RR) of DKA, of glycemic (HbA1c, fasting plasma glucose, continuous glucose monitoring parameters, insulin dose, and insulin sensitivity indices) and non-glycemic (body mass index (BMI), systolic BP, renal function, albuminuria, and diabetic eye disorders) efficacy, and of other safety outcomes (including hypoglycemia, infections, major adverse cardiovascular events, and death).Methods and findingsWe searched MEDLINE, Cochrane Library, EMBASE, ClinicalTrials.gov, Cochrane CENTRAL Register of Controlled Trials, and other electronic sources through August 30, 2020, for RCTs comparing SGLT2i with active comparators or placebo in adult patients with T1DM. Reviewers extracted data for relevant outcomes, performed random effects meta-analyses, subgroup analyses, and multivariable meta-regression. The strength of evidence was summarized with the GRADE approach. Among 9,914 records identified, 18 placebo-controlled RCTs (7,396 participants, 50% males, mean age 42 y (range 23 to 55 y), 5 different SGLT2i evaluated), were included. Main outcome measures were effect sizes and moderators of glycemic and non-glycemic efficacy and of safety outcomes. In a multivariable meta-regression model, baseline BMI (β = 0.439 [95% CI: 0.211, 0.666], p < 0.001) and estimated glucose disposal rate (eGDR) (β = −0.766 [−1.276, −0.256], p = 0.001) were associated with the RR of DKA (RR: 2.81; 95% CI:1.97, 4.01; p < 0.001, R2 = 61%). A model including also treatment-related parameters (insulin dose change-to-baseline insulin sensitivity ratio and volume depletion) explained 86% of variance across studies in the risk of DKA (R2 = 86%). The association of DKA with a BMI >27 kg/m2 and with an eGDR <8.3 mg/kg/min was confirmed also in subgroup analyses. Among efficacy outcomes, the novel findings were a reduction in albuminuria (WMD: −9.91, 95% CI: −16.26, −3.55 mg/g, p = 0.002), and in RR of diabetic eye disorders (RR: 0.27[0.11, 0.67], p = 0.005) associated with SGLT2i. A SGLT2i dose-response gradient was consistently observed for main efficacy outcomes, but not for adverse events (AEs). Overall, predictors of DKA and of other AEs differed substantially from those of glycemic and non-glycemic efficacy. A limitation of our analysis was the relatively short (≤52 weeks) duration of included RCTs. The potential relevance for clinical practice needs also to be confirmed by real-world prospective studies.ConclusionsIn T1DM, the risk of DKA and main therapeutic responses to SGLT2i are modified by baseline BMI and insulin resistance, by total insulin dose reduction-to-baseline insulin sensitivity ratio, and by volume depletion, which may enable the targeted use of these drugs in patients with the greatest benefit and the lowest risk of DKA.

Chronotherapeutic efficacy of suvorexant on sleep quality and metabolic parameters in patients with type 2 diabetes and insomnia

AimsThis study aimed to assess the chronotherapeutic efficacy of suvorexant on subjective sleep parameters and metabolic parameters in patients with type 2 diabetes and insomnia. MethodsThirteen patients with type 2 diabetes who met the Pittsburg Sleep Quality index criteria for primary insomnia took suvorexant 20 mg/day (15 mg/day for ≥65 years) for 14 ± 2 weeks. The following parameters were assessed before and after the treatment: sleep diary for sleep duration and quality (i.e., sleep onset latency, waking after sleep onset, and sleep efficiency [sSE]), Insomnia Severity Index, clinical and biochemical data, continuous glucose monitoring (CGM), and validated self-administered questionnaire on food intake. ResultsSuvorexant significantly improved sSE, abdominal circumference, and sucrose intake (all p < 0.05), but did not change HbA1c, CGM parameters, or body weight. Correlation analysis revealed that changes in sSE were associated with those in HbA1c and body weight (r = −0.61 and r = −0.66, respectively; both p < 0.05). ConclusionsSuvorexant significantly improved sleep quality and obesity-associated parameters in patients with type 2 diabetes in 14 weeks. Improvements in sleep quality were associated with improvements in glycemic control. Sleep disorder treatment using suvorexant may provide metabolic benefits for patients with type 2 diabetes.

Do pregnant women with gestational diabetes need continuous glucose monitoring?

BackgroundGestational diabetes mellitus affects 5–18% of pregnant women worldwide. Good blood glucose control is required to decrease the risk of macrosomia and long-term adverse effects for mothers and their offspring. Although continuous glucose monitoring (CGM) has been increasingly used for glucose management, little evidence has been reported in patients with gestational diabetes. We aimed to estimate and compare the effects of CGM parameters and routine oral glucose tolerance test (OGTT) measurements on fetal growth. MethodsIn this observational study, we recruited pregnant women with gestational diabetes who underwent CGM for 5–14 days after OGTT. We collected OGTT glucose measurements (including fasting, 1-h, and 2-h glucose concentrations), CGM time-series data, and birthweight. Parameters extracted from CGM data were glucose exposure metrics (including mean of day and night glucose and estimated HbA1c levels), glucose variability metrics (including J index and mean amplitude of glycaemic excursions), and a comprehensive glucose metric that captures both increasing mean glucose and glucose variability (ie, hours per day spent in severe glucose variability). We calculated birthweight percentiles using the INTERGROWTH-21st birthweight standard and used multiple linear regression models to estimate the association of birthweight percentile with OGTT measurements and CGM glucose features. We calculated adjusted mean difference and their 95% CIs for a 1 SD increase in glucose metrics. FindingsBetween Jan 11, 2017, and Nov 15, 2018, we enrolled 97 women with gestational diabetes. For OGTT measures, each 1 SD increase in maternal fasting glucose was associated with a 5·62 (95% CI 0·39–10·85) percentile increase in neonatal birthweight. Among CGM parameters, each 1 SD increase in mean glucose concentration at night and hours per day spent in severe glucose variability were associated with a 5·81 (95% CI 0·34–11·29) and 6·45 (0·73–12·17) percentile increase in birthweight. None of the levels of other glucose metrics either from OGTT or CGM measurements were associated with birthweight percentile. InterpretationFasting glucose has a comparable effect on fetal growth to glucose metrics obtained from CGM data, indicating that fasting glucose measurement is an effective and low-cost option for the management of gestational diabetes. FundingThe National Natural Science Foundation of China.

Efficacy and safety of dual SGLT 1/2 inhibitor sotagliflozin in type 1 diabetes: meta-analysis of randomised controlled trials

ObjectiveTo assess the efficacy and safety of dual sodium glucose cotransporter (SGLT) 1/2 inhibitor sotagliflozin in type 1 diabetes mellitus.DesignMeta-analysis of randomised controlled trials.Data sourcesMedline; Cochrane Library; Embase; international meeting...

Continuous glucose monitoring defined glucose variability is associated with cardiovascular autonomic neuropathy in type 1 diabetes.

The purpose of this study was to establish the association between continuous glucose monitoring (CGM)-defined glycaemic variability (GV) and cardiovascular autonomic neuropathy (CAN) in type 1 diabetes independent of mean glucose and to examine the relative contribution of each internationally standardized CGM parameter to this association. This study included 80 adults with type 1 diabetes who underwent 3-day CGM and autonomic function tests within 3months. The degree of association between internationally standardized CGM parameters and CAN, defined as at least two abnormal parasympathetic tests or the presence of orthostatic hypotension, were analysed by logistic regression, receiver operating characteristics (ROC), and dominance analysis. A total of 36 subjects (45.0%) were diagnosed with CAN. When adjusted with mean glucose and clinical risk factors of CAN, standard deviation, coefficient of variation, mean amplitude of glycaemic excursion, percent time in level 1 (glucose 54-69mg/dL) and level 2 (glucose<54mg/dL) hypoglycaemia, area under the curve in level 2 hypoglycaemia, low blood glucose index, high blood glucose index, and percent time in glucose 70 to 180mg/dL were independently associated with CAN. Multivariable ROC analysis and dominance analysis revealed the highest relative contribution of percent time in level 2 hypoglycaemia to the independent associations between CGM parameters and presence of CAN. CGM-defined GV was associated with CAN independent of mean glucose in adults with type 1 diabetes. Among internationally standardized CGM parameters, those describing the degree of level 2 hypoglycaemia were the most significant contributors to this association.

Risk Factors of Hypoglycemia in Patients with Type 2 Diabetes Mellitus: A Study Based on Continuous Glucose Monitoring

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). 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. 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. 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.

Effect of 6 months of hybrid closed-loop insulin delivery in adults with type 1 diabetes: a randomised controlled trial protocol

IntroductionManual determination of insulin dosing largely fails to optimise glucose control in type 1 diabetes. Automated insulin delivery via closed-loop systems has improved glucose control in short-term studies. The objective...

Early effects of sodium-glucose co-transporter 2 inhibitors in type 2 diabetes: study based on continuous glucose monitoring

BackgroundInhibitors of sodium-glucose co-transporter 2 (SGLT2) have immediate glucose-lowering effects by promoting urinary glucose excretion, without altering insulin level. Only a few studies have evaluated blood glucose dynamics in the early period after administration. The present retrospective study was designed to determine the immediate effects of SGLT2 inhibitors on blood glucose dynamics.MethodsThe study subjects were 24 patients with type 2 diabetes whose blood glucose dynamics were evaluated with continuous glucose monitoring for 1 week before and after initiation of SGLT2 inhibitor therapy. Blood glucose dynamics were examined on days −1, 0 (treatment commencement day), 3, and 7 by evaluating different continuous glucose monitoring parameters and blood glucose before each meal. Furthermore, blood glucose levels at 1 and 2 h after each meal and daily urinary glucose levels were determined.ResultsA significant reduction in blood glucose levels 2 h after breakfast was observed between the day before treatment (249.8 mg/dL) and the day treatment started (218.9 mg/dL). The mean daily blood glucose level improved significantly from 201.4 to 142.3 mg/dL from the day the treatment started. Blood glucose variation also improved significantly by week 1, as demonstrated by changes in standard deviation and mean amplitude of glycemic excursions (from 39.6 to 31.7 and 106.9 to 87.4 mg/dL, respectively). The percent time at blood glucose <70 mg/dL remained unchanged while urinary glucose on day 7 correlated with minimum blood glucose level (r = 0.474, p = 0.022).ConclusionsThe results showed that the SGLT2 inhibitors lower blood glucose from 2 h after the first dose and improve blood glucose variation by week 1 after start of the treatment. Furthermore, SGLT2 inhibitors did not alter the incidence of hypoglycemic episodes at week 1, suggesting that SGLT2 protects against severe hypoglycemia by inhibiting urinary glucose excretion.

Determinants of hemoglobin A1c level in patients with type 2 diabetes after in-hospital diabetes education: A study based on continuous glucose monitoring.

Aims/IntroductionWe investigated the relationship between blood glucose profile at hospital discharge, evaluated by continuous glucose monitoring (CGM), and hemoglobin A1c (HbA1c) level at 12 weeks after discharge in patients with type 2 diabetes who received inpatient diabetes education.Materials and MethodsThis was a retrospective study. The participants were 54 patients with type 2 diabetes who did not change their medication after discharge. The mean blood glucose (MBG), standard deviation, coefficient of variation, mean postprandial glucose excursion, maximum blood glucose, minimum blood glucose, percentage of time with blood glucose at ≥180 mg/dL (time at ≥180), percentage of time with blood glucose at ≥140 mg/dL, and percentage of time with blood glucose at <70 mg/dL were measured at admission and discharge using CGM. The primary end‐point was the relationship between CGM parameters and HbA1c level at 12 weeks after discharge.ResultsThe HbA1c level at 12 weeks after discharge correlated with MBG level (r = 0.30, P = 0.029). Multivariate analysis showed that MBG level and disease duration were predictors of 12‐week HbA1c level. Multivariate logistic regression analysis was carried out considering goal achievement as a HbA1c level <7.0% 12 weeks after discharge. Disease duration and time at ≥180 were associated with goal achievement.ConclusionsThe present results suggested that blood glucose profile at discharge using CGM seems useful to predict HbA1c level after discharge in patients with type 2 diabetes who received inpatient diabetes education. Early treatment to improve MBG level, as well as postprandial hyperglycemia, is important to achieve strict glycemic control.

Post Stroke Dysglycemia and Acute Infarct Volume Growth: A Study Using Continuous Glucose Monitoring

Background: The aim of the present study was to clarify the effect of glucose profiles after stroke, which was assessed by a continuous glucose monitoring (CGM) device. Methods: Acute ischemic stroke patients within 24 h of onset were prospectively studied. CGM was performed for 72 h after admission. CGM parameters were evaluated as follows: (1) mean glucose level, (2) area under the curve (AUC) for glucose level >140 mg/dl and (3) SD of the glucose level. Infarct volume was measured at admission and 24 and 72 h after admission using diffusion-weighted imaging. CGM data and infarct volume growth were compared at 24 and 72 h. Results: Seventy-eight patients were enrolled in the present study. Spearman's rank correlation coefficients showed that both the mean glucose level (r = 0.433, p < 0.001 for 24 h; r = 0.308, p = 0.006 for 72 h) and AUC >140 mg/dl (r = 0.417, p < 0.001 for 24 h; r = 0.277, p = 0.014 for 72 h) were significantly correlated with acute infarct volume growth. The SD of the glucose level was associated with infarct volume growth at 24 h (r = 0.303, p = 0.007), but not 72 h (r = 0.195, p = 0.088). Conclusion: Post-stroke hyperglycemia was associated with infarct volume growth during the acute phase of ischemic stroke.

Declining ß-cell function is associated with the lack of long-range negative correlation in glucose dynamics and increased glycemic variability: A retrospective analysis in patients with type 2 diabetes

ObjectiveTo determine whether characteristics of glucose dynamics are reflections of β-cell function or rather of inadequate diabetes control. Materials/methodsWe analyzed historical liquid meal tolerance test (LMTT) and continuous glucose monitoring (CGM) data, which had been obtained from 56 non-insulin treated type 2 diabetic outpatients during withdrawal of antidiabetic drugs. Computed CGM parameters included detrended fluctuation analysis (DFA)-based indices, autocorrelation function exponent, mean amplitude of glycemic excursions (MAGE), glucose SD, and measures of glycemic exposure. The LMTT-based disposition index (LMTT-DI) calculated from the ratio of the area-under-the-insulin-curve to the area-under-the-glucose-curve and Matsuda index was used to assess relationships among β-cell function, glucose profile complexity, autocorrelation function, and glycemic variability. ResultsThe LMTT-DI was inverse linearly correlated with the short-range α1 and long-range scaling exponent α2 (r = −0.275 and −0.441, respectively, p < 0.01) such that lower glucose complexity was associated with better preserved insulin reserve, but it did not correlate with the autocorrelation decay exponent γ. By contrast, the LMTT-DI was strongly correlated with MAGE and SD (r = 0.625 and 0.646, both p < 0.001), demonstrating a curvilinear relationship between β-cell function and glycemic variability. On stepwise regression analyses, the LMTT-DI emerged as an independent contributor, explaining 20, 38, and 47% (all p < 0.001) of the variance in the long-range DFA scaling exponent, MAGE, and hemoglobin A1C, respectively, whereas insulin sensitivity failed to contribute independently. ConclusionsLoss of complexity and increased variability in glucose profiles are associated with declining β-cell reserve and worsening glycemic control.

Continuous Glucose Monitoring During Pregnancy in Women With Polycystic Ovary Syndrome

To estimate whether women with polycystic ovary syndrome (PCOS) will display ambient hyperglycemia (as measured by continuous glucose monitoring) early in pregnancy that progressively exacerbates with advancing pregnancy. This was a case-control study during singleton pregnancies of 17 women with PCOS and 17 healthy women. A 75-g oral glucose tolerance test (OGTT) followed by 24-hour continuous glucose monitoring was obtained four times throughout the pregnancy (visit 1: 6-10 weeks; visit 2: 12-16 weeks; visit 3: 24-28 weeks; visit 4: 34-38 weeks). Eight women with PCOS (47%) and two women in the control group (12%) developed gestational diabetes mellitus (GDM) as defined by World Health Organization criteria. Women with PCOS had a higher area under the curve for glucose during the OGTT at visit 1, visit 2, and visit 3, and for insulin at visit 1, compared with the control group. No differences were found between groups for any of the continuous glucose monitoring parameters studied. The free androgen index significantly decreased over the course of the study in both groups with a stronger decrease in the PCOS group at visit 1 (P=.003), visit 2 (P=.07), and visit 3 (P=.04). The difference in birth weight between groups was not significant: 3,346 g in women with PCOS and 3,633 g in women in the control group, and there was no perinatal morbidity. Women with PCOS are at increased risk for GDM, which manifests early in pregnancy and is detectable by OGTT. Serial 24-hour glucose monitoring did not reveal changes in glucose metabolism, although our sample size was small. Hyperandrogenemia improves with progressive pregnancy in women with PCOS. II.

Association of glycemic variability and the presence and severity of coronary artery disease in patients with type 2 diabetes

BackgroundGlucose variability is one of components of the dysglycemia in diabetes and may play an important role in development of diabetic vascular complications. The objective of this study was to assess the relationship between glycemic variability determined by a continuous glucose monitoring (CGM) system and the presence and severity of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM).MethodsIn 344 T2DM patients with chest pain, coronary angiography revealed CAD (coronary stenosis ≥ 50% luminal diameter narrowing) in 252 patients and 92 patients without CAD. Gensini score was used to assess the severity of CAD. All participants' CGM parameters and biochemical characteristics were measured at baseline.ResultsDiabetic patients with CAD were older, and more were male and cigarette smokers compared with the controls. Levels of the mean amplitude of glycemic excursions (MAGE) (3.7 ± 1.4 mmol/L vs. 3.2 ± 1.2 mmol/L, p < 0.001), postprandial glucose excursion (PPGE) (3.9 ± 1.6 mmol/L vs. 3.6 ± 1.4 mmol/L, p = 0.036), serum high-sensitive C-reactive protein (hs-CRP) (10.7 ± 12.4 mg/L vs. 5.8 ± 6.7 mg/L, p < 0.001) and creatinine (Cr) (87 ± 23 mmol/L vs. 77 ± 14 mmol/L, p < 0.001) were significantly higher in patients with CAD than in patients without CAD. Gensini score closely correlated with age, MAGE, PPGE, hemoglobin A1c (HbA1c), hs-CRP and total cholesterol (TC). Multivariate analysis indicated that age (p < 0.001), MAGE (p < 0.001), serum levels of HbA1c (p = 0.022) and hs-CRP (p = 0.005) were independent determinants for Gensini score. Logistic regression analysis revealed that MAGE ≥ 3.4 mmol/L was an independent predictor for CAD. The area under the receiver-operating characteristic curve for MAGE (0.618, p = 0.001) was superior to that for HbA1c (0.554, p = 0.129).ConclusionsThe intraday glycemic variability is associated with the presence and severity of CAD in patients with T2DM. Effects of glycemic excursions on vascular complications should not be neglected in diabetes.

Relationship between serum osteocalcin and glycaemic variability in Type 2 diabetes

1. Recent reports have described the role of osteocalcin in glucose metabolism and glycaemic variability has been proven to be associated with an increased risk of diabetes complications. However, the relationship between osteocalcin and glycaemic variability remains unclear. The aim of the present study was to examine the relationship between serum osteocalcin and glycaemic variability, as determined by a continuous glucose monitoring (CGM) system in patients with Type 2 diabetes mellitus (T2DM). 2. Fifty-nine T2DM patients with glycosylated haemoglobin (HbA1c) levels between 7.0% and 10.9% were recruited to the present study. Biochemical information and CGM parameters were collected at baseline and after 8 weeks of antihyperglycaemic therapy (either sulphonylurea, sulphonylurea + an α-glucosidase inhibitor or insulin + metformin combination therapy). 3. Compared with baseline, serum osteocalcin increased significantly (P = 0.014), whereas parameters related to glucose variability, including the mean amplitude of glycaemic excursions (MAGE) and the standard deviation of blood glucose values, decreased significantly (P < 0.001) after the 8 week treatment period. At baseline, there was a positive correlation between serum osteocalcin levels and fasting C-peptide levels (P = 0.004) and homeostatic model assessment of β-cell function (P = 0.048), but a negative correlation between serum osteocalcin levels and fasting plasma glucose (P = 0.023), HbA1c (P = 0.020), glycated albumin (P = 0.019) and 24 h mean blood glucose (P < 0.001). Multiple stepwise regression analysis indicated that baseline osteocalcin was the single parameter that best predicted the change in MAGE (β = -0.122; P = 0.039). 4. In conclusion, serum osteocalcin concentrations increased with improved glucose control. High initial osteocalcin levels were associated with subsequent improvements in glucose variability during glucose-lowering treatment.

Insulin Resistance, Defective Insulin-Mediated Fatty Acid Suppression, and Coronary Artery Calcification in Subjects With and Without Type 1 Diabetes

OBJECTIVETo assess insulin action on peripheral glucose utilization and nonesterified fatty acid (NEFA) suppression as a predictor of coronary artery calcification (CAC) in patients with type 1 diabetes and nondiabetic controls.RESEARCH DESIGN AND METHODSInsulin action was measured by a three-stage hyperinsulinemic-euglycemic clamp (4, 8, and 40 mU/m2/min) in 87 subjects from the Coronary Artery Calcification in Type 1 Diabetes cohort (40 diabetic, 47 nondiabetic; mean age 45 ± 8 years; 55% female).RESULTSPeripheral glucose utilization was lower in subjects with type 1 diabetes compared with nondiabetic controls: glucose infusion rate (mg/kg FFM/min) = 6.19 ± 0.72 vs. 12.71 ± 0.66, mean ± SE, P < 0.0001, after adjustment for age, sex, BMI, fasting glucose, and final clamp glucose and insulin. Insulin-induced NEFA suppression was also lower in type 1 diabetic compared with nondiabetic subjects: NEFA levels (μM) during 8 mU/m2/min insulin infusion = 370 ± 27 vs. 185 ± 25, P < 0.0001, after adjustment for age, sex, BMI, fasting glucose, and time point insulin. Lower glucose utilization and higher NEFA levels, correlated with CAC volume (r = −0.42, P < 0.0001 and r = 0.41, P < 0.0001, respectively) and predicted the presence of CAC (odds ratio [OR] = 0.45, 95% CI = 0.22–0.93, P = 0.03; OR = 2.4, 95% CI = 1.08–5.32, P = 0.032, respectively). Insulin resistance did not correlate with GHb or continuous glucose monitoring parameters.CONCLUSIONSType 1 diabetic patients are insulin resistant compared with nondiabetic subjects, and the degree of resistance is not related to current glycemic control. Insulin resistance predicts the extent of coronary artery calcification and may contribute to the increased risk of cardiovascular disease in patients with type 1 diabetes as well as subjects without diabetes.

Relationship between Clinical Markers of Glycemia and Glucose Excursion Evaluated by Continuous Glucose Monitoring (CGM).

In order to evaluate the relationship between clinical markers of glycemia and glucose excursion, we performed 48-hour continuous glucose monitoring (CGM) in 43 diabetic patients. For the clinical markers, HbA(1c), glycoalbumin (GA), and 1,5-anhydroglucitol (1,5-AG) were measured, and for the parameters of glucose excursion from CGM, average glucose (AG), standard deviation of glucose (SD), the area under the curve for glucose levels >180 mg/dL (AUC(>180)), and the difference between the maximum and minimum glucose levels during 48 hours (DeltaG(48hr)) were analyzed. All patients were treated without any changes of the dosages of oral anti-diabetic agents or insulin for at least the previous 3 months with coefficient of variation (CV) of HbA(1c) less than 4 %. In results, while HbA(1c) did not show any single correlation with AG, SD, AUC(>180), or DeltaG(48hr), both GA and 1,5-AG were significantly related to all these parameters. Furthermore, GA significantly correlated to all CGM parameters, and SD significantly correlated to GA in multiple regression analyses. These results suggest that GA may be a different marker from HbA(1c) for diabetic complications, because GA, but not HbA(1c), may reflect not only short-term average glucose but also fluctuation of glucose.

Reference Values for Continuous Glucose Monitoring in Chinese Subjects

OBJECTIVEThe widespread clinical application of continuous glucose monitoring (CGM) is limited by the lack of generally accepted reference values. This multicenter study aims to establish preliminary normal reference values for CGM parameters in a sample of healthy Chinese subjects.RESEARCH DESIGN AND METHODSA total of 434 healthy individuals with normal glucose regulation completed a 3-day period of glucose monitoring using a CGM system. The 24-h mean blood glucose (24-h MBG) and the percentage of time that subjects' blood glucose levels were ≥140 mg/dl (PT140) and ≤70 mg/dl (PT70) within 24 h were analyzed.RESULTSThere was excellent compliance of finger stick blood glucose values with CGM measurements for subjects. Among the 434 subjects, the daily blood glucose varied from 76.9 ± 11.3 to 144.2 ± 23.2 mg/dl. The 24-h MBG, PT140, and PT70 were 104 ± 10 mg/dl, 4.1 ± 5.8%, and 2.4 ± 5.3%, respectively. As for these parameters, no significant differences were found between men and women. The 95th percentile values were adopted as the upper limits of CGM parameters, which revealed 119 mg/dl (6.6 mmol/l) for 24-h MBG, 17.1% for PT140, and 11.7% for PT70.CONCLUSIONSWe recommend a 24-h MBG value <119 mg/dl, PT140 <17% (4 h), and PT70 <12% (3 h) as normal ranges for the Chinese population.