Mean Amplitude Of Glucose Excursions Research Articles

Effects of glucagon-like peptide-1 receptor agonists on glycated haemoglobin and continuous glucose monitoring metrics as adjunctive therapy to insulin in adults with type 1 diabetes: A meta-analysis of randomized controlled trials.

To conduct a meta-analysis of randomized controlled trials (RCTs) to evaluate the effect of glucagon-like peptide-1 receptor agonists (GLP-1RAs) on glycated haemoglobin (HbA1c) and continuous glucose monitoring (CGM) metrics as an adjunct to insulin therapy in adults with type 1 diabetes mellitus (T1D). A systematic literature search was conducted through Medline (via PubMed), Cochrane Library, and Google Scholar up to 27 May 2024. Dual-independent study selection, data extraction, and quality assessment were performed. Results were summarized using random-effects meta-analysis. Six RCTs were identified, involving a total of 378 individuals with T1D. The use of GLP-1RAs in addition to standard insulin therapy was associated with a significant reduction in HbA1c (mean difference [MD] -0.21%, 95% confidence interval [CI] -0.36 to -0.06; p = 0.007) and a similar time in range (TIR) compared to placebo (MD -0.22%, 95% CI -2.39 to 1.95; p = 0.84). GLP-1RA therapy resulted in a significantly higher time below range (MD 1.13%, 95% CI 0.50 to 1.76; p < 0.001) and a lower time above range compared with placebo (MD -1.83%, 95% CI -2.51 to -1.15; p < 0.001). Nonsignificant differences were noted for the secondary outcomes, including the mean amplitude of glucose excursion, continuous overall net glycaemic action for 60 min, mean daily glucose, coefficient of variation, and mean standard deviation of weekly glucose levels. Our findings suggest that, in individuals with T1D, add-on therapy with GLP-1RAs does not confer significant benefits in terms of CGM metrics and is associated with a longer time below the target glycaemic range.

Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants

BackgroundContinuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis.MethodsThis cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree.ResultsMean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor.ConclusionsHigher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

Cross-sectional association of continuous glucose monitoring-derived metrics with cerebral small vessel disease in older adults with type 2 diabetes.

To examine cross-sectional associations between continuous glucose monitoring (CGM)-derived metrics and cerebral small vessel disease (SVD) in older adults with type 2 diabetes. In total, 80 patients with type 2 diabetes aged ≥70 years were analysed. Participants underwent CGM for 14 days. From the CGM data, we derived mean sensor glucose, percentage glucose coefficient of variation, mean amplitude of glucose excursion, time in range (TIR, 70-180 mg/dl), time above range (TAR) and time below range metrics, glycaemia risk index and high/low blood glucose index. The presence of cerebral SVD, including lacunes, microbleeds, enlarged perivascular spaces and white matter hyperintensities, was assessed, and the total number of these findings comprised the total cerebral SVD score (0-4). Ordinal logistic regression analyses were performed to examine the association of CGM-derived metrics with the total SVD score. The median SVD score was 1 (interquartile range 0-2). Higher hyperglycaemic metrics, including mean sensor glucose, TAR >180 mg/dl, TAR >250 mg/dl, and high blood glucose index and glycaemia risk index, were associated with a higher total SVD score. In contrast, a higher TIR (per 10% increase) was associated with a lower total SVD score (odds ratio 0.73, 95% confidence interval 0.56-0.95). Glycated haemoglobin, percentage glucose coefficient of variation, mean amplitude of glucose excursions, time below range and low blood glucose index were not associated with total cerebral SVD scores. The hyperglycaemia metrics and TIR, derived from CGM, were associated with cerebral SVD in older adults with type 2 diabetes.

Early Dinner Improves the Glycemic Profile in Habitual Late Eaters With Uncontrolled Type 2 Diabetes Mellitus in the Short Term.

Background Late dinner (LD) can worsen the glucose profile in type 2 diabetes (T2D). We assessed the short-term effect of early dinner (ED) on glycemic control in habitual late eaters with uncontrolled T2D. Methodology This interventional, single-arm, within-group trial recruited 10 habitual late eaters with uncontrolled T2D (glycosylated hemoglobin: 7-9% and either fasting plasma glucose (FPG): ≥140 mg/dl or post-prandial plasma glucose: ≥200 mg/dl). They had their usual LD (beyond 22:00 hours) on Days 0-3 and ED (before 20:00 hours) on Days 4-10. Continuous glucose monitoring system (CGMS) parameters, two-hour post-dinner, and fasting (10-hour post-dinner) investigations were analyzed. Bedtime hunger was assessed using a Labeled Magnitude Satiety Scale. Results The mean dinner time was reduced from 22:28 hours to 19:29 hours. CGMS revealed that ED lowered the 10-hour post-dinner incremental area under the curve (22,587.9 ± 5,168.3 mg/dl×mins vs. 15,886.3 ± 4,288.7 mg/dl×mins, P < 0.002), 10-hour post-dinner average blood glucose (ABG) (137.5 ± 9.3 mg/dl vs. 125 ± 7.9 mg/dl, P < 0.002), 24-hour ABG (132.2 ± 7.5 mg/dl vs. 124.8 ± 5.4 mg/dl, P = 0.037), and night mean amplitude of glucose excursion (83.7 ± 5.8 mg/dl vs. 69.3 ± 7.5 mg/dl, P = 0.027). ED also reduced FPG (119.8 ± 7.3 mg/dl vs. 105.2 ± 5.7 mg/dl, P = 0.015), fasting insulin (15.0 ± 4.3 µIU/ml vs. 9.7 ± 2.7 µIU/ml, P < 0.002), and HOMA-IR (4.36 ± 1.2 vs. 2.56 ± 0.79, P < 0.002). Post-dinner glucose, insulin, and inflammatory markers were unchanged. Bedtime hunger increased significantly on Days 4 and 5 but returned to baseline by Day 10. Conclusions A simple modification of dinner time in habitual late eaters with uncontrolled T2D improves FPG, glycemic control, and insulin resistance in the short term.

Glycemic variability is associated with sural nerve conduction velocity in outpatients with type2diabetes: Usefulness of a new point-of-care device for nerve conduction studies.

Although several studies have shown the association between continuous glucose monitoring (CGM)-derived glycemic variability (GV) and diabetic peripheral neuropathy, no studies have focused on outpatients or used NC-stat®/DPNCheck™, a new point-of-care device for nerve conduction study (NCS). We investigated the association between CGM-derived GV and NCS using DPNCheck™ in outpatients with type 2 diabetes, and further analyzed the difference in results between patients with and without well-controlled HbA1c levels. All outpatients with type 2 diabetes using the CGM device (FreeStyle Libre Pro®) between 2017 and 2022 were investigated. Sural nerve conduction was evaluated by sensory nerve action potential (SNAP) amplitude and sensory conduction velocity (SCV) using DPNCheck™. Associations of CGM-derived GV metrics with SNAP amplitude and SCV were investigated. In total, 304 outpatients with type 2 diabetes were included. In a linear regression model, most CGM-derived GV metrics except for the mean amplitude of glucose excursion and low blood glucose index were significantly associated with SCV, but not with SNAP amplitude. The significant associations of most CGM-derived GV metrics with SCV remained after adjustment for possible confounding factors, but not after adjustment for glycated hemoglobin (HbA1c). Most CGM-derived GV metrics were significantly associated with SCV after adjustment for HbA1c in patients with a HbA1c ≤ 6.9%, but not in those with a HbA1c ≥ 7.0%. In outpatients with type 2 diabetes, multiple CGM-derived GV metrics were significantly associated with SCV obtained by DPNCheck™. GVmay have independent impacts on peripheral nerve function, particularly in patients with well-controlled HbA1c levels.

Diet and Meal Pattern Determinants of Glucose Levels and Variability in Adults with and without Prediabetes or Early-Onset Type 2 Diabetes: A Pilot Study.

This observational pilot study examined the association between diet, meal pattern and glucose over a 2-week period under free-living conditions in 26 adults with dysglycemia (D-GLYC) and 14 with normoglycemia (N-GLYC). We hypothesized that a prolonged eating window and late eating occasions (EOs), along with a higher dietary carbohydrate intake, would result in higher glucose levels and glucose variability (GV). General linear models were run with meal timing with time-stamped photographs in real time, and diet composition by dietary recalls, and their variability (SD), as predictors and glucose variables (mean glucose, mean amplitude of glucose excursions [MAGE], largest amplitude of glucose excursions [LAGE] and GV) as dependent variables. After adjusting for calories and nutrients, a later eating midpoint predicted a lower GV (β = -2.3, SE = 1.0, p = 0.03) in D-GLYC, while a later last EO predicted a higher GV (β = 1.5, SE = 0.6, p = 0.04) in N-GLYC. A higher carbohydrate intake predicted a higher MAGE (β = 0.9, SE = 0.4, p = 0.02) and GV (β = 0.4, SE = 0.2, p = 0.04) in N-GLYC, but not D-GLYC. In summary, our data suggest that meal patterns interact with dietary composition and should be evaluated as potential modifiable determinants of glucose in adults with and without dysglycemia. Future research should evaluate causality with controlled diets.

Effect of sodium-glucose cotransporter-2 inhibitors on continuous glucose monitoring metrics, as adjunctive to insulin in adults with type 1 diabetes mellitus: a meta-analysis of randomized controlled trials

AimsThis meta-analysis of randomized controlled trials (RCTs) aimed to evaluate the effect of sodium-glucose cotransporter-2 inhibitors (SGLT2is) on continuous glucose monitoring metrics as adjunctive to insulin in adults with type 1 diabetes mellitus (T1D). MethodsA systematic literature search was conducted through Medline (via PubMed), Cochrane Library and Google Scholar until October 25, 2023. Dual-independent study selection, data extraction and quality assessment were conducted. Results were summarized with random effects meta-analysis. ResultsEight RCTs were identified, involving a total of 2310 T1D patients. The use of SGLT2is on top of standard insulin therapy was associated with a significantly higher time in range (TIR) compared to placebo (mean difference (MD) 9.7 %; 95 % confidence interval (CI) [8.3, 1.11]; P < 0.001). The time above range was significantly lower in patients receiving SGLT2is (MD -8.71 %; 95 % CI [−11.62, −5.79]; P < 0.001), whereas no difference was observed regarding the time below range (TBR) (MD 0.34 %; 95 % CI [−0.17, 0.85]; P = 0.19). A significantly lower sensor-recorded mean daily glucose was noted in the group receiving SGLT2is (MD -16.55 mg/dL; 95 % CI [−19.82, −13.29]; P < 0.001). When considering the metrics of glucose variability, SGLT2is demonstrated a significant favorable effect on the mean amplitude of glucose excursions (MD -16.92 mg/dL; 95 % CI [−25.31, −8.13]; P < 0.001) and the mean standard deviation of weekly glucose levels (MD -7.67 mg/dL; 95 % CI [−11, −4.35]; P < 0.001). No significant effect was observed concerning the coefficient of variation (MD -1 %; 95 % CI [−2.39, 0.4]; P = 0.16). Regarding safety outcomes, SGLT2is were significantly linked to higher odds of diabetic ketoacidosis compared to insulin alone (OR 3.18; 95 % CI [1.79, 5.66]; P < 0.001), with no significant impact on severe hypoglycemia events (OR 1; 95 % CI [0.54, 1.85]; P = 0.1). ConclusionOur findings suggest that in individuals with T1D, adjunct therapy with SGLT2is provides a significant benefit in terms of TIR and reduced glucose variability, without an increase in TBR.

The effect of sodium-glucose cotransporter 2 inhibitors as an adjunct to insulin in patients with type 1 diabetes assessed by continuous glucose monitoring: A systematic review and meta-analysis

AimsPatients undergoing insulin-based therapy for type 1 diabetes often experience poor glycemic control characterized by significant fluctuations. This study was undertaken to analyze the effect of sodium-glucose cotransporter 2 inhibitors (SGLT2Is), as an adjunct to insulin, on time in range (TIR) and glycemic variability in patients with type 1 diabetes, using continuous glucose monitoring (CGM). In addition, we examined which type of SGLT2I yielded a superior effect compared to others. MethodsWe conducted a comprehensive search of PubMed, EMBASE, the Cochrane Library, Web of Science, and clinical trial registry websites, retrieving all eligible randomized clinical trials (RCTs) published up until February 2023. We analyzed the mean TIR, mean amplitude of glucose excursions (MAGE), mean daily glucose (MDG), diabetic ketoacidosis (DKA), standard deviation (SD), total insulin dose, and severe hypoglycemia to evaluate the efficacy and safety of SGLT2Is. A random-effects model was also employed. ResultsThis study encompassed 15 RCTs. The meta-analysis revealed that the use of SGLT2Is as an adjuvant therapy to insulin led to a significant increase in TIR (MD = 10.78, 95%CI = 9.33–12.23, I2 = 42 %, P < 0.00001) and a decrease in SD (MD = −0.38, 95%CI = −0.50 to −0.26, I2 = 0 %, P < 0.00001), MAGE (MD = −0.92, 95%CI = −1.17 to −0.67, I2 = 19 %, P < 0.00001), MDG(MD = −1.01, 95%CI = −1.32 to −0.70, I2 = 48 %, P < 0.00001), and total insulin dose (MD = −5.81, 95%CI = −7.81 to −3.82, I2 = 32 %, P < 0.00001). No significant increase was observed in the rate of severe hypoglycemia (RR = 1.04, 95 % CI = 0.76–1.43, P = 0.80). However, SGLT2I therapy was associated with increased DKA occurrence (RR = 2.79, 95 % CI = 1.42–5.48; P = 0.003, I2 = 16 %). In addition, the subgroup analyses based on the type of SGLT2Is revealed that dapagliflozin might exhibit greater efficacy compared to other SGLT2Is across most outcomes. ConclusionsSGLT2Is exhibited a positive effect on improving blood glucose level fluctuations. Subgroup analysis showed that dapagliflozin appeared to have more advantages. However, giving due consideration to preventing adverse effects, particularly DKA, is paramount. RegistrationProspero CRD42023408276.

Effects of reducing free sugars on 24-hour glucose profiles and glycemic variability in subjects without diabetes.

The Western diet, especially beverages and high processed food products, is high in sugars which are associated with the development of obesity and diabetes. The reduction of refined carbohydrates including free and added sugars improves glycemic control in individuals with diabetes, but the data regarding effects in subjects without diabetes are limited. This study aimed to evaluate the effects of reducing free sugar intake on 24-h glucose profiles and glycemic variability using continuous glucose monitoring (CGM). In the randomized controlled study, 21 normal weight and overweight/obese subjects (BMI 18-40 kg/m2) without diabetes were assigned to a 4-week reduced-sugar (RS) diet or control diet after a 2-week baseline phase. During the baseline phase, all participants were advised not to change their habitual diet. During the intervention phase, RS participants were asked to avoid added sugar and white flour products, whereas participants of the control group were requested to proceed their habitual diet. Anthropometric parameters and HbA1c were assessed before and at the end of the intervention phase. Interstitial glucose was measured using continuous glucose monitoring (CGM), and the food intake was documented by dietary records for 14 consecutive days during the baseline phase and for the first 14 consecutive days during the intervention phase. Mean 24-h glucose as well as intra- and inter-day indices of glucose variability, i.e., standard deviation (SD) around the sensor glucose level, coefficient of variation in percent (CV), mean amplitude of glucose excursions (MAGE), continuous overlapping net glycemic action (CONGA), and mean absolute glucose (MAG), were calculated for the baseline and intervention phases. During the intervention, the RS group decreased the daily intake of sugar (i.e., -22.4 ± 20.2 g, -3.28 ± 3.61 EN %), total carbohydrates (-6.22 ± 6.92 EN %), and total energy intake (-216 ± 108 kcal) and increased the protein intake (+2.51 ± 1.56 EN %) compared to the baseline values, whereby this intervention-induced dietary changes differed from the control group. The RS group slightly reduced body weight (-1.58 ± 1.33 kg), BMI, total fat, and visceral fat content and increased muscle mass compared to the baseline phase, but these intervention-induced changes showed no differences in comparison with the control group. The RS diet affected neither the 24-h mean glucose levels nor intra- and inter-day indices of glucose variability, HbA1c, or diurnal glucose pattern in the within- and between-group comparisons. The dietary reduction of free sugars decreases body weight and body fat which may be associated with reduced total energy intake but does not affect the daily mean glucose and glycemic variability in individuals without diabetes. German Clinical Trials Register (DRKS); identifier: DRKS00026699.

Effects of Glycemic Variability on Regulatory T Cells in Patients with Type 2 Diabetes and Kidney Disease.

To investigate the pathogenesis of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM), we evaluated the effects of short-term glycemic variability (GV) on the profile of T cell subpopulations. A total of 47 T2DM patients with normoalbuminuria, 47 microalbuminuria, and 49 macroalbuminuria were enrolled. The continuous glucose monitoring (CGM) determined the GV of enrolled patients. Flow cytometry was used to determine the proportion of T cell subpopulations. The frequency of T helper (Th) 17 and Th1 cells significantly increased while regulatory T cells (Tregs) significantly decreased in the macroalbuminuria group compared to normoalbuminuria and microalbuminuria groups (P < 0.01). The suppressive function of Tregs was significantly lower in the macroalbuminuria group than the normoalbuminuria group (P < 0.05). Compared with the normoalbuminuria group, the mean amplitude of glucose excursions (MAGE) of the macroalbuminuria group was significantly higher (P<0.05). Furthermore, there were negative associations between the proportion of Tregs and MAGE. Increased GV could decrease the proportion of Tregs and may impair their function. This may lead to increases in Th1 and Th17 cells, and some inflammatory cytokines, which might contribute to the development and progression of DKD in T2DM.

Time in range as a useful marker for evaluating retinal functional changes in diabetic retinopathy patients.

To elucidate the relationship between macular sensitivity and time in range (TIR) obtained from continuous glucose monitoring (CGM) measures in diabetic patients with or without diabetic retinopathy (DR). This was a cross-sectional study including 100 eyes of non-DR patients and 60 eyes of DR patients. An advanced microperimetry was used to quantitate the retinal mean sensitivity (MS) and fixation stability in central macula. TIR of 3.9-10.0 mmol/L was evaluated with CGM. Pearson coefficient analysis and multiple linear regression analysis were used to assess the correlation between TIR and retinal sensitivity. In a comparison of non-DR patients, significant differences (P<0.05) were found in HbA1c, TIR, coefficient of variation (CV), standard deviation of blood glucose (SDBG) and mean amplitude of glucose excursion (MAGE) values in DR patients. Besides, those DR patients had significantly poor best-corrected visual acuity (BCVA, logMAR, P=0.001). In terms of microperimetry parameters, retinal mean sensitivity (MS) and the percentages of fixation points located within 2° and 4° diameter circles were significantly decreased in the DR group (P<0.001, P<0.001, P=0.02, respectively). The bivariate contour ellipse area (BCEA) encompassing 68.2%, 95.4%, 99.6% of fixation points were all significantly increased in the DR group (P=0.01, P=0.006, P=0.01, respectively). Correlation analysis showed that MS were significantly correlated with HbA1c (P=0.01). TIR was positively correlated with MS (r=0.23, P=0.01). SDBG was negatively correlated with MS (r=-0.24, P=0.01) but there was no correlation between CV and MAGE with MS (P>0.05). A multivariable linear regression analysis was performed to prove that TIR and SDBG were both independent risk factors for MS reduction in the DR group. TIR is correlated with retinal MS reduction in DR patients, suggesting a useful option for evaluating DR progression.

Continuous glucose monitoring-derived glycemic metrics and adverse pregnancy outcomes among women with gestational diabetes: a prospective cohort study

Continuous glucose monitoring (CGM) has shown potential in improving maternal and neonatal outcomes in individuals with type 1/2 diabetes, but data in gestational diabetes mellitus (GDM) is limited. We aimed to explore the relationship between CGM-derived metrics during pregnancy and pregnancy outcomes among women with GDM. We recruited 1302 pregnant women with GDM at a mean gestational age of 26.0 weeks and followed them until delivery. Participants underwent a 14-day CGM measurement upon recruitment. The primary outcome was any adverse pregnancy outcome, defined as having at least one of the outcomes: preterm birth, large-for-gestational-age (LGA) birth, fetal distress, premature rupture of membranes, and neonatal intensive care unit (NICU) admission. The individual outcomes included in the primary outcome were considered as secondary outcomes. We conducted multivariable logistic regression to evaluate the association of CGM-derived metrics with these outcomes. Per 1-SD difference in time above range (TAR), glucose area under the curve (AUC), nighttime mean blood glucose (MBG), daytime MBG, and daily MBG was associated with higher risk of any adverse pregnancy outcome, with odds ratio: 1.22 (95% CI 1.08-1.36), 1.22 (95% CI 1.09-1.37), 1.18 (95% CI 1.05-1.32), 1.21 (95% CI 1.07-1.35), and 1.22 (95% CI 1.09-1.37), respectively. Time in range, TAR, AUC, nighttime MBG, daytime MBG, daily MBG, and mean amplitude of glucose excursions were positively associated, while time blow range was inversely associated with the risk of LGA. Additionally, higher value for TAR was associated with higher risk of NICU admission. We further summarized the potential thresholds of TAR (2.5%) and daily MBG (4.8mmol/L) to distinguish individuals with and without any adverse pregnancy outcome. The CGM-derived metrics may help identify individuals at higher risk of adverse pregnancy outcomes. These CGM biomarkers could serve as potential new intervention targets to maintain a healthy pregnancy status among women with GDM. National Key R&D Program of China, National Natural Science Foundation of China, and Westlake Laboratory of Life Sciences and Biomedicine.

Faster-acting insulin aspart reduces glycaemic variability in sensor-augmented pump treated type 1 diabetes patients

AimTo evaluate the effect of faster aspart over glycaemic variability in type 1 diabetes (T1D) patients treated with sensor-augmented pump (SAP) in a real-world scenario. MethodsObservational study with SAP-treated adult T1D patients treated with faster aspart for three months. The primary endpoint was the mean amplitude of glucose excursions (MAGE). ResultsFifty patients were treated with faster aspart. Eleven patients (23%) withdrew during the follow-up mainly due to worsening of diabetes control (9 patients). Mean age was 41.2 yrs. (range 21–59) and T1D duration 22.4±10.0 yrs. Mean SAP treatment duration was 3.6±3.1 yrs. We detected a reduction of -7.0 (95% CI −1.1, −12.9; p=0.021) in MAGE at the end of the study. Other glycemic variability indices were also improved: standard deviation of mean interstitial glucose (−3mg/dl; 95% CI, −1, −5; p=0.01), CONGA4 (−2.2; 95% CI −0.3, −4.2; p=0.029), CONGA6 (−2.6; 95% CI −0.6, −4.6; p=0.011), GRADE (−0.5; 95% CI −0.1, −0.9; p=0.022), HBGI (−0.7; 95% CI −0.2, −1.3; p=0.013), J-index (−2.9; 95% CI −0.7, −5.0; p=0.011) and MODD (−5.7; 95% CI −1.7, −9.7; p=0.006). A slight reduction in mean glucose management indicator was also detected (−0.14%; 95% CI, −0.02, −0.27; −1.4mmol/mol; 95% CI −0.1, −3.3; p=0.03). ConclusionsIn SAP-treated T1D patients, faster aspart insulin was associated with reduced glycaemic variability, but also a high percentage of dropouts due to worsened glycaemic control. NCT04233203.

Association of carotid atherosclerosis and peripheral artery disease in patients with type 2 diabetes: risk factors and biomarkers

BACKGROUND: Carotid atherosclerosis (CA) and lower extremity peripheral artery disease (PAD) is a common and potentially life-threatening comorbidity in diabetes.AIM: to determine risk factors and biomarkers of the association of CA and PAD in patients with type 2 diabetes.MATERIALS AND METHODS: A single-center cross-sectional comparative study was carried out. Three hundred ninety one patients with type 2 diabetes were included. Duplex ultrasound of carotid and low limb arteries, screening/monitoring of diabetic complications and associated diseases, and assessment of glycemic control, biochemical and coagulation parameters were performed. Factors involved in vascular wall remodeling, including calponin-1, relaxin, L-citrulline, matrix metalloproteinase-2 and -3, were measured in blood serum by ELISA.RESULTS: The signs of CA and PAD were observed in 330 and 187 patients respectively. In 178 patients, both CA and PAD were revealed. The risk of combined involvement of carotid and lower extremity arteries was higher in patients with diabetic retinopathy (OR=2.57, p&lt;0.001), chronic kidney disease (OR=4.48, p&lt;0.001), history of myocardial infarction (OR=5.09, p&lt;0.001), coronary revascularization (OR=4.31, p&lt;0.001) or cerebrovascular accident (OR=3.07, p&lt;0.001). In ROC-analysis, age ≥65.5 years (OR=3.43, p&lt;0.001), waist-to-hip ratio ≥0.967 (OR=3.01, p=0.001), diabetes duration ≥12.5 years (OR=3.7, p&lt;0.001), duration of insulin therapy ≥4.5 years (OR=3.05, p&lt;0.001), duration of arterial hypertension ≥16.5 years (OR=1.98, p=0.002), serum L-citrulline ≥68 µmol/l (OR=3.82, p=0.003), and mean amplitude of glucose excursions ≥3.72 mmol/l (OR=1.79, p=0.006) were the risk factors for atherosclerosis of two vascular beds. In multivariate logistic regression analysis, age, diabetes duration and waist-to-hip ratio were independent risk factors for association of CA and PAD (p=0.005, p=0.0003, and p=0.004 respectively).CONCLUSION: In subjects with type 2 diabetes, carotid and lower extremity atherosclerotic disease is associated with age, diabetes duration, abdominal obesity, microvascular and macrovascular complications, glucose variability, and high serum levels of L-citrulline.

Regimen comprising GLP-1 receptor agonist and basal insulin can decrease the effect of food on glycemic variability compared to a pre-mixed insulin regimen

BackgroundIncreasing evidence suggests that glucagon-like peptide 1 (GLP-1) receptor agonists (RA) can stabilize glycemic variability (GV) and interfere with eating behavior. This study compared the impact of insulin, GLP-1 RA, and dietary components on GV using professional continuous glucose monitoring (CGM).MethodsPatients with type 2 diabetes underwent CGM before and after switching from a twice-daily pre-mixed insulin treatment regimen to a GLP-1 RA (liraglutide) plus basal insulin regimen. The dietary components were recorded and analyzed by a certified dietitian. The interactions between the medical regimen, GV indices, and nutrient components were analyzed.ResultsSixteen patients with type 2 diabetes were enrolled in this study. No significant differences in the diet components and total calorie intake between the two regimens were found. Under the pre-mixed insulin regimen, for increase in carbohydrate intake ratio, mean amplitude of glucose excursion (MAGE) and standard deviation (SD) increased; in contrast, under the new regimen, for increase in fat intake ratio, MAGE and SD decreased, while when the protein intake ratio increased, the coefficient of variation (CV) decreased. The impact of the food intake ratio on GV indices disappeared under the GLP-1 RA regimen. After switching to the GLP-1 RA regimen, the median MAGE, SD, and CV values decreased significantly. However, the significant difference in GV between the two regimens decreased during the daytime.ConclusionA GLP-1 RA plus basal insulin regimen can stabilize GV better than a regimen of twice-daily pre-mixed insulin, especially in the daytime, and can diminish the effect of food components on GV.

Analysis of detrended fluctuation function derived from continuous glucose monitoring may assist in distinguishing latent autoimmune diabetes in adults from T2DM.

BackgroundWe aimed to explore the performance of detrended fluctuation function (DFF) in distinguishing patients with latent autoimmune diabetes in adults (LADA) from type 2 diabetes mellitus (T2DM) with glucose data derived from continuous glucose monitoring.MethodsIn total, 71 LADA and 152 T2DM patients were enrolled. Correlations between glucose parameters including time in range (TIR), mean glucose, standard deviation (SD), mean amplitude of glucose excursions (MAGE), coefficient of variation (CV), DFF and fasting and 2-hour postprandial C-peptide (FCP, 2hCP) were analyzed and compared. Receiver operating characteristics curve (ROC) analysis and 10-fold cross-validation were employed to explore and validate the performance of DFF in diabetes classification respectively.ResultsPatients with LADA had a higher mean glucose, lower TIR, greater SD, MAGE and CV than those of T2DM (P<0.001). DFF achieved the strongest correlation with FCP (r = -0.705, P<0.001) as compared with TIR (r = 0.485, P<0.001), mean glucose (r = -0.337, P<0.001), SD (r = -0.645, P<0.001), MAGE (r = -0.663, P<0.001) and CV (r = -0.639, P<0.001). ROC analysis showed that DFF yielded the greatest area under the curve (AUC) of 0.862 (sensitivity: 71.2%, specificity: 84.9%) in differentiating LADA from T2DM as compared with TIR, mean glucose, SD, MAGE and CV (AUC: 0.722, 0.650, 0.800, 0.820 and 0.807, sensitivity: 71.8%, 47.9%, 63.6%, 72.7% and 78.8%, specificity: 67.8%, 83.6%, 80.9%, 80.3% and 72.4%, respectively). The kappa test indicated a good consistency between DFF and the actual diagnosis (kappa = 0.551, P<0.001). Ten-fold cross-validation showed a stable performance of DFF with a mean AUC of 0.863 (sensitivity: 78.8%, specificity: 77.8%) in 10 training sets and a mean AUC of 0.866 (sensitivity: 80.9%, specificity: 84.1%) in 10 test sets.ConclusionsA more violent glucose fluctuation pattern was marked in patients with LADA than T2DM. We first proposed the possible role of DFF in distinguishing patients with LADA from T2DM in our study population, which may assist in diabetes classification.

Difference on Glucose Profile From Continuous Glucose Monitoring in People With Prediabetes vs. Normoglycemic Individuals: A Matched-Pair Analysis.

Comprehensive characteristics of the glycemic profile for prediabetes derived by continuous glucose monitoring (CGM) are unknown. We evaluate the difference of CGM profiles between individuals with prediabetes and normoglycemic individuals, including the response to oral glucose tolerance test (OGTT). Individuals with prediabetes matched for age, sex, and BMI with normoglycemic individuals were instructed to use professional CGM for 1 week. OGTT was performed on the second day. The primary outcomes were percentages of glucose readings time below range (TBR): <54 or <70 mg/dL, time in range (TIR): 70 to 180 mg/dL, and time above range (TAR): >180 or >250 mg/dL. Area under the curve (AUC) was calculated following the OGTT. Glucose variability was depicted by coefficient of variation (CV), SD, and mean amplitude of glucose excursion (MAGE). Wilcoxon sign-ranked test, McNemar mid P-test and linear regression models were employed. In all, 36 participants (median age 51 years; median body mass index [BMI] = 26.4 kg/m2) formed 18 matched pairs. Statistically significant differences were observed for 24-hour time in range (TIR; median 98.5% vs. 99.9%, P = .013), time above range (TAR) >180 mg/dl (0.4% vs. 0%, P = .0062), and 24-hour mean interstitial glucose (113.8 vs. 108.8 mg/dL, P = .0038) between people with prediabetes compared to normoglycemic participants. Statistically significant differences favoring the normoglycemic group were found for glycemic variability indexes (median CV 15.2% vs. 11.9%, P = .0156; median MAGE 44.3 vs. 33.3 mg/dL, P = 0.0043). Following OGTT, the AUC was significantly lower in normoglycemic compared to the prediabetes group (median 18615.3 vs. 16370.0, P = .0347 for total and 4666.5 vs. 2792.7, P = .0429 for incremental 2-hour post OGTT). Individuals with prediabetes have different glucose profiles compared to normoglycemic individuals. CGM might be helpful in individuals with borderline glucose values for a more accurate reclassification.

Continuous glucose monitoring in diabetes patients with chronic kidney disease on dialysis: a meta-analysis.

This review investigates the effectiveness of continuous glucose monitoring (CGM) in diabetes patients who were on routine dialysis. Literature search was conducted in electronic databases and studies were selected by following precise eligibility criteria. Random-effects meta-analyses were performed to estimate: 1) correlations of CGM with other indicators including glycated hemoglobin A<inf>1c</inf> (HbA<inf>1c</inf>), glycated albumin and mean amplitude of glucose excursions (MAGE); 2) mean differences (MDs) in CGM and MAGE values between dialysis and off-dialysis days or during vs before dialysis. There was a good correlation between CGM and self-monitoring of blood glucose values (r=0.837 [95% CI: 0.67, 0.92]). Correlation coefficient between CGM and HbA<inf>1c</inf> was 0.523 (95% CI: 0.422, 0.604) in diabetes patients on dialysis and 0.592 (95% CI: 0.354, 0.757) in diabetes patients without renal failure. Correlation coefficient between CGM and glycated albumin in diabetes patients on dialysis was 0.544 (95% CI: 0.254, 0.744). Average CGM and MAGE values on dialysis day were not significantly different from those of off-dialysis day in diabetes patients (MDs: -0.40 mmol/L [95% CI: -1.06, 0.26]; P=0.23; and MAGE 0.50 mmol/L [95% CI: -0.01, 1.00]; P=0.05). Compared to pre-dialysis values, average CGM and MAGE values were significantly lower during dialysis in diabetes patients (MDs: -2.11 mmol/L [95% CI: -3.25, -0.97]; P=0.0003 and MAGE -2.24 mmol/L [95% CI: -3.99, -0.50]; P=0.01). CGM is an efficient method of glycemic monitoring in diabetes patients on dialysis. CGM had similar correlations with HbA<inf>1c</inf> and glycated albumin.

Impact of in-hospital versus ambulatory glucose variability on coronary plaque vulnerability in patients with coronary artery disease

AimThe impact of in-hospital and ambulatory glucose variability (GV) on lipid core plaques (LCP) is unclear. We evaluated the relation of GV during hospitalization and after discharge to LCPs. MethodsA total of 35 patients undergoing percutaneous coronary intervention (PCI) under near-infrared spectroscopy intravascular ultrasound (NIRS-IVUS) guidance for acute myocardial infarction (MI) and stable coronary artery disease were prospectively included. LCP was evaluated with a lipid core burden index (LCBI) and a maximum LCBI in 4 mm (max LCBI4mm) in the non-target vessel using NIRS-IVUS. GV was measured by a flush glucose monitoring system. ResultsIn-hospital mean amplitude of glucose excursion (MAGE) was significantly higher than that after discharge (73.4±26.8 vs. 66.0±22.8 mg/dl, p=0.03). In the entire study population, LCBI and maxLCBI4mm in the non-target vessel were correlated with MAGE after discharge (r=0.51, p=0.002 and r=0.39, p=0.02), but not significantly correlated with in-hospital MAGE. The relations of MAGE to higher LCBI and maxLCBI4mm were more evident in patients with acute MI. ConclusionsGV was greater during hospitalization than after discharge in patients undergoing PCI. Greater GV after discharge was significantly associated with higher LCBI and maxLCBI4mm, suggesting that ambulatory GV may be closely link to coronary atherosclerosis.

Faster-acting insulin aspart reduces glycaemic variability in sensor-augmented pump treated type 1 diabetes patients

AimTo evaluate the effect of faster aspart over glycaemic variability in type 1 diabetes (T1D) patients treated with sensor-augmented pump (SAP) in a real-world scenario. MethodsObservational study with SAP-treated adult T1D patients treated with faster aspart for three months. The primary endpoint was the mean amplitude of glucose excursions (MAGE). ResultsFifty patients were treated with faster aspart. Eleven patients (23%) withdrew during the follow-up mainly due to worsening of diabetes control (9 patients). Mean age was 41.2 yrs. (range 21–59) and T1D duration 22.4±10.0 yrs. Mean SAP treatment duration was 3.6±3.1 yrs. We detected a reduction of -7.0 (95% CI −1.1, −12.9; p=0.021) in MAGE at the end of the study. Other glycemic variability indices were also improved: standard deviation of mean interstitial glucose (−3mg/dl; 95% CI, −1, −5; p=0.01), CONGA4 (−2.2; 95% CI −0.3, −4.2; p=0.029), CONGA6 (−2.6; 95% CI −0.6, −4.6; p=0.011), GRADE (−0.5; 95% CI −0.1, −0.9; p=0.022), HBGI (−0.7; 95% CI −0.2, −1.3; p=0.013), J-index (−2.9; 95% CI −0.7, −5.0; p=0.011) and MODD (−5.7; 95% CI −1.7, −9.7; p=0.006). A slight reduction in mean glucose management indicator was also detected (−0.14%; 95% CI, −0.02, −0.27; −1.4mmol/mol; 95% CI −0.1, −3.3; p=0.03). ConclusionsIn SAP-treated T1D patients, faster aspart insulin was associated with reduced glycaemic variability, but also a high percentage of dropouts due to worsened glycaemic control. NCT04233203.