The importance of HbA1c and glucose variability in patients with type 1 and type 2 diabetes: outcome of continuous glucose monitoring (CGM)

Personal and Social-Built Environmental Factors of Glucose Variability Among Multiethnic Groups of Adults With Type 2 Diabetes: Research Protocol Using Ecological Momentary Assessment, Continuous Glucose Monitoring, and Actigraphy

Glucose variability (GV)-the degree of fluctuation in glucose levels over a certain period of time-is emerging as an important parameter of dynamic glycemic control. Repeated glycemic oscillations have been reported to be the link to diabetes complications. This prospective observational study aims to: (1) identify multilevel risk factors (personal and social-built environmental factors) associated with high GV; (2) identify "within-person predictors" of high GV leveraging the intra-person data to inform future personalized diabetes interventions; and (3) examine which lifestyle factors either mediate or moderate the relationship between emotional well-being and GV among diverse adults with type 2 diabetes (T2D). We will recruit 200 adults with T2D from the community. All participants will complete baseline surveys assessing demographics, lifestyle, social-built environmental, and clinical factors. Real-time dynamic glucose levels will be measured using continuous glucose monitoring (CGM). Sleep, physical activity, diet/eating, and emotional well-being will be measured with an actigraphy device and a real-time self-report tool (ecological momentary assessment [EMA]) across 14 days. Two 24-h dietary recall data will be collected by online video calls. Generalized linear models, multilevel models, and structural equation models will be developed to achieve the study aims. The findings from the study will identify high-risk groups of high GV who would benefit from CGM to improve diabetes outcomes and inform the future development of personalized just-in-time interventions targeting lifestyle behaviors with an increased understanding of GV and by supporting healthcare providers' clinical decisions.

Investigation of Glucose Metabolism by Continuous Glucose Monitoring and Validation of Dipeptidyl Peptidase 4 Inhibitor Use in Patients with Myotonic Dystrophy Type 1

Objectives: We characterized blood glucose fluctuations in patients with myotonic dystrophy type 1 (DM1). After confirming the incretin secretion capacity of patients with DM1, we intended to clarify whether dipeptidyl peptidase 4 (DPP-4) inhibitor administration was appropriate in cases of DM1 with diabetes mellitus. Methods: A 48 h continuous glucose monitoring (CGM) was performed in 29 Japanese patients with DM1. An oral glucose tolerance test (OGTT) was performed in patients with DM1 and five disease controls, and levels of blood glucose, insulin, and incretin (glucagon-like peptide-1 and gastric inhibitory polypeptide) were measured. DPP-4 inhibitors were administered to patients with diabetes mellitus complicated by DM1, and the CGM results were compared. Results: The CGM showed distinct patterns of blood glucose variability among patients classified by an OGTT pattern with significant differences in glucose parameters such as time above 140 mg/dL and mean amplitude of glycemic excursions between the groups. High sensor glucose values were observed in a certain number of patients who were classified as having normal or impaired glucose tolerance by the OGTT. The CGM confirmed the presence of low glucose levels in several patients. Incretin secretion, the target of DPP-4 inhibitors, was preserved in patients with DM1. DPP-4 inhibitor treatment resulted in lower glucose levels and improved insulin secretion in some patients. Conclusions: This is the first CGM study for DM1 patients. The CGM identified potential early abnormalities in glucose metabolism in DM1. In the future, it will be crucial to explore effective methods for harnessing CGM and assessing it quantitatively in DM1.

Washed microbiota transplantation reduces glycemic variability in unstable diabetes

BACKGROUND

Dysbiosis of gut microbiota is causally linked to impaired host glucose metabolism. We aimed to study effects of the new method of fecal microbiota transplantation, washed microbiota transplantation (WMT), on reducing glycemic variability (GV) in unstable diabetes.

METHODS

Fourteen eligible patients received three allogenic WMTs and were followed up at 1 week, 1 month, and 3 months. Primary outcomes were daily insulin dose, glucose excursions during meal tests, and GV indices calculated from continuous monitoring or self-monitoring glucose values. Secondary outcomes were multiomics data, including 16S rRNA gene sequencing, metagenomics, and metabolomics to explore underlying mechanisms.

RESULTS

Daily insulin dose and glucose excursions markedly dropped, whereas GV indices significantly improved up to 1 month. WMT increased gut microbial alpha diversity, beta diversity, and network complexity. Taxonomic changes featured lower abundance of genera Bacteroides and Escherichia-Shigella, and higher abundance of genus Prevotella. Metagenomics functional annotations revealed enrichment of distinct microbial metabolic pathways, including methane biosynthesis, citrate cycle, amino acid degradation, and butyrate production. Derived metabolites correlated significantly with improved GV indices. WMT did not change circulating inflammatory cytokines, enteroendocrine hormones, or C-peptide.

CONCLUSIONS

WMT showed strong ameliorating effect on GV, raising the possibility of targeting gut microbiota as an effective regimen to reduce GV in diabetes.

Economic Hardships from COVID-19 and its Association with Socioeconomic Factors and Diabetes Management Indicators among Diabetic Residents: A Cross-Sectional Study

Aims

The three objectives of this study were to determine the economic hardships of COVID-19 pandemic, their socio-economic predictors, and their association with diabetes management indicators in three cities in a middle-income country.

Methods

A community-based cross-sectional survey of 309 people with diabetes aged 34–85 was carried out in 10 communities during July and August 2020. Face-to-face surveys were conducted by trained community physicians. Economic hardship was assessed by income loss and “financial toxicity” during the COVID-19 pandemic, where financial toxicity was defined as experiencing economic difficulties in accessing diabetes management resources. Indicators of diabetes management was assessed by blood glucose and Hemoglobin A1c (HbA1c) monitoring frequency.

Results

Among all respondents, 38.5% reported having income loss, and 15.5% experiencing financial toxicity during the pandemic. Younger and self-employed people living suburban areas were more likely to experience income loss. Similarly, suburban area residency and lower household income were associated with financial toxicity. Patients with financial toxicity were less likely to monitor HbA1c in the past three months (OR = 0.20; 95% CI, 0.07–0.48).

Conclusion

Diabetes management as indicated by less frequent HbA1c monitoring was associated with experiencing COVID-19 related financial toxicity. Our findings identified vulnerable groups in need of additional support for diabetes management.

Influence of Fasting Plasma Glucose Targets on Glycemic Variability in Chinese Participants With Type 2 Diabetes: A Post Hoc Analysis of the FPG GOAL Trial (BEYOND III)

INTRODUCTION

This post hoc analysis examines the relationship between glycemic variability (GV) and fasting plasma glucose (FPG) targets used to achieve glycated hemoglobin (HbA1c) < 7%, and HbA1c levels after 24 weeks of treatment with insulin glargine and oral antidiabetic drugs (OADs) in Chinese participants with type 2 diabetes mellitus (T2DM) from the BEYOND III FPG GOAL trial (NCT02545842).

METHODS

Participants were randomized for three FBG targets (≤ 5.6 mmol/L, ≤ 6.1 mmol/L, and ≤ 7.0 mmol/L) receiving insulin glargine 100 U/mL were analyzed for mean change from baseline to 24 weeks in postprandial glucose (PPG) excursion and FPG coefficient of variation (FPG-CV). The study analyzed change from baseline in HbA1c and the proportion of participants who achieved HbA1c < 7% at 24 weeks, according to their baseline FPG-CV and change from baseline in PPG excursion.

RESULTS

The change in PPG excursion and FPG-CV from baseline to 24 weeks was not significantly different between the three groups stratified by randomization or by 24-week FPG levels. While the change in HbA1c from baseline to 24 weeks was slightly higher among participants with baseline FPG-CV < 33.3% (vs. > 66.7%; P = 0.023), a higher proportion of participants with baseline FPG-CV < 33.3% achieved HbA1c < 7% (P = 0.021).

CONCLUSIONS

GV was not associated with either target FPG levels or HbA1c < 7.0% after 24 weeks of treatment with insulin glargine and OADs.

TRIAL REGISTRATION

Clinicaltrials.gov identifier NCT02545842.

Influence of Glucose Fluctuation on Peripheral Nerve Damage in Streptozotocin-Induced Diabetic Rats

BACKGROUND

It is unclear whether glycemic variability (GV) is a risk factor for diabetic peripheral neuropathy (DPN), and whether control of GV is beneficial for DPN. The purpose of this study was to investigate the effect of GV on peripheral nerve damage by inducing glucose fluctuation in streptozotocin-induced diabetic rats.

METHODS

Rats were divided into four groups: normal (normal glucose group [NOR]), diabetes without treatment (sustained severe hyperglycemia group; diabetes mellitus [DM]), diabetes+once daily insulin glargine (stable hyperglycemia group; DM+LAN), and diabetes+once daily insulin glargine with twice daily insulin glulisine (unstable glucose fluctuation group; DM+Lantus [LAN]+Apidra [API]). We measured anti-oxidant enzyme levels and behavioral responses against tactile, thermal, and pressure stimuli in the plasma of rats. We also performed a quantitative comparison of cutaneous and sciatic nerves according to glucose fluctuation.

RESULTS

At week 24, intraepidermal nerve fiber density was less reduced in the insulin-administered groups compared to the DM group (P<0.05); however, a significant difference was not observed between the DM+LAN and DM+LAN+API groups irrespective of glucose fluctuation (P>0.05; 16.2±1.6, 12.4±2.0, 14.3±0.9, and 13.9±0.6 for NOR, DM, DM+LAN, and DM+LAN+API, respectively). The DM group exhibited significantly decreased glutathione levels compared to the insulin-administered groups (2.64±0.10 μmol/mL, DM+LAN; 1.93±0.0 μmol/mL, DM+LAN+API vs. 1.25±0.04 μmol/mL, DM; P<0.05).

CONCLUSION

Our study suggests that glucose control itself is more important than glucose fluctuation in the prevention of peripheral nerve damage, and intra-day glucose fluctuation has a limited effect on the progression of peripheral neuropathy in rats with diabetes.

Glycemic variability and indices of glycemic control among pregnant women with type 1 diabetes (T1D) based on the use of continuous glucose monitoring share technology

BACKGROUND

Pregnancies complicated by type 1 diabetes (T1D) experience high levels of glycemic variability, which may be associated with adverse maternal and neonatal outcomes. Therefore, strategies that help pregnant women with T1D manage their glycemic control are of great interest.

METHODS

We examined associations with or without remote monitoring of Continuous Glucose Monitor (CGM) data by friends and family with indices of glycemic control and glycemic variability during pregnancies complicated by T1D in a pilot non-randomized trial (n = 28). During preconception or the first trimester, participants were placed in one of two groups based on device compatibility: (1) CGM Alone (n = 13): women without iPhone, iPad or iPod Touch; or (2) CGM Share (n = 15): women with iPhone, iPad, or iPod Touch and followers with devices compatible for data viewing. Linear mixed models were used to compare indices of glycemic control and glycemic variability over time between groups.

RESULTS

Participants using CGM Share had lower estimated HbA1c levels over time (p = .028), glucose management index (p = .041), and fewer glucose excursions >200 mg/dL in each trimester (p = .022) compared to those using CGM Alone. Participants using CGM Alone had higher high blood glucose index (p = .020), mean area under the curve (p = .026), and standard deviation (p = .046) compared to those using CGM Share. Other measures of glycemic variability did not differ between groups.

CONCLUSION

In this non-randomized pilot study, use of CGM Share was associated with improvements in several indices of glycemic control and glycemic variability.

Improved Glycemic Control and Variability: Application of Healthy Ingredients in Asian Staples

A reduction in carbohydrate intake and low-carbohydrate diets are often advocated to prevent and manage diabetes. However, limiting or eliminating carbohydrates may not be a long-term sustainable and maintainable approach for everyone. Alternatively, diet strategies to modulate glycemia can focus on the glycemic index (GI) of foods and glycemic load (GL) of meals. To assess the effect of a reduction in glycemic load of a 24 h diet by incorporating innovative functional ingredients (β-glucan, isomaltulose) and alternative low GI Asian staples (noodles, rice)on glycemic control and variability, twelve Chinese men (Age: 27.0 ± 5.1 years; BMI:21.6 ± 1.8kg/m²) followed two isocaloric, typically Asian, 24h diets with either a reduced glycemic load (LGL) or high glycemic load (HGL) in a randomized, single-blind, controlled, cross-over design. Test meals included breakfast, lunch, snack and dinner and the daily GL was reduced by 37% in the LGL diet. Continuous glucose monitoring provided 24 h glycemic excursion and variability parameters: incremental area under the curve (iAUC), max glucose concentration (Max), max glucose range, glucose standard deviation (SD), and mean amplitude of glycemic excursion (MAGE), time in range (TIR). Over 24h, the LGL diet resulted in a decrease in glucose Max (8.12 vs. 6.90 mmol/L; p = 0.0024), glucose range (3.78 vs. 2.21 mmol/L; p = 0.0005), glucose SD (0.78 vs. 0.43 mmol/L; p = 0.0002), mean amplitude of glycemic excursion (2.109 vs. 1.008; p < 0.0001), and increase in 4.5-6.5mmol/L TIR (82.2 vs. 94.6%; p = 0.009), compared to the HGL diet. The glucose iAUC, MAX, range and SD improved during the 2 h post-prandial window of each LGL meal, and this effect was more pronounced later in the day. The current results validate the dietary strategy of incorporating innovative functional ingredients (β-glucan, isomaltulose) and replacing Asian staples with alternative low GI carbohydrate sources to reduce daily glycemic load to improve glycemic control and variability as a viable alternative to the reduction in carbohydrate intake alone. These observations provide substantial public health support to encourage the consumption of staples of low GI/GL to reduce glucose levels and glycemic variability. Furthermore, there is growing evidence that the role of chrononutrition, as reported in this paper, requires further examination and should be considered as an important addition to the understanding of glucose homeostasis variation throughout the day.

EMDIA Case Series-Effective Medication Therapy Management (MTM) for Diabetes Type 2 Patients-A Proof of Concept Study

Background: A 2016 meta-analysis of pharmaceutical care for patients with diabetes mellitus showed that the following four components were most effective: (a) individual goal setting, (b) sending feedback to the physician, (c) reviewing the medication, and (d) reviewing blood glucose measurements. Methods: To formulate a hypothesis regarding the effect of these four pharmaceutical care components on glycemic control in patients with diabetes mellitus and the feasibility of these components in practice. Ten patients with type 2 diabetes were included in the case series and received medication therapy management over four months. Results: The four care components were feasible in everyday practice and could be implemented within one patient visit. The average visits were 49 and 28 min at the beginning and end of the study, respectively. The glycated hemoglobin values did not change over the study period, though the fasting blood glucose decreased from 142 to 120 mg/dl, and the number of unsolved drug-related problems decreased from 6.9 to 1.9 per patient by the study end. Conclusions: This case series supports the hypothesis that community pharmacists can implement structured pharmaceutical care in everyday pharmacy practice for patients with type 2 diabetes mellitus.

Prevalence of glycemic variability and factors associated with the glycemic arrays among end-stage kidney disease patients on chronic hemodialysis

Glycemic variability (GV) confers a significantly higher risk of diabetic-related complications, especially cardiovascular. Despite extensive research in this area, data on end-stage kidney disease (ESKD) patients on chronic hemodialysis are scarce. This study aims to determine the magnitude of GV among ESKD (diabetic vs nondiabetic) patients and its associated factors on hemodialysis days (HDD) and non-hemodialysis days (NHDD) where postulation of a higher GV observed among diabetic on HDD.We recruited 150 patients on hemodialysis, 93 patients with type 2 diabetic (DM-ESKD), and 57 with nondiabetic (NDM-ESKD). The GV indices (standard deviation [SD] and percentage coefficient variant [%CV]) were obtained from 11-point and 7-point self-monitoring blood glucose (fasting to post-meal) (SMBG) profiles on HDD and NHDD. The GV indices and its associated factors of both DM-ESKD and NDM-ESKD were analyzed to compare HDD vs NHDD.Mean blood glucose on HDD was 9.33 [SD 2.7, %CV 30.6%] mmol/L in DM-ESKD compared with 6.07 [SD 0.85, %CV 21.3%] mmol/L in NDM-ESKD (P = <.01). The DM-ESKD group experienced significantly above target GV indices compared to NDM-ESKD on both HDD and NHDD, particularly in the subgroup with HbA1c 8-10% (P = <.01). Presence of diabetes, older age, hyperlipidemia, HbA1c, ferritin levels, and albumin were identified as factors associated with GV.DM-ESKD patients have above-target GV indices, especially on HDD, therefore increasing their risk of developing future complications. We identified high HbA1c, older age group, presence of hyperlipidemia, ferritin levels, and albumin as factors associated with GV indices that may be used as surrogate markers for GV. Since these groups of patients are vulnerable to CVD mortality, urgent attention is needed to rectify it.

Characteristics of Continuous Glucose Monitoring Metrics in Persons with Type 1 and Type 2 Diabetes Treated with Multiple Daily Insulin Injections

Background: Although guidelines advocate similar continuous glucose monitoring (CGM) targets for insulin-treated persons with type 1 diabetes (T1D) and type 2 diabetes (T2D), it is unclear how these persons differ with respect to hypoglycemia, glucose variability, and other CGM metrics in clinical practice. Methods: We used data from 2 multicenter randomized-controlled trials (GOLD and MDI-Liraglutide) where 161 persons with T1D and 124 persons with T2D treated with multiple daily injections were included and monitored with masked CGM. Results: Persons from both cohorts had similar mean glucose levels, 10.9 mmol/L (196 mg/dL) in persons with T1D and 10.8 mmol/L (194 mg/dL) in persons with T2D. Time in hypoglycemia (<3.9 mmol/L [70 mg/dL]) was 5.1% and 1.0% for persons with T1D and T2D, respectively (P < 0.001). Corresponding estimates for the standard deviations of mean glucose levels were 4.4 mmol/L (79 mg/dL) versus 3.0 (54 mg/dL) (P < 0.001), for coefficient of variation 41% versus 28% (P < 0.001), and for time in range 38.2% versus 45.3%, respectively (P = 0.004). Mean C-peptide levels were 0.05 nmol/L and 0.67 nmol/L (P < 0.001) for persons with T1D and T2D, respectively. Conclusions: Persons with T1D compared with persons with T2D treated with multiple daily insulin injections spend considerably more time in hypoglycemia, have higher glucose variability, and less "time in range." This needs to be taken into account in daily clinical care and in recommended targets for CGM metrics.

Association of time in range with hemoglobin A1c, glycated albumin and 1,5-anhydro-d-glucitol

AIMS/INTRODUCTION

Hemoglobin A1c (HbA1c), glycated albumin (GA) and 1,5-anhydro-d-glucitol (1,5-AG) are used as indicators of glycemic control, whereas continuous glucose monitoring (CGM) is used to assess daily glucose profiles. The aim of this study was to investigate the relationships between CGM metrics, such as time in range (TIR), and glycemic control indicators.

MATERIALS AND METHODS

We carried out retrospective CGM and blood tests on 189 outpatients with impaired glucose tolerance (n = 22), type 1 diabetes mellitus (n = 67) or type 2 diabetes mellitus (n = 100).

RESULTS

In type 1 diabetes mellitus and type 2 diabetes mellitus patients, HbA1c and GA were negatively correlated with TIR, whereas 1,5-AG was positively correlated with TIR. In type 1 diabetes mellitus patients, a TIR of 70% corresponded to HbA1c, GA and 1,5-AG of 6.9% (95% confidence interval [CI] 6.5-7.2%), 20.3% (95% CI 19.0-21.7%) and 6.0 µg/mL (95% CI 5.1-6.9 µg/mL), respectively. In type 2 diabetes mellitus patients, a TIR of 70% corresponded to HbA1c, GA and 1,5-AG of 7.1% (95% CI 7.0-7.3%), 19.3% (95% CI 18.7-19.9%) and 10.0 µg/mL (95% CI 9.0-11.0 µg/mL), respectively. TIR values corresponding to HbA1c levels of 7.0% were 56.1% (95% CI 52.3-59.8%) and 74.2% (95% CI 71.3-77.2%) in type 1 diabetes mellitus and type 2 diabetes mellitus patients, respectively.

CONCLUSIONS

The results of this study showed that the estimated HbA1c corresponding to a TIR of 70% was approximately 7.0% for both type 1 diabetes mellitus and type 2 diabetes mellitus patients, and that the estimated 1,5-AG calculated from the TIR of 70% might be different between type 1 diabetes mellitus and type 2 diabetes mellitus patients.

Effect of CGM in the HbA1c and Coefficient of Variation of glucose in a pediatric sample

AIM OF THE STUDY

Previous studies have found no significant improvements in glycated hemoglobin (HbA1c), while using Continuous Glucose Monitoring (CGM), with children and adolescents. The aim of this paper is to measure the change in HbA1c, and the Coefficient of Variation in glucose levels, when using CGM, once the effect of other relevant variables, such as gender, actual age, the years the patient has had diabetes, use of an insulin pump, the presence of autoimmune disease, other associated pathologies, and weekly hours of exercise, are controlled for.

METHODS

This is a retrospective study that uses a linear regression model. Data was collected from Type 1 Diabetes Mellitus (T1DM), children diagnosed between 2003 and 2017 in the Pediatric Unit for Diabetes in Zaragoza, Spain. We used a linear regression and the method of estimation is Ordinary Least Squares.

RESULTS

Results show that the use of CGM decreased the HbA1c value by 3.5% and the Coefficient of Variation by 14%.

CONCLUSIONS

The implication of these results is that this device helped in the management of diabetes, although more research is needed to distinguish between different devices in terms of their efficacy.

Oscillatory pattern of glycemic control in patients with diabetes mellitus

Daily glucose variability is higher in diabetic mellitus (DM) patients which has been related to the severity of the disease. However, it is unclear whether glycemic variability displays a specific pattern oscillation or if it is completely random. Thus, to determine glycemic variability pattern, we measured and analyzed continuous glucose monitoring (CGM) data, in control subjects and patients with DM type-1 (T1D). CGM data was assessed for 6 days (day: 08:00-20:00-h; and night: 20:00-08:00-h). Participants (n = 172; age = 18-80 years) were assigned to T1D (n = 144, females = 65) and Control (i.e., healthy; n = 28, females = 22) groups. Anthropometry, pharmacologic treatments, glycosylated hemoglobin (HbA1c) and years of evolution were determined. T1D females displayed a higher glycemia at 10:00-14:00-h vs. T1D males and Control females. DM patients displays mainly stationary oscillations (deterministic), with circadian rhythm characteristics. The glycemia oscillated between 2 and 6 days. The predictive model of glycemia showed that it is possible to predict hyper and hypoglycemia (R² = 0.94 and 0.98, respectively) in DM patients independent of their etiology. Our data showed that glycemic variability had a specific oscillation pattern with circadian characteristics, with episodes of hypoglycemia and hyperglycemia at day phases, which could help therapeutic action for this population.

Flash glucose monitoring in diabetic dogs: a feasible method for evaluating glycemic control

OBJECTIVE

To alleviate clinical signs and avoid life-threatening complications in dogs with diabetes mellitus, individualized treatment plans and frequent reassessments are necessary. Performing blood glucose profiles every 7-14 days following insulin adjustments and monthly thereafter, is recommended. In 2016, a factory calibrated continuous blood glucose monitoring system was presented as a possible alternative to glucometer readings. The objectives of this study were to summarize the experiences with this new technology and to show, that in combination with simple rules, already the first measurement period can improve glycemic control.

MATERIAL AND METHODS

The electronic database of the endocrine unit of the clinic was retrospectively searched for diabetic dogs with flash glucose monitoring. In case of repeated sensor implantations, only the first sensor was considered. The recordings of day A (starting at midnight after sensor placement) were compared to the measurements of day B (day before sensor failure) and all owners were contacted to fill in a standardized questionnaire.

RESULTS

The final study population consisted of 24 dogs weighing 3.4 to 36 kg. Although the clicking noise during sensor placement irritated most dogs, the application was considered easy and painless. Waiting for disinfectant evaporation and fixation of the sensor disc with forceps helped to avoid sensor detachment when removing the application device. Although transient mild to moderate skin irritations were observed in 80 % of the dogs, 95 % of the owners were highly satisfied with this new monitoring technology. Mean and maximum glucose (p = 0.043, p = 0.003) as well as glucose readings ≥ 11.1 mmol/l (p = 0.032) decreased from day A to B, whereas markers of glycemic variability did not change.

CONCLUSION AND CLINICAL RELEVANCE

Flash glucose monitoring is a feasible, safe method with high user satisfaction and offers a possibility to improve glycemic control in diabetic dogs.

Increased Time in Range and Fewer Missed Bolus Injections After Introduction of a Smart Connected Insulin Pen

Background: This observational study investigated whether the connected NovoPen^® 6 could influence insulin regimen management and glycemic control in people with type 1 diabetes (T1D) using a basal-bolus insulin regimen and continuous glucose monitoring in a real-world setting. Methods: Participants from 12 Swedish diabetes clinics downloaded pen data at each visit (final cohort: n = 94). Outcomes included time in range (TIR; sensor glucose 3.9-10.0 mmol/L), time in hyperglycemia (>10 mmol/L), and hypoglycemia (L1: 3.0- <3.9 mmol/L; L2: <3.0 mmol/L). Missed bolus dose (MBD) injections were meals without bolus injection within -15 and +60 min from the start of a meal. Outcomes were compared between the baseline and follow-up periods (≥5 health care professional visits). Data were analyzed from the first 14 days following each visit. For the TIR and total insulin dose analyses (n = 94), a linear mixed model was used, and for the MBD analysis (n = 81), a mixed Poisson model was used. Results: TIR significantly increased (+1.9 [0.8; 3.0]_{95% CI} h/day; P < 0.001) from baseline to follow-up period, with a corresponding reduction in time in hyperglycemia (-1.8 [-3.0; -0.6]_{95% CI} h/day; P = 0.003) and L2 hypoglycemia (-0.3 [-0.6; -0.1]_{95% CI} h/day; P = 0.005), and no change in time in L1 hypoglycemia. MBD injections decreased by 43% over the study (P = 0.002). Change in MBD injections corresponded to a decrease from 25% to 14% based on the assumption that participants had three main meals per day. Conclusions: Our study highlights the potential benefit on glycemic control and dosing behavior when reliable insulin dose data from a connected pen contribute to insulin management in people with T1D.

Different amounts of moderate to vigorous physical activity and change in glycemic variability in adolescents with type 1 diabetes: is there dose-response relationship?

OBJECTIVE

To identify the level of physical activity and glycemic variability of adolescents with type 1 diabetes mellitus and to compare glycemic variability on days with different amounts of moderate to vigorous physical activity (MVPA).

SUBJECTS AND METHODS

A sample of 34 subjects aged 10 to 15 years, 18 (52.94%) female; age: 13.04 ± 1.94; HbA1c: 9.76 ± 1.51. Physical activity was measured by wGT3X accelerometer. The glucose data were obtained using continuous glucose monitoring, and the following glycemic variability measures were calculated: standard deviation (SD), low blood glucose index (LBGI), high blood glucose index (HBGI), mean amplitude of glycemic excursions (MAGE), glycemic risk assessment in diabetes equation (GRADE) and coefficient of variation (CV). The most and least active days (the days with greater and lesser time dedicated to physical activities of moderate to vigorous intensity, respectively) were identified. In addition, based on the whole period of accelerometer use, daily means of time spent in MVPA were identified among participants, who were then divided into three groups: up to 100 minutes; from 101 to 200 minutes and above 201 minutes. Then, the measures of glycemic variability were compared among the most and least active days and among the groups too.

RESULTS

The amount of MVPA was significantly different between the days evaluated (237.49 ± 93.29 vs. 125.21 ± 58.10 minutes), but glycemic variability measures did not present a significant difference.

CONCLUSION

Despite the significant differences in the amount of MVPA between the two days evaluated, the glycemic variability did not change significantly. Arch Endocrinol Metab. 2020;64(3):312-8.

Clinical Recommendations for the Use of the Ambulatory Glucose Profile in Diabetes Care

BACKGROUND

The ambulatory glucose profile (AGP) uses the wealth of data that are generated by continuous glucose monitoring, including flash glucose monitoring technologies, to provide a visual representation of glucose levels over a typical standard day of usually the most recent two weeks for a person with diabetes and helps to identify patterns and trends in glucose control. The AGP allows certain patterns of glucose levels to be identified and analyzed, such that treatment adjustments can be made, and new individual treatment goals can be defined. This helps to ensure increased treatment satisfaction and adherence, quality of life, and an improvement in metabolic management for people with diabetes.

OBJECTIVE

To date, a range of approaches exists for interpreting the information contained in an AGP, with different priorities given to identifying and targeting patterns of hypoglycemia and the degree of variability and stability underlying the glucose levels. The objective of the present recommendation is to describe the steps for assessing an AGP in detail and to illustrate these steps using visual examples.

CONCLUSION

This paper describes the consensus recommendations from a group of German expert diabetologists on the necessary steps for assessing an AGP in a structured and detailed way and to explain these steps using practical clinical examples.

Associations of dietary macronutrient and fibre intake with glycaemia in individuals with Type 1 diabetes

AIMS

To study the association between dietary intake and glycaemia in Type 1 diabetes.

METHODS

Data on energy and nutrient intakes, and the mean and coefficient of variation of self-monitored blood glucose measurements were obtained from records completed by 1000 adults with Type 1 diabetes. Associations between these measures of glycaemia and dietary intake were investigated using generalized linear regression, with and without macronutrient substitution.

RESULTS

In the first set of analyses, fibre intake was associated with lower mean self-monitored blood glucose values (β = -0.428, 95% CI -0.624 to -0.231; P<0.001). In these same analyses, carbohydrate (β = 0.011, 95% CI 0.002 to 0.020; P=0.014), alcohol (β = 0.013, 95% CI 0.003 to 0.023; P=0.009) and monounsaturated fatty acid intakes (β=0.012, 95% CI 0.001 to 0.023; P=0.029) were associated with higher variability in blood glucose measurements. In the macronutrient substitution analyses, substituting proteins for either carbohydrates (β = -0.026, 95% CI -0.040 to -0.013; P<0.001), fats (β = -0.018, 95% CI -0.033 to -0.004; P=0.014), or alcohol (β = -0.026, 95% CI -0.045 to -0.006; P=0.010), or fats for carbohydrates (β=-0.009, 95% CI -0.017 to -0.001; P=0.030), were all associated with lower variability in the measured blood glucose values. After adjusting for fibre intake, no significant results were observed in analyses of mean self-monitored blood glucose.

CONCLUSIONS

This observational, cross-sectional study indicates that dietary fibre is associated with lower mean blood glucose concentrations in people with Type 1 diabetes. Glycaemic excursions were reduced when protein was substituted for other macronutrients and when fat replaced carbohydrate, after adjusting for fibre intake.

Flash Glucose Monitoring Accepted in Daily Life of Children and Adolescents with Type 1 Diabetes and Reduction of Severe Hypoglycemia in Real-Life Use

Background: Flash glucose monitoring (FGM) is covered by the Belgian public health insurance for type 1 diabetes since 2016. The objective of this study was to describe the use of FGM and diabetes outcomes in type 1 diabetic children and adolescents 1 year after reimbursement. Methods: All patients had the choice to convert to FGM or to continue with self-monitoring of blood glucose (SMBG). Clinical data were collected at baseline, at the next visit, and after 12 months; glucose profiles at next visit and after 12 months. Regression analyses were performed to identify predictors of FGM acceptance and changes in metabolic control. Results: A total of 334 subjects were included, of whom 278 (83.2%) switched to FGM. They were younger (13.6 vs. 15.2 years; P = 0.012) and performed more SMBG testing at baseline than patients who did not switch (4.3 vs. 4.1 tests daily; P = 0.008). At the end of follow-up, the rate of severe hypoglycemia decreased by 53% in the group of FGM users (P = 0.012) while it remained stable in SMBG users. Median glycated hemoglobin did not change significantly in both groups. Among subjects who switched to FGM, 15.8% reverted to SMBG after a median use of 5.3 months. Adverse events, diabetes duration, and FGM utilization were independent predictors of the risk for reverting. FGM-related adverse events were associated with a fivefold increased risk to revert to SMBG (hazard ratio = 5.12; P < 0.0001). Conclusions: FGM is relatively well accepted and decreases the risk of severe hypoglycemic events in our pediatric population. FGM is more often discontinued in patients experiencing adverse events and with longer diabetes duration.

The phenomenon of HbA1c stability and the risk of hypoglycemia in long-standing type 1 diabetes

AIMS

Hyperglycemia is the major factor underlying vascular complications of diabetes. Unfortunately, improved glycemia control is frequently accompanied by an increased risk of hypoglycemia. The aim of the study was to assess the relationship between hemoglobin A1c (HbA1c) and 1-week Continuous Glucose Monitoring (CGM) data in long-standing type 1 diabetes (T1DM).

METHODS

We recruited 58 subjects with long-standing T1DM consecutively enrolled to the study. Each patient underwent a 1-week CGM and laboratory profile at baseline. Subjects were divided into three subgroups according to baseline HbA1c tertiles: T1 < 7.1%, T2 = 7.1-8.0%, and T3 > 8.0%.

RESULTS

T1 patients were characterized by the longest time in range (66% of a week), whereas T3 patients experienced hyperglycemia in >50% time of the week. T1 patients were noted to have 25% of nighttime with glycemia <3.9 mmol/L (8% with glycemia <2.8 mmol/L). Most recent HbA1c closely reflected 10-years mean HbA1c values (R = 0.83; P < 0.0001).

CONCLUSIONS

(1) Long-term diabetes control (10 years HbA1c mean) is a strong predictor of the current HbA1c levels. (2) Current and historical HbA1c levels are closely linked to CGM-derived glycemia. (3) Risk of clinically significant hypoglycemia negatively correlates with HbA1c. (4) HbA1c > 8.0% is associated with unsatisfactorily low (44%) time in range.

The mechanisms of glycemic variability accelerate diabetic central neuropathy and diabetic peripheral neuropathy in diabetic rats

The effect of glycemic variability (GV) on diabetic neuropathy, including diabetic central neuropathy and diabetic peripheral neuropathy (DPN), and the involved mechanism are not fully understood. In this study, a fluctuant hyperglycemia rat model was induced by alternate intraperitoneal injections of glucose and insulin. To assess diabetic central neuropathy, step-down type passive avoidance tests were conducted, and the expression levels of p-Tau, T-Tau, p-GSK3β, GSK3β, p-Akt, and Akt in the hippocampus were measured. To assess DPN, the motor nerve conduction velocity (MNCV) was measured, and the microstructure of the sciatic nerve was observed. Additionally, the expression levels of oxidative stress and inflammation indicators were detected in the sciatic nerve. We observed that both learning and memory abilities were disrupted by GV. GV promoted Tau phosphorylation and inhibited the Akt/GSK3β pathway in the hippocampus. Additionally, GV weakened the MNCV of the sciatic nerve, and the structures of both the myelin sheath and the axons in the sciatic nerve were disrupted. GV also significantly reduced the expression of superoxide dismutase (SOD) and increased the expression levels of malondialdehyde (MDA), of proinflammatory cytokines (TNF-α and IL-6) and of NF-κB. In conclusion, the present study highlighted that GV might induce diabetic central neuropathy through the hyperphosphorylation of Tau in the hippocampus by inhibiting the Akt/GSK3β pathway and that it may cause DPN through oxidative stress and inflammatory responses by activating the NF-κB pathway.

Estimation of glycaemic control in the past month using ratio of glycated albumin to HbA1c

AIMS

To evaluate comprehensively the use of the glycated albumin to HbA_1c ratio for estimation of glycaemic control in the previous month.

METHODS

A total of 306 children with Type 1 diabetes mellitus underwent ≥10 simultaneous measurements of glycated albumin and HbA_1c . Correlation and concordance rates were examined between HbA_1c measurements taken 1 month apart (ΔHbA_1c ) and glycated albumin/HbA_1c ratio fluctuations were calculated as Z-scores from the cohort value at enrolment of this study cohort (method A) or the percent difference from the individual mean over time (method B).

RESULTS

Fluctuations in glycated albumin/HbA_1c ratio (using both methods) were weakly but significantly correlated with ΔHbA_1c , whereas concordance rates were significant for glycaemic deterioration but not for glycaemic improvement. Concordance rates were higher using method B than method A.

CONCLUSIONS

The glycated albumin/HbA_1c ratio was able to estimate glycaemic deterioration in the previous month, while estimation of glycaemic improvement in the preceding month was limited. Because method B provided a better estimate of recent glycaemic control than method A, the individual mean of several measurements of the glycated albumin/HbA_1c ratio over time may also identify individuals with high or low haemoglobin glycation phenotypes in a given population, such as Japanese children with Type 1 diabetes, thereby allowing more effective diabetes management.

Associations of blood glucose dynamics with antihyperglycemic treatment and glycemic variability in type 1 and type 2 diabetes

AIMS

The dynamical structure of glucose fluctuation has largely been disregarded in the contemporary management of diabetes.

METHODS

In a retrospective study of patients with diabetes, we evaluated the relationship between glucose dynamics, antihyperglycemic therapy, glucose variability, and glucose exposure, while taking into account potential determinants of the complexity index. We used multiscale entropy (MSE) analysis of continuous glucose monitoring data from 131 subjects with type 1 (n = 18), type 2 diabetes (n = 102), and 11 nondiabetic control subjects. We compared the MSE complexity index derived from the glucose time series among the treatment groups, after adjusting for sex, age, diabetes duration, body mass index, and carbohydrate intake.

RESULTS

In type 2 diabetic patients who were on a diet or insulin regimen with/without oral agents, the MSE index was significantly lower than in nondiabetic subjects but was lowest in the type 1 diabetes group (p < 0.001). The decline in the MSE complexity across the treatment groups correlated with increasing glucose variability and glucose exposure. Statistically, significant correlations existed between higher MSE complexity indices and better glycemic control. In multivariate regression analysis, the antidiabetic therapy was the most powerful predictor of the MSE (β = -0.940 ± 0.242, R ² = 0.306, p < 0.001), whereas the potential confounders failed to contribute.

CONCLUSIONS

The loss of dynamical complexity in glucose homeostasis correlates more closely with therapy modalities and glucose variability than with clinical measures of glycemia. Thus, targeting the glucoregulatory system by adequate therapeutic interventions may protect against progressive worsening of diabetes control.

Insulin degludec is associated with less frequent and milder hypoglycemia in insulin-deficient patients with type 1 diabetes compared with insulin glargine or detemir

Introduction

The aim of this study was to determine the efficacy of insulin degludec (IDeg) relative to insulin glargine (IGlar) or insulin detemir (IDet) in glycemic control, as evaluated by continuous glucose monitoring (CGM) in insulin-deficient patients with type 1 diabetes.

Methods

We studied 28 outpatients treated with IGlar or IDet (IGlar/IDet). Basal insulin was switched to IDeg when glycemic control was considered unstable, as judged by the dawn phenomenon or nocturnal hypoglycemia. Whole-day CGM data were also divided into daytime and nighttime data.

Results

The dawn phenomenon or nocturnal hypoglycemia under IGlar/IDet treatment was observed in all patients. Among 26 patients who completed the study, there were no significant differences in parameters representing glycemic variability, hyperglycemia, mean glycemic control, and HbA1c or insulin therapy-related quality of life at the night score. Measures of hypoglycemia [whole-day %Low and area under the curve (AUC) below 70] were significantly lower under IDeg treatment than under IGlar/IDet treatment (%Low, 9.6 ± 11.5 vs. 14.7 ± 14.9%, p = 0.045; AUC below 70, 85.5 ± 126.0 vs. 145.0 ± 178.6 mg/dl h, p = 0.030). Dividing patients into two groups according to percentage or degree of hypoglycemia under IGlar/IDet treatment, the whole-day, daytime and nighttime %Low in the high-percentage groups and AUC below 70 in the high-degree groups were significantly ameliorated, respectively (p < 0.05).

Conclusion

Patients with unstable glycemic control under IGlar/IDet treatment did not improve glycemic control upon switching to IDeg, but the frequency and the degree of hypoglycemia was reduced in insulin-deficient outpatients with type 1 diabetes, especially in those suffering from severe hypoglycemia.

Acute Low-Volume High-Intensity Interval Exercise and Continuous Moderate-Intensity Exercise Elicit a Similar Improvement in 24-h Glycemic Control in Overweight and Obese Adults

Background: Acute exercise reduces postprandial oxidative stress and glycemia; however, the effects of exercise intensity are unclear. We investigated the effect of acute low-volume high-intensity interval-exercise (LV-HIIE) and continuous moderate-intensity exercise (CMIE) on glycemic control and oxidative stress in overweight and obese, inactive adults.

Methods: Twenty-seven adults were randomly allocated to perform a single session of LV-HIIE (9 females, 5 males; age: 30 ± 1 years; BMI: 29 ± 1 kg·m⁻²; mean ± SEM) or CMIE (8 females, 5 males; age: 30 ± 2.0; BMI: 30 ± 2.0) 1 h after consumption of a standard breakfast. Plasma redox status, glucose and insulin were measured. Continuous glucose monitoring (CGM) was conducted during the 24-h period before (rest day) and after exercise (exercise day).

Results: Plasma thiobarbituric acid reactive substances (TBARS; 29 ±13%, p < 0.01; mean percent change ±90% confidence limit), hydrogen peroxide (44 ± 16%, p < 0.01), catalase activity (50 ± 16%, p < 0.01), and superoxide dismutase activity (21 ± 6%, p < 0.01) significantly increased 1 h after breakfast (prior to exercise) compared to baseline. Exercise significantly decreased postprandial glycaemia in whole blood (−6 ± 5%, p < 0.01), irrespective of the exercise protocol. Only CMIE significantly decreased postprandial TBARS (CMIE: −33 ± 8%, p < 0.01; LV-HIIE: 11 ± 22%, p = 0.34) and hydrogen peroxide (CMIE: −25 ± 15%, p = 0.04; LV-HIIE: 7 ± 26%; p = 0.37). Acute exercise provided a similar significant improvement in 24-h average glucose levels (−5 ± 2%, p < 0.01), hyperglycemic excursions (−37 ± 60%, p < 0.01), peak glucose concentrations (−8 ± 4%, p < 0.01), and the 2-h postprandial glucose response to dinner (−9 ± 4%, p < 0.01), irrespective of the exercise protocol.

Conclusion: Despite elevated postprandial oxidative stress compared to CMIE, LV-HIIE is an equally effective exercise mode for improving 24-h glycemic control in overweight and obese adults.

A randomised, open-labelstudy of insulin glargine or neutral protamine Hagedorn insulin in Chinese paediatric patients with type 1 diabetes mellitus

BACKGROUND

We aimed to describe the safety and efficacy of insulin glargine in Chinese paediatric patients with type 1 diabetes mellitus (T1DM). Neutral protamine Hagedorn (NPH) insulin was the reference therapy.

METHODS

This open-label, randomised, Phase III study was conducted at 10 sites in China. Children aged ≥6 to <18 years with T1DM were randomised (2:1) to insulin glargine or NPH insulin asbasal insulinfor a 24-week treatment period. For all patients, insulin aspart was given as bolus insulin. The primary endpoint was absolute change in glycated haemoglobin(HbA1c) from baseline to Week 24. Secondary endpoints included the percentage of patients reaching HbA1c <7.5% (<58.5 mmol/mol), and safety. The study was registered at clinicaltrials.gov (NCT01223131).

RESULTS

In total,196 patients were screened, and 162 were randomised (107 and 55 patients were randomised to insulin glargine and NPH insulin, respectively). The mean ± SD of absolute change in HbA1c was-0.25 ± 1.68% (-2.69 ± 18.32 mmol/mol) in the insulin glargine group and -0.54 ± 1.67% (-5.55 ± 20.32 mmol/mol) in the NPH insulin group. At Week 24, 18.7 and 21.6% of patients in the insulin glargine and NPH insulin groups achieved HbA1c <7.5% (<58.5 mmol/mol). Both treatments were generally well tolerated. A numerically lower rate of symptomatic hypoglycaemia per patient year was observed for insulin glargine versus NPH insulin (24.3 ± 45.8 versus32.3 ± 43.2); severe hypoglycaemia was rare (<2%).

CONCLUSIONS

Initiation of insulin glargine can aid Chinese paediatric patients with T1DM to safely reduce their HbA1c levels.

Functional and proteomic alterations of plasma high density lipoproteins in type 1 diabetes mellitus

OBJECTIVE

Higher HDL-cholesterol (HDL-C) is linked to lower cardiovascular risk but individuals with type 1 diabetes mellitus (T1DM) with normal or high HDL-C have higher cardiovascular events compared to age matched non-diabetic controls (ND). We determined whether altered HDL functions despite having normal HDL-C concentration may explain increased cardiovascular risk in T1DM individuals. We also determined whether irreversible posttranslational modifications (PTMs) of HDL bound proteins occur in T1DM individuals with altered HDL functions.

METHODS

T1DM with poor glycemic control (T1D-PC, HbA1c≥8.5%, n=15) and T1DM with good glycemic control (T1D-GC, HbA1c≤6.6%, n=15) were compared with equal numbers of NDs, ND-PC and ND-GC respectively, matched for age, sex and body mass index (BMI). We measured cholesterol efflux capacity (CEC) of HDL in the serum using J774 macrophages, antioxidant function of HDL as the ability to reverse the oxidative damage of LDL and PON1 activity using commercially available kit. For proteomic analysis, HDL was isolated by density gradient ultracentrifugation and was analyzed by mass spectrometry and shotgun proteomics method.

RESULTS

Plasma HDL-C concentrations in both T1DM groups were similar to their ND. However, CEC (%) of T1D-PC (16.9±0.8) and T1D-GC (17.1±1) were lower than their respective ND (17.9±1, p=0.01 and 18.2±1.4, p=0.02). HDL antioxidative function also was lower (p<0.05). The abundance of oxidative PTMs of apolipoproteins involved in CEC and antioxidative functions of HDL were higher in T1D-PC (ApoA4, p=0.041) and T1D-GC (ApoA4, p=0.025 and ApoE, p=0.041) in comparison with ND. Both T1D-PC and T1D-GC groups had higher abundance of amadori modification of ApoD (p=0.002 and p=0.041 respectively) and deamidation modification of ApoA4 was higher in T1D-PC (p=0.025).

CONCLUSIONS

Compromised functions of HDL particles in T1DM individuals, irrespective of glycemic control, could be explained by higher abundance of irreversible PTMs of HDL proteins. These results lend mechanistic support to the hypothesis that HDL quality rather than quantity determines HDL function in T1DM and suggest that measurements of concentrations of HbA1c and HDL-C are not sufficient as biomarkers of effective treatment to lower cardiovascular risk in T1DM individuals.

Incidence and risk factors for severe and symptomatic hypoglycemia in type 1 diabetes. Results of the HYPOS-1 study

OBJECTIVE

Hypoglycemia is common in type 1 diabetes mellitus (T1DM). We aimed to update the incidence of severe and symptomatic hypoglycemia and investigate several correlated factors.

METHODS

In this multicenter, observational retrospective study, the data of 206 T1DM patients from a sample of 2,229 consecutive patients seen at 18 diabetes clinics were analyzed. Sociodemographic and clinical characteristics, severe hypoglycemia in the past 12 months, and symptomatic hypoglycemia in the past 4 weeks were recorded with a self-report questionnaire and a clinical form during a routine visit. Poisson multivariate models were applied.

RESULTS

A minority of patients accounted for the majority of both severe and symptomatic episodes. The incidence rate (IR) of severe hypoglycemia was 0.49 (0.40-0.60) events/person-years. The incidence rate ratio (IRR) was higher in patients with previous severe hypoglycemia (3.71; 2.28-6.04), neuropathy (4.16; 2.14-8.05), long duration (>20 years, 2.96; 1.60-5.45), and on polypharmacy (1.24; 1.13-1.36), but it was lower when a complication was present. The IR of symptomatic hypoglycemia was 53.3 events/person-years, with an IRR significantly higher among women or patients with better education, or shorter duration or on pumps. The IRR was lower in patients with higher BMI or neuropathy or aged more than 50 years.

CONCLUSIONS

Fewer than 20 % of T1DM patients are free from hypoglycemia, with one in six having experienced at least one severe episode in the last year. The distribution is uneven, with a tendency of episodes to cluster in some patients. Severe and symptomatic episodes have different correlates and reflect different conditions.

Shortfalls of the use of HbA1C-derived eAG in older adults with diabetes

AIMS

The hemoglobin HbA1C (HbA1C) value, translated into estimated average glucose concentration (eAG), is commonly used to assess glycaemic control and manage treatment regimens in people with diabetes. However, the relationships among HbA1C-derived eAG, and mean glucose concentration derived from continuous glucose monitoring (CGM) in different populations have not been well studied. We examined this relationship in older people with diabetes and compared the results to those currently used in clinical practice.

METHODS

Data from three studies evaluating CGM in older adults (≥70 years of age), with stable glycaemic control were analyzed retrospectively. Mean glucose and mean amplitude of glucose excursion (MAGE) were calculated from CGM data and correlated with HbA1C and HbA1C-derived eAG using the ADAG study formula.

RESULTS

HbA1C and CGM data were analyzed from 90 patients with mean age 76±5 years, HbA1C 7.9±1.2% (63±13 mmol/mol) and 77% with Type 2 diabetes. The HbA1C and HbA1C-derived eAG correlated significantly with CGM-measured mean glucose (r(2)=0.30, p<0.0001) and MAGE (r(2)=0.16, p=0.00013) in this population and all its subgroups, but the slopes of the relationship between HbA1C and eAG or CGM-measured mean glucose were significantly different.

CONCLUSIONS

HbA1C-derived eAG values may not accurately reflect CGM-measured mean glucose or MAGE in older adults with diabetes. Wide glucose excursions should be considered and HbA1C should be interpreted cautiously when making treatment changes based on HbA1C.

Association between blood glucose variability and coronary plaque instability in patients with acute coronary syndromes

Background

Blood glucose variability is receiving considerable attention as a new risk factor for coronary artery disease. This study aimed to investigate the association between blood glucose variability and coronary plaque tissue characteristics.

Methods

In 57 patients with acute coronary syndrome, integrated backscatter intravascular ultrasound (IB-IVUS) and gray-scale IVUS were performed before balloon dilatation or stent implantation in the culprit vessels. Standard IVUS indices were evaluated for volume index (volume/length), and plaque components were measured by IB-IVUS for percent tissue volume. In addition to conventional glucose indicators, blood glucose variability in a stable state was determined by calculating the mean amplitude of glycemic excursions (MAGE) using a continuous glucose monitoring system.

Results

Higher MAGE values were significantly correlated with larger percent plaque volumes (r = 0.32, p = 0.015), and increased lipid (r = 0.44, p = 0.0006) and decreased fibrous (r = −0.45, p = 0.0005) plaque components. In contrast, HbA1c or fasting plasma glucose values were not significantly correlated with plaque volumes and percent plaque components. Homeostasis model assessment of insulin resistance values were positively correlated with vessel (r = 0.35, p = 0.007) and plaque (r = 0.27, p = 0.046) volumes, but not with percent plaque components. In multiple regression analysis, higher MAGE values were independently associated with increased lipid (β = 0.80, p = 0.0035) and decreased fibrous (β = -0.79, p = 0.0034) contents in coronary plaques.

Conclusions

Among all glucose indicators studied, only higher blood glucose variability was an independent determinant of increased lipid and decreased fibrous contents with larger plaque burden, suggesting blood glucose variability as one of the important factors related to coronary plaque vulnerability.

Coefficient of variation of R-R interval closely correlates with glycemic variability assessed by continuous glucose monitoring in insulin-depleted patients with type 1 diabetes

AIMS

In type 1 diabetic patients, insulin secretory capacity, meals and physical activity correlate with glycemic variability. Autonomic function associated with gastrointestinal motility and counterregulatory hormone secretion is another candidate which correlates with glucose variability. The aim of this study is to clarify a new clinical parameter associated with glycemic variability in insulin-depleted patients with type 1 diabetes.

METHODS

We studied 31 inpatients with type 1 diabetes. We evaluated glycemic variability calculated by continuous glucose monitoring, clinical parameters and the coefficient of variation of R-R interval (CVR-R). Glycemic variability was also assessed during the daytime and nighttime.

RESULTS

The CVR-R showed a significant negative correlation with the whole-day standard deviation (SD) (r = -0.50, p = 0.007), mean amplitude of glycemic excursions (MAGE) (r = -0.47, p=0.011), M-value (r = -0.38, p = 0.048) and mean of daily differences (MODD) (r = -0.59, p = 0.001). The CVR-R also showed a significant negative correlation with the nighttime SD (r = -0.59, p = 0.001), MAGE (r = -0.47, p=0.011), M-value (r = -0.53, p = 0.004) and MODD (r = -0.65, p = 0.0003). And furthermore, the CVR-R also showed a significant negative correlation with the daytime SD (r = -0.44, p = 0.019) and MAGE (r = -0.50, p = 0.006), but not with the daytime M-value or MODD. The nighttime SD was significantly higher in patients with diabetic polyneuropathy than in patients without it (p = 0.016), while the CVR-R was significantly lower in patients with polyneuropathy than in patients without it (p = 0.009).

CONCLUSIONS

CVR-R is closely correlated with glycemic variability, especially during nighttime, in insulin-depleted patients with type 1 diabetes. Measuring CVR-R may help us to presume the degree of glycemic variability in those patients.

Glycemic Variability: How Do We Measure It and Why Is It Important?

Chronic hyperglycemia is the primary risk factor for the development of complications in diabetes mellitus (DM); however, it is believed that frequent or large glucose fluctuations may independently contribute to diabetes-related complications. Postprandial spikes in blood glucose, as well as hypoglycemic events, are blamed for increased cardiovascular events in DM. Glycemic variability (GV) includes both of these events; hence, minimizing GV can prevent future cardiovascular events. Correcting GV emerges as a target to be pursued in clinical practice to safely reduce the mean blood glucose and to determine its direct effects on vascular complications in diabetes. Modern diabetes management modalities, including glucagon-related peptide-1-based therapy, newer insulins, modern insulin pumps and bariatric surgery, significantly reduce GV. However, defining GV remains a challenge primarily due to the difficulty of measuring it and the lack of consensus regarding the optimal approach for its management. The purpose of this manuscript was not only to review the most recent evidence on GV but also to help readers better understand the available measurement options and how the various definitions relate differently to the development of diabetic complications.

Comparison of Subcutaneous Regular Insulin and Lispro Insulin in Diabetics Receiving Continuous Nutrition: A Numerical Study

BACKGROUND

Optimal management of non-critically ill patients with diabetes maintained on continuous enteral feeding (CEN) is poorly defined. Subcutaneous (SQ) lispro and SQ regular insulin were compared in a simulated type 1 and type 2 diabetic patient receiving CEN.

METHOD

A glucose-insulin feedback mathematical model was employed to simulate type 1 and type 2 diabetic patients on CEN. Each patient received 25 SQ injections of regular insulin or insulin lispro, ranging from 0-6 U. Primary endpoints were the change in mean glucose concentration (MGC) and change in glucose variability (GV); hypoglycemic episodes were also reported. The model was first validated against patient data.

RESULTS

Both SQ insulin preparations linearly decreased MGC, however, SQ regular insulin decreased GV whereas SQ lispro tended to increase GV. Hourly glucose concentration measurements were needed to capture the increase in GV. In the type 2 diabetic patient, "rebound hyperglycemia" occurred after SQ lispro was rapidly metabolized. Although neither SQ insulin preparation caused hypoglycemia, SQ lispro significantly lowered MGC compared to SQ regular insulin. Thus, it may be more likely to cause hypoglycemia. Analyses of the detailed glucose concentration versus time data suggest that the inferior performance of lispro resulted from its shorter duration of action. Finally, the effects of both insulin preparations persisted beyond their duration of actions in the type 2 diabetic patient.

CONCLUSIONS

Subcutaneous regular insulin may be the short-acting insulin preparation of choice for this subset of diabetic patients. Clinical trial is required before a definitive recommendation can be made.

Longitudinal associations of nutritional factors with glycated hemoglobin in youth with type 1 diabetes: the SEARCH Nutrition Ancillary Study

BACKGROUND

Improved glycated hemoglobin (Hb A1c) delays the progression of microvascular and macrovascular complications in individuals with type 1 diabetes (T1D). We previously showed that higher baseline intakes of n-3 (ω-3) fatty acids and leucine are associated with preserved β cell function 2 y later in youth with T1D.

OBJECTIVE

In the current study, we extend this work to explore the longitudinal associations of nutritional factors with Hb A1c in youth with T1D.

DESIGN

We included 908 T1D youth with baseline and follow-up Hb A1c measurements. Nutritional factors assessed at baseline were as follows: breastfeeding status and timing of complimentary food introduction; intakes of leucine, carbohydrates, protein, fat, and fiber estimated from a food-frequency questionnaire (FFQ); and plasma biomarkers for vitamins D and E, eicosapentaenoic acid (EPA), and docosahexaenoic acid. We fit linear regression models adjusted for baseline Hb A1c, sociodemographic variables, diabetes-related variables, time between baseline and follow-up visits, saturated fat, physical activity, and for FFQ-derived nutrients, total calories. The vitamin D model was further adjusted for season and body mass index z score.

RESULTS

The mean ± SD age and diabetes duration at baseline was 10.8 ± 3.9 y and 10.1 ± 5.8 mo, respectively. A total of 9.3% of participants had poor Hb A1c (value ≥9.5%) at baseline, which increased to 18.3% during follow-up (P < 0.0001). Intakes of EPA (β = -0.045, P = 0.046), leucine (β = -0.031, P = 0.0004), and protein (β = -0.003, P = 0.0002) were significantly negatively associated with follow-up Hb A1c after adjustment for confounders. Intake of carbohydrates was significantly positively (β = 0.001, P = 0.003) associated with follow-up Hb A1c after adjustment for confounders.

CONCLUSIONS

Several nutritional factors may be associated with Hb A1c during early stages of disease progression in youth recently diagnosed with T1D. In addition to the overall role of major macronutrients such as carbohydrates and protein, leucine and n-3 fatty acid intakes, such as of EPA, may be important for long-term glycemic control.

Carbohydrate intake is associated with time spent in the euglycemic range in patients with type 1 diabetes

AIMS/INTRODUCTION

Greater glycemic variability and lack of predictability are important issues for patients with type 1 diabetes. Dietary factors are one of the contributors to this variability, but how closely diet is linked to glycemic fluctuation on a daily basis has not been investigated. We examined the association between carbohydrate intake and glycemic excursion in outpatients.

MATERIALS AND METHODS

A total of 33 patients with type 1 diabetes were included in the analyses (age 44.5 ± 14.7 years, diabetes duration 15.1 ± 8.3 years, 64% female, 30% using insulin pump, glycated hemoglobin 8.1 ± 1.3%). Time spent in euglycemia (70-180 mg/dL), hyperglycemia (>180 mg/dL) and hypoglycemia (<70 mg/dL) of consecutive 48-h periods of continuous glucose monitoring data were collected together with simultaneous records of dietary intake, insulin dose and physical activity. Correlation analyses and multiple regression analyses were used to evaluate the contribution of carbohydrate intake to time spent in the target glycemic range.

RESULTS

In multiple regression analyses, carbohydrate intake (β = 0.53, P = 0.001), basal insulin dose per kg per day (β = -0.31, P = 0.034) and diabetes duration (β = 0.30, P = 0.042) were independent predictors of time spent in euglycemia. Carbohydrate intake (β = -0.51, P = 0.001) and insulin pump use (β = -0.34, P = 0.024) were independent predictors of time spent in hyperglycemia. Insulin pump use (β = 0.52, P < 0.001) and bolus insulin dose per kg per day (β = 0.46, P = 0.001) were independent predictors of time spent in hypoglycemia.

CONCLUSIONS

Carbohydrate intake is associated with time spent in euglycemia in patients with type 1 diabetes.

Glycemic Variability: Assessing Glycemia Differently and the Implications for Dietary Management of Diabetes

The primary therapeutic target for diabetes management is the achievement of good glycemic control, of which glycated hemoglobin (HbA1c) remains the standard clinical marker. However, glycemic variability (GV; the amplitude, frequency, and duration of glycemic fluctuations around mean blood glucose) is an emerging target for blood glucose control. A growing body of evidence supports GV as an independent risk factor for diabetes complications. Several techniques have been developed to assess and quantify intraday and interday GV. Additionally, GV can be influenced by several nutritional factors, including carbohydrate quality, quantity; and distribution; protein intake; and fiber intake. These factors have important implications for clinical nutrition practice and for optimizing blood glucose control for diabetes management. This review discusses the available evidence for GV as a marker of glycemic control and risk factor for diabetes complications. GV quantification techniques and the influence of nutritional considerations for diabetes management are also discussed.

Evaluation of blood glucose fluctuation in Japanese patients with type 1 diabetes mellitus by self-monitoring of blood glucose and continuous glucose monitoring

AIMS

Accurate assessment of blood glucose fluctuation is essential for managing blood glucose control while avoiding hypoglycemia in patients with diabetes mellitus. In this study, blood glucose was measured by continuous glucose monitoring (CGM) in patients with type 1 diabetes mellitus (T1DM) whom self-monitoring of blood glucose (SMBG) was carried out three or more times per day, and evaluation was performed using blood glucose fluctuation parameters obtained by CGM and SMBG.

METHODS

Twenty-nine insulin-depleted patients with T1DM were enrolled. Their blood glucose fluctuations were measured at the same time by SMBG and CGM, and the correlations were evaluated.

RESULTS

Correlations were found between the following values obtained by SMBG and CGM: mean and standard deviation of blood glucose levels, average daily risk range, Morbus value and high-blood-glucose index. The hypoglycemia duration and the nocturnal hypoglycemia duration showed no correlation with any of the blood glucose fluctuation parameters obtained by SMBG.

CONCLUSIONS

The findings suggest that routine SMBG and glycated hemoglobin (HbA1c) measurement are sufficient for evaluation of hyperglycemia in T1DM. On the other hand, blood glucose fluctuation parameters obtained by SMBG and HbA1c have been shown to have no correlations with either hypoglycemia duration or nocturnal hypoglycemia duration.

Assessment of the association between glycemic variability and diabetes-related complications in type 1 and type 2 diabetes

Chronic hyperglycemia is the main risk factor for the development of diabetes-related complications in both type 1 and type 2 diabetes, but it is thought that frequent or large glucose fluctuations may contribute independently to diabetes-related complications. A systematic literature review was performed using the PubMed, EMBASE and Cochrane Library databases with searches limited to studies published from June 2002 to March 2014, in English and including ≥50 patients. Twenty eight articles were included in the final review. Eighteen studies reported the association between glucose variability and diabetes-related complications exclusively in type 2 diabetes. A positive association between increased variability and microvascular complications and coronary artery disease was consistently reported. Associations between glucose variability and other macrovascular complications were inconsistent in type 2 diabetes. Seven studies examined the association between glucose variability and complications exclusively in type 1 diabetes. Increased glucose variability appears to play a minimal role in the development of micro- and macrovascular complications in type 1 diabetes. Consistent findings suggest that in type 2 diabetes glucose variability is associated with development of microvascular complications. The role of increased glucose variability in terms of microvascular and macrovascular complications in type 1 diabetes is less clear; more data in are needed.

Lower glucose variability and hypoglycemia measured by continuous glucose monitoring with novel long-acting insulin LY2605541 versus insulin glargine

OBJECTIVE

To use continuous glucose monitoring (CGM) to evaluate the impact of the novel, long-acting basal insulin analog LY2605541 on hypoglycemia and glycemic variability in patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

Hypoglycemia and glucose variability were assessed with CGM of interstitial glucose (IG) in a subset of patients with type 2 diabetes from a phase II, randomized, open-label, parallel study of LY2605541 (n = 51) or insulin glargine (GL) (n = 25). CGM was conducted on 3 consecutive days (72-84 h) during the week before week 0, 6, and 12 study visits.

RESULTS

Measured by CGM for 3 days prior to the 12-week visit, fewer LY2605541-treated patients experienced hypoglycemic events overall (50.0 vs. 78.3%, P = 0.036) and nocturnally (20.5 vs. 47.8%, P = 0.027) and spent less time with IG ≤70 mg/dL than GL-treated patients during the 24-h (25 ± 6 vs. 83 ± 16 min, P = 0.012) and nocturnal periods (11 ± 5 vs. 38 ± 13 min, P = 0.024). These observations were detected without associated differences in the average duration of individual hypoglycemic episodes (LY2605541 compared with GL 57.2 ± 5.4 vs. 69.9 ± 10.2 min per episode, P = NS). Additionally, LY2605541-treated patients had lower within-day glucose SD for both 24-h and nocturnal periods.

CONCLUSIONS

By CGM, LY2605541 treatment compared with GL resulted in fewer patients with hypoglycemic events and less time in the hypoglycemic range and was not associated with protracted hypoglycemia.

Differential effects of vildagliptin and glimepiride on glucose fluctuations in patients with type 2 diabetes mellitus assessed using continuous glucose monitoring

AIM

To assess whether there is a difference in the effects of vildagliptin and glimepiride on glucose fluctuation in patients with type 2 diabetes mellitus (T2DM) using continuous glucose monitoring (CGM).

METHODS

This was an open-label, randomized cross-over study conducted in T2DM patients. A total of 24 patients (age: 58.3 ± 5.56 years, baseline HbA1c: 7.6 ± 0.50%) who were on stable metformin monotherapy (500-3000 mg) were enrolled, and all completed the study. Each patient received two 5-day treatments (vildagliptin 50 mg b.i.d. or glimepiride 2 mg q.d.) in a cross-over manner. Various biomarkers and blood glucose concentrations were measured following breakfast. The 24-h glucose profiles were also measured using the CGM device at baseline and after 5 days of treatment, and fluctuations in glucose levels were estimated from CGM data.

RESULTS

Both vildagliptin and glimepiride reduced postprandial glucose levels, based on both CGM data (15% vs. 16%) and measured plasma glucose (13% vs.17%). Vildagliptin showed lower glucose fluctuations than glimepiride as measured by mean amplitude of glycaemic excursions (MAGE, p = 0.1076), standard deviation (s.d., p = 0.1346) of blood glucose rate of change, but did not reach statistical significance attributed to the small sample size. MAGE was reduced by ∼20% with vildagliptin versus glimepiride. Vildagliptin led to statistically significant lowering of the rate of change in the median curve (RCMC) and interquartile range (IQR) of glucose. Treatment with vildagliptin significantly increased the levels of active glucagon-like peptide-1 by 2.36-fold (p ≤ 0.0001) and suppressed glucagon by 8% (p = 0.01), whereas glimepiride significantly increased the levels of insulin and C-peptide by 21% (p = 0.012) and 12% (p = 0.003), respectively.

CONCLUSIONS

Vildagliptin treatment was associated with less fluctuation of glucose levels than glimepiride treatment as assessed by 24-h CGM device, suggesting vildagliptin may have the potential to offer long-term beneficial effects for patients with T2DM in preventing the development of complications of diabetes.

Glucose Fluctuations during Gestation: An Additional Tool for Monitoring Pregnancy Complicated by Diabetes

Continuous glucose monitoring (CGM) gives a unique insight into magnitude and duration of daily glucose fluctuations. Limited data are available on glucose variability (GV) in pregnancy. We aimed to assess GV in healthy pregnant women and cases of type 1 diabetes mellitus or gestational diabetes (GDM) and its possible association with HbA1c. CGM was performed in 50 pregnant women (20 type 1, 20 GDM, and 10 healthy controls) in all three trimesters of pregnancy. We calculated mean amplitude of glycemic excursions (MAGE), standard deviation (SD), interquartile range (IQR), and continuous overlapping net glycemic action (CONGA), as parameters of GV. The high blood glycemic index (HBGI) and low blood glycemic index (LBGI) were also measured as indicators of hyperhypoglycemic risk. Women with type 1 diabetes showed higher GV, with a 2-fold higher risk of hyperglycemic spikes during the day, than healthy pregnant women or GDM ones. GDM women had only slightly higher GV parameters than healthy controls. HbA1c did not correlate with GV indicators in type 1 diabetes or GDM pregnancies. We provided new evidence of the importance of certain GV indicators in pregnant women with GDM or type 1 diabetes and recommended the use of CGM specifically in these populations.

Continuous glucose monitors: current status and future developments

PURPOSE OF REVIEW

Advances in diabetes technologies allow patients to manage their diabetes with greater precision and flexibility. Many recent studies show that continuous glucose monitors (CGMs) can be used to tighten glycemic control safely and to ease certain burdens of diabetes self-management.

RECENT FINDINGS

The following summary reflects the most recent findings in CGM and provides an overall review of who would most benefit from CGM use. Benefits of CGM may vary based on age, type of diabetes, pregnancy, health, sleep, or heart rate. Accuracy and reliability are critical in current uses of CGM and especially for new and future systems that automate insulin partially (e.g., low glucose suspend) or entirely (e.g., 'fully closed-loop' artificial pancreas). Clinicians are simultaneously testing available products in new patient groups such as the critically ill and type 2 diabetes patients not using mealtime insulin.

SUMMARY

In a widening set of circumstances, use of CGM has been shown to promote safer and more effective glycemic control than self-monitoring of blood glucose. Imperfections remain in certain scenarios such as hypoglycemia and in certain populations such as young children. Ongoing research on sensors and calibration software should translate to better systems.