Glucose Variability: Timing, Risk Analysis, and Relationship to Hypoglycemia in Diabetes

Glucometric parameter changes in patients with type 2 diabetes during ramadan fasting: A prospective comparative real-world study

Background

This study assessed glucometric changes in Type 2 diabetes mellitus (T2DM) patients before, during, and after Ramadan fasting using an intermittently scanned continuous glucose monitoring system (isCGMS).

Methods

This prospective comparative study included T2DM patients aged 30-70 years who were receiving nonintensive insulin in Riyadh, Saudi Arabia. In addition to the baseline characteristics, glycated hemoglobin (HbA1c) and ambulatory glucose profile (AGP)-derived metric data were collected at three specific points: pre-, during-, and post-Ramadan. Self-care activities during Ramadan were evaluated using the Diabetes Self-Management Questionnaire (DSMQ).

Results

Overall, a total of 93 T2DM patients were enrolled in the study. Their mean age ±SD age was 47.9 ± 7.5 years, and 51.6 % of them were males. Compared with pre- and post-Ramadan, there was a significant decrease in HbA1c (p < 0.001 for both periods), average glucose level (p = 0.001 and p = 0.026, respectively), glucose variability (p = 0.043 and p = 0.005, respectively), and % time above the range of 181-250 mg/dL (p < 0.001 for both periods), as well as a significant increase in % time in target (70-180 mg/dL) during Ramadan (p < 0.001 for both periods). However, the % time below 54 mg/dL was slightly greater during Ramadan than both pre- and post-Ramadan (p < 0.001 and p = 0.002, respectively). Furthermore, 32.3 % reported inadequate self-care behaviors during Ramadan.

Conclusions

Ramadan fasting could improve glucose levels in T2DM patients who were not on intensive insulin, with a relatively low incidence of hypoglycemia.

Adaptive Biobehavioral Control: A Pilot Analysis of Human-Machine Coadaptation in Type 1 Diabetes

Background: While it is well recognized that an automated insulin delivery (AID) algorithm should adapt to changes in physiology, it is less understood that the individual would also have to adapt to the AID system. The adaptive biobehavioral control (ABC) method presented here attempts to compensate for this deficiency by including AID into an information cloud-based ecosystem. Methods: The Web Information Tool (WIT) implements the ABC concept via the following: (1) a Physiological Adaptation Module (PAM) that tracks metabolic changes and adapts AID parameters accordingly and (2) a Behavioral Adaptation Module (BAM) that provides information feedback. The safety of WIT (primary outcome) was assessed in an 8-week randomized, two-arm parallel pilot study. All participants used the Control-IQ® AID system enhanced with PAM, but only those in the Experimental group had access to BAM. Secondary glycemic outcomes were computed using the 2-week baseline period and the last 2 weeks of treatment. Results: Thirty participants with type 1 diabetes (T1D) completed all study procedures (17 female/13 male; age: 40 ± 14 years; HbA1c: 6.6% ± 0.5%). No severe hypoglycemia, DKA, or other serious adverse events were reported. Comparing the Experimental and Control groups, no significant difference was observed in time in range (70-180 mg/dL): 74.6% vs 73.8%, adjusted mean difference: 2.65%, 95% CI (-1.12%,6.41%), P = 0.161. Time in 70-140 mg/dL was significantly higher in the Experimental group: 50.7% vs 49.2%, 5.71% (0.44%,10.97%), P = 0.035, without increased time below range: 0.54% (-0.09%,1.17%), P = 0.089. Conclusion: The results demonstrate that it is safe to integrate an AID system into the WIT ecosystem. Validation in a full-scale study is ongoing.

Perceived Cognitive Function and Glycemic Variability: Baseline Results From a Cognitive Rehabilitation Intervention

PURPOSE

The purpose of this study was to examine the association between glucose variability, diabetes self-management, and cognitive function in participants enrolled in a cognitive rehabilitation intervention for people with type 2 diabetes.

METHODS

Baseline data from the Memory, Attention, and Problem-Solving Skills for Diabetes randomized controlled trial (n = 95; mean age 65.6 years, SD 5.99; 59.3% female; 59% non-Hispanic White) were analyzed and included scores from the PROMIS Cognitive Function version 2, a measure of perceived cognitive function; glucose variability measurements from continuous glucose monitors; and scores on the Summary of Diabetes Self-Care Activities Survey.

RESULTS

Participants had higher levels of perceived cognitive dysfunction than the US average. Lower PROMIS scores were associated with higher levels of glucose variability. Better perceived cognitive health was related to better diabetes self-management. Glucose variability, measured by the coefficient of variation, was a significant predictor of perceived cognitive function.

CONCLUSIONS

Perceived cognitive function was associated with diabetes self-management and glucose variability. Understanding this association can support the development of interventions to mitigate effects associated with glucose variability and changes in cognitive function. Including measurements of perceived cognitive function in assessments has the potential to alert health care providers about the need for additional support in diabetes management and the possibility of cognitive impairment that may need further objective assessment.

Observational study on stability of within-day glycemic variability of type 2 diabetes inpatients treated with decoctions of traditional Chinese medicine

Background

Within-day glycemic variability (GV), characterized by frequent and significant fluctuations in blood glucose levels, is a growing concern in hospitalized patients with type 2 diabetes mellitus (T2DM). It is associated with an increased risk of hypoglycemia and potentially higher long-term mortality rates. Robust clinical evidence is needed to determine whether traditional Chinese medicine (TCM) decoctions can be a beneficial addition to the management of within-day GV in this patient population.

Methods

This retrospective cohort study utilized data from adult inpatients diagnosed with T2DM admitted to the Traditional Chinese Medicine Hospital of Kaifeng. The primary outcome investigated was the association between the use of TCM decoctions and improved stability of within-day GV. Blood glucose variability was assessed using the standard deviation of blood glucose values (SDBG). For each patient, the total number of hospitalization days with SDBG below 2 mmol/L was calculated to represent within-day GV stability. Hospitalization duration served as the secondary outcome, compared between patients receiving TCM decoctions and those who did not. The primary analysis employed a multivariable logistic regression model, with propensity score matching to account for potential confounding variables.

Results

A total of 1,360 patients were included in the final analysis. The use of TCM decoctions was significantly associated with enhanced stability of within-day GV (OR = 1.77, 95% CI: 1.34-2.33, P < 0.01). This association was most prominent in patients with a diagnosis of deficiency syndrome (predominantly qi-yin deficiency, accounting for 74.8% of cases) and a disease duration of less than 5 years (OR = 2.28, 95% CI: 1.21-4.29, P = 0.03). However, TCM decoctions did not exert a statistically significant effect on hospitalization duration among patients with T2DM (OR = 0.96, 95% CI: 0.91-1.01, P = 0.22).

Conclusion

This study suggests that TCM decoctions may be effective in improving within-day GV stability in hospitalized patients with T2DM. This effect appears to be most pronounced in patients diagnosed with deficiency syndrome, particularly those with qi-yin deficiency and a shorter disease course. Further investigation is warranted to confirm these findings and elucidate the underlying mechanisms.

Time With Rapid Change of Glucose

BACKGROUND

A variety of metrics are used to describe glycemic variation, some of which may be difficult to comprehend or require complex strategies for smoothing of the glucose curve. We aimed to describe a new metric named time with rapid change of glucose (TRC), which is presented as percentage of time, similar to time above range (TAR), time in range (TIR), and time below range (TBR).

METHOD

We downloaded glucose data for 90 days from 159 persons with type 1 diabetes using the Abbott Freestyle Libre version 1. We defined TRC as the proportion of time (%) with an absolute rate of change of glucose > 1.5 mmol/L/15 minutes (1.8mg/dL/min) corresponding to a minimum rate of change for glucose in the 3.9-10.0 mmol/L (70-180 mg/dL) range within 1 hour. TRC is related to the other glucose variability metrics: CV within day (CVw) and mean amplitude of glycemic excursion (MAGE).

RESULTS

The more than 1.27 million glucose rates were t-location scale distributed with SD 0.91 mmol/L/15 min (1.1 mg/dL/15 min). The median TRC was 6.9% (IQR 4.5%-9.5%). The proportion of TRC with positive slope was 3.9% (2.6%-5.3%) and significantly higher than the proportion with negative slope 2.8% (1.5%-4.4%) P < .001. TRC correlated with CVw and MAGE (Spearman's correlation coefficient .56 and .65, respectively, P < .001).

CONCLUSION

TRC is proposed as an easily perceived metric to compare the performance of hybrid or fully automated closed-loop insulin delivery systems to obtain glucose homeostasis.

Association between short-term glucose fluctuations and cognition in patients with acute ischemic stroke complicated by type 2 diabetes mellitus

OBJECTIVES

Glucose fluctuations are more harmful than persistent hyperglycemia for chronic complications of diabetes. However, the relationship between cognition and glucose fluctuations in patients with acute ischemic stroke (AIS) complicated by type 2 diabetes mellitus (T2DM) remains unclear. We aimed to evaluate the association between short-term glucose fluctuations and cognition in patients with AIS complicated by T2DM.

DESIGN

A cohort study with a 2-year follow-up.

SETTING AND PARTICIPANTS

We included 554 patients with mild AIS (mean age: 62 years; 170 females and 384 males).

MEASUREMENTS

Glucose variability (GV) was evaluated using glycated hemoglobin (HbA1c), stress hyperglycemia (SHR), standard deviation of blood glucose (SDBG), mean postprandial blood glucose (MPBG), mean amplitude of glycemic excursion (MAGE), and time in range (TIR). We evaluated the relationship between GV, fasting blood glucose (FBG) and cognition during the acute phase using linear regression analysis. We evaluated the relationship between GV, FBG and the occurrence of post-stroke cognitive impairment (PSCI) using a logistic regression model. Mediation analyses were fitted to explore whether the relationships of HbA1c with cognition were mediated by cerebral small vessel disease (CSVD).

RESULTS

A clear pattern of age-related GV was observed. Higher SHR in middle-aged participants; higher HbA1c, and lower TIR in older participants; and higher MAGE, MPBG, and SDBG across a broad age range (50-80 years) were associated with cognitive impairment in the acute phase of AIS. Higher SHR and SDBG together with lower TIR in middle-aged participants, higher HbA1c in older participants, and higher FBG, MPBG, and MAGE across a broad age range (50-80 years) were associated with the occurrence of PSCI. The association between HbA1c and cognition was partially mediated (proportion: 7-16%) by CSVD.

CONCLUSIONS

Short-term glucose fluctuations are associated with cognition and a higher risk of PSCI in patients with AIS complicated by T2DM. CSVD might play an important role in the relationship between short-term glucose fluctuations and cognition.

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

AIMS

Continuous glucose monitoring (CGM) metrics can assist diabetes management. Consensus statements recommend > 70 % time in range (TIR) and ≤ 36 % glucose coefficient of variation (CV). However, how these targets perform in clinical practice is unknown. This retrospective, longitudinal cohort study analyzed relationships between TIR, CV, glycated hemoglobin (HbA1c), and hypoglycemia in a real-world setting.

METHODS

Data of 542 adults with type 1 diabetes who used CGM (January 2014-July 2020) were analyzed. Associations between TIR and HbA1c at the same and subsequent visits, incidence rate ratios (IRRs) for hypoglycemia at different CVs, and number of hypoglycemic events at cross-sections of HbA1c and CV were estimated by regression.

RESULTS

TIR was inversely related to HbA1c; for every 10 % increase in TIR, HbA1c was significantly reduced by 0.34 % (4 mmol/mol) and 0.20 % (2 mmol/mol) at the same and subsequent visits, respectively. Level 2 hypoglycemia was significantly reduced at CV < 30 %, 30-33 %, 33.1-36 %, and 36.1-40 %: adjusted IRRs vs CV ≥ 40.1 % of 0.14, 0.28, 0.32, and 0.50, respectively. Hypoglycemic events were reduced at lower CV across HbA1c levels and at higher HbA1c across CV levels.

CONCLUSION

This study quantifies HbA1c improvements with increased TIR and hypoglycemia reductions with improved CV in clinical practice.

Prevalence, Safety, and Metabolic Control Among Danish Children and Adolescents with Type 1 Diabetes Using Open-Source Automated Insulin Delivery Systems

Background: Treatment of type 1 diabetes mellitus (T1DM) has become increasingly technical with rapid developments in integration of pumps and sensors to regulate insulin dosage, and patient-initiated solutions as open-source automated insulin delivery (OS-AID) systems, have gained popularity in people with diabetes. Studies have shown increased glycemic control and mental wellbeing in users of OS-AID systems. The aim of this study was to estimate the prevalence, the effect on metabolic control, the risk, and the effect on everyday life for users and their parents of OS-AID systems in Danish children and adolescents with T1DM. Methods: This retrospective cohort study recruited participants through pediatric diabetes outpatient clinics and social media. Surveys were distributed and current and retrospective data on glycemic control (HbA1c, time in range [TIR] etc.) were collected. Results: Fifty-six users of OS-AID systems out of 2950 Danish children and adolescents with T1DM were identified from all outpatient clinics in Denmark. Thirty-one responded on contact and were included (55% of the identified), median age 12 [interquartile range: 11-14] years, 51% females, and mean duration of use of OS-AID systems 2.37 ± 0.86 years. Glycemic control increased significantly with TIR increasing from mean 62.29% ± 13.68% to 70.12% ± 10.08%, *P < 0.01, and HbA1c decreasing from mean 50.13 ± 5.76 mmol/mol (6.7% ± 2.7%) to 47.86 ± 6.24 mmol/mol (6.5% ± 2.7%), **P < 0.05. No changes were found in safety parameters. Parents reported better quality of sleep evaluated by Pittsburgh Sleep Quality Index. Conclusion: This study is the first to provide knowledge on pediatric users of OS-AID systems in Denmark and found a prevalence of 1.89% for OS-AID systems, improved TIR, and no increased risk associated with use of OS-AID systems.

Continuous glucose monitoring metrics in pregnancy with type 1 diabetes mellitus

Managing diabetes during pregnancy is challenging, given the significant risk it poses for both maternal and foetal health outcomes. While traditional methods involve capillary self-monitoring of blood glucose level monitoring and periodic HbA1c tests, the advent of continuous glucose monitoring (CGM) systems has revolutionized the approach. These devices offer a safe and reliable means of tracking glucose levels in real-time, benefiting both women with diabetes during pregnancy and the healthcare providers. Moreover, CGM systems have shown a low rate of side effects and high feasibility when used in pregnancies complicated by diabetes, especially when paired with continuous subcutaneous insulin infusion pump as hybrid closed loop device. Such a combined approach has been demonstrated to improve overall blood sugar control, lessen the occurrence of preeclampsia and neonatal hypoglycaemia, and minimize the duration of neonatal intensive care unit stays. This paper aims to offer a comprehensive evaluation of CGM metrics specifically tailored for pregnancies impacted by type 1 diabetes mellitus.

Assessing the temporal within-day glycemic variability during hospitalization in patients with type 2 diabetes patients using continuous glucose monitoring: a retrospective observational study

AIMS

Frequent and extensive within-day glycemic variability (GV) in blood glucose levels may increase the risk of hypoglycemia and long-term mortality in hospitalized patients with diabetes. We aimed to assess the amplitude and frequency of within-day GV in inpatients with type 2 diabetes and to explore the factors influencing within-day GV.

METHODS

We conducted a single-center, retrospective observational study by analyzing hospital records and 10-day real-time continuous glucose monitoring data. Within-day GV was assessed using the coefficient of variation (%CV). The primary outcome was the amplitude and frequency of within-day GV. The frequency of within-day GV was assessed by the consecutive days (CD) of maintaining within the target %CV range after first reaching it (CD after first reaching the target) and the maximum consecutive days of maintaining within the target %CV range (Max-CD). The target %CV range was less than 24.4%. We evaluated the factors influencing within-day GV using COX regression and Poisson regression models.

RESULTS

A total of 1050 cases were analyzed, of whom 86.57% reduced the amplitude of within-day GV before the sixth day of hospitalization. Of the 1050 hospitalized patients, 66.57% stayed within the target %CV range for less than two days after first reaching the target and 69.71% experienced a Max-CD of fewer than four days. Reducing the average postprandial glucose excursion (hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.77-0.85; incidence rate ratios [IRR]: 0.72, 95% CI: 0.69-0.74) and the use of α-glucosidase inhibitors (IRR: 1.1, 95% CI: 1.01-1.18) and glucagon-like peptide-1 agonist (IRR: 1.30, 95% CI: 1.02-1.65) contributed to reducing the amplitude and decreasing the frequency of within-day GV. However, the use of insulin (HR: 0.64, 95% CI: 0.55-0.75; IRR: 0.86, 95% CI: 0.79-0.93) and glinide (HR: 0.47, 95% CI: 0.31-0.73; IRR: 0.84, 95% CI: 0.73-0.97) may lead to an increased frequency of within-day GV.

CONCLUSIONS

An increasing frequency of within-day GV was observed during the hospitalization in patients with type 2 diabetes, despite the effective reduction in the amplitude of within-day GV. Using medications designed to lower postprandial blood glucose could contribute to minimize the risk of frequent within-day GV.

Wearing the Lab: Advances and Challenges in Skin-Interfaced Systems for Continuous Biochemical Sensing

Continuous, on-demand, and, most importantly, contextual data regarding individual biomarker concentrations exemplify the holy grail for personalized health and performance monitoring. This is well-illustrated for continuous glucose monitoring, which has drastically improved outcomes and quality of life for diabetic patients over the past 2 decades. Recent advances in wearable biosensing technologies (biorecognition elements, transduction mechanisms, materials, and integration schemes) have begun to make monitoring of other clinically relevant analytes a reality via minimally invasive skin-interfaced devices. However, several challenges concerning sensitivity, specificity, calibration, sensor longevity, and overall device lifetime must be addressed before these systems can be made commercially viable. In this chapter, a logical framework for developing a wearable skin-interfaced device for a desired application is proposed with careful consideration of the feasibility of monitoring certain analytes in sweat and interstitial fluid and the current development of the tools available to do so. Specifically, we focus on recent advancements in the engineering of biorecognition elements, the development of more robust signal transduction mechanisms, and novel integration schemes that allow for continuous quantitative analysis. Furthermore, we highlight the most compelling and promising prospects in the field of wearable biosensing and the challenges that remain in translating these technologies into useful products for disease management and for optimizing human performance.

Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Over the past two decades, there has been continuous advancement in the accuracy and complexity of continuous glucose monitoring devices. Continuous glucose monitoring provides valuable insights into blood glucose dynamics, and can record glucose fluctuations accurately and completely. Glycemic variability (GV) is a straightforward measure of the extent to which a patient's blood glucose levels fluctuate between high peaks and low nadirs. Many studies have investigated the relationship between GV and complications, primarily in the context of type 2 diabetes. Nevertheless, the exact contribution of GV to the development of diabetes complications remains unclear. In this literature review, we aimed to summarize the existing evidence regarding the measurement, target level, pathophysiological mechanisms relating GV and tissue damage, and population-based studies of GV and diabetes complications. Additionally, we introduce novel methods for measuring GV, and discuss several unresolved issues of GV. In the future, more longitudinal studies and trials are required to confirm the exact role of GV in the development of diabetes complications.

Effects of a Novel Glucokinase Activator, Dorzagliatin, on Glycemic Control and Glucose Fluctuation in Drug-Naïve Patients with Type 2 Diabetes Mellitus

Aim

The prevalence rate of type 2 diabetes mellitus (T2DM) has been increasing and a large proportion of patients still do not achieve adequate or sustainable glycemic control on the basis of previous hypoglycemic treatment. In this present study, we explored whether dorzagliatin, a novel glucokinase activator (GKA), could improve glycemic control and lessen glucose fluctuation in drug-naïve patients with T2DM.

Methods

A self-comparative observational study of 25 drug-naïve patients with T2DM (aged 18-75 years and HbA1c of 7.5%-11.0%) treated with dorzagliatin 75 mg twice daily for 52 weeks. Before and after dorzagliatin intervention, the serum levels of hemoglobin A1c (HbA1c), insulin, and C-peptide were measured repeatedly during fasting and after a mixed meal. The continuous glucose monitoring (CGM) device was also used to obtain 24-hour glucose profiles and assess the changes in glycemic variability parameters.

Results

After 52 weeks of treatment with dorzagliatin, a numerally greater reduction in HbA1c of 1.03% from the baseline was observed in patients with T2DM, accompanied by significant improvement in insulin resistance and insulin secretion. Moreover, the standard deviation of blood glucose (SDBG) and the mean amplitude of glycemic excursion (MAGE) derived from CGM data were significantly decreased after dorzagliatin therapy. The 24-h glucose variation profile showed that study patients had obviously lower mean glucose levels during the postprandial period from the baseline to week 52, an effect also demonstrated by the significant decrease in the incremental area under glucose concentration versus time curve for 2 h (iAUC0-2 h) after meals.

Conclusions

This study suggests that dorzagliatin therapy could effectively improve glycemic control and glucose fluctuation in drug-naïve patients with T2DM.

Key indices of glycaemic variability for application in diabetes clinical practice

Near normal glycaemic control in diabetes consists to target daily glucose fluctuations and quarterly HbA1c oscillations in addition to overall glucose exposure. Consequently, the prerequisite is to define simple, and mathematically undisputable key metrics for the short- and long-term variability in glucose homeostasis. As the standard deviations (SD) of either glucose or HbA1c are dependent on their means, the coefficient of variation (CV = SD/mean) should be applied instead as it that avoids the correlation between the SD and mean values. A CV glucose of 36% is the most appropriate threshold between those with stable versus labile glucose homeostasis. However, when near normal mean glucose concentrations are achieved a lower CV threshold of <27 % is necessary for reducing the risk for hypoglycaemia to a minimal rate. For the long-term variability in glucose homeostasis, a CVHbA1c < 5 % seems to be a relevant recommendation for preventing adverse clinical outcomes.

Serum Cytokines and Growth Factors in Subjects with Type 1 Diabetes: Associations with Time in Ranges and Glucose Variability

The detrimental effect of hyperglycemia and glucose variability (GV) on target organs in diabetes can be implemented through a wide network of regulatory peptides. In this study, we assessed a broad panel of serum cytokines and growth factors in subjects with type 1 diabetes (T1D) and estimated associations between concentrations of these molecules with time in ranges (TIRs) and GV. One hundred and thirty subjects with T1D and twenty-seven individuals with normal glucose tolerance (control) were included. Serum levels of 44 cytokines and growth factors were measured using a multiplex bead array assay. TIRs and GV parameters were derived from continuous glucose monitoring. Subjects with T1D compared to control demonstrated an increase in concentrations of IL-1β, IL-1Ra, IL-2Rα, IL-3, IL-6, IL-7, IL-12 p40, IL-16, IL-17A, LIF, M-CSF, IFN-α2, IFN-γ, MCP-1, MCP-3, and TNF-α. Patients with TIR ≤ 70% had higher levels of IL-1α, IL-1β, IL-6, IL-12 p70, IL-16, LIF, M-CSF, MCP-1, MCP-3, RANTES, TNF-α, TNF-β, and b-NGF, and lower levels of IL-1α, IL-4, IL-10, GM-CSF, and MIF than those with TIR > 70%. Serum IL-1β, IL-10, IL-12 p70, MCP-1, MCP-3, RANTES, SCF, and TNF-α correlated with TIR and time above range. IL-1β, IL-8, IL-10, IL-12 p70, MCP-1, RANTES, MIF, and SDF-1α were related to at least one amplitude-dependent GV metric. In logistic regression models, IL-1β, IL-4, IL-10, IL-12 p70, GM-CSF, HGF, MCP-3, and TNF-α were associated with TIR ≤ 70%, and MIF and PDGF-BB demonstrated associations with coefficient of variation values ≥ 36%. These results provide further insight into the pathophysiological effects of hyperglycemia and GV in people with diabetes.

Glucose fluctuation promotes mitochondrial dysfunctions in the cardiomyocyte cell line HL-1

AIMS

Glycemic variability has been suggested as a risk factor for diabetes complications but the precise deleterious mechanisms remain poorly understood. Since mitochondria are the main source of energy in heart and cardiovascular diseases remain the first cause of death in patients with diabetes, the aim of the study was to evaluate the impact of glucose swings on mitochondrial functions in the cardiomyocyte cell line HL-1.

METHODS

HL-1 cells were exposed to low (LG, 2.8 mmol/l), normal (NG, 5.5 mmol/l), high (HG, 25 mmol/l) or intermittent high glucose (IHG, swing between low and high) every 2h during 12h (short-time treatment) or every 12h during 72h (long-time treatment). Anaerobic catabolism of glucose was evaluated by measuring glucose consumption and lactate production, oxidative phosphorylation was evaluated by polarography and ATP measurement, mitochondrial superoxide anions and the mitochondrial membrane potential (MMP) were analysed using fluorescent probes, and the protein oxidation was measured by oxyblot.

RESULTS

IHG and HG increased glucose consumption and lactate production compared to LG and NG but without any difference between short- and long-time treatments. After 72h and unlike to LG, NG and HG, we didn't observe any increase of the mitochondrial respiration in the presence of succinate upon IHG treatment. IHG, and to a lesser extent HG, promoted a time-dependent decrease of the mitochondrial membrane potential compared to LG and NG treatments. HG and IHG also increased superoxide anion production compared to LG and NG both at 12 and 72h but with a higher increase for IHG at 72h. At last, both HG and IHG stimulated protein oxidation at 72h compared to LG and NG treatments.

CONCLUSIONS

Our results demonstrated that exposure of HL-1 cells to glucose swings promoted time-dependent mitochondrial dysfunctions suggesting a deleterious effect of such condition in patients with diabetes that could contribute to diabetic cardiomyopathy.

Effectiveness of flash glucose monitoring in patients with type 1 diabetes and recurrent hypoglycemia between early and late stages after flash glucose monitoring initiation

AIMS

Evaluate the effectiveness of reimbursed flash glucose monitoring with optional alarms (FGM) in preventing severe hypoglycemia (SH) and reducing hypoglycemia exposure in T1D patients prone to hypoglycemia.

METHODS

Ambispective study in T1D patients treated with multiple daily injections (MDI) and prone to hypoglycemia, initiating reimbursed FGM (FreeStyle Libre 2). The primary outcome was the number of SH events (requiring third party assistance) and main secondary outcomes were time below range < 70 (TBR < 70) and < 54 mg/dL (TBR < 54), impaired awareness of hypoglycemia (IAH) and quality of life (QoL). Logistic regression models were constructed to explore variables associated with success of the intervention.

RESULTS

We included 110 patients (52.7 % women, mean age 47.8 ± 17.0 years). SH events at 1-year follow-up decreased from 0.3 ± 0.6 to 0.03 ± 0.2 (p < 0.001). Significant reductions in patients presenting an SH (26.4 % vs. 2.9 %, p < 0.001) and IAH (47.1 % vs. 25.9 %, p = 0.002) were observed, as well as improvements in QoL. TBR < 70 and TBR < 54 were not significantly reduced. Baseline GMI was inversely associated with a decrease in TBR < 70 [OR 0.37 (0.15-0.93)] and directly with an increase in time in range 70-180 mg/dL [OR 2.10 (1.03-4.28)].

CONCLUSIONS

FGM decreased SH and improved hypoglycemia awareness and QoL. Initial tight glycemic control was associated with a decrease in hypoglycemia, while patients with suboptimal control reduced hyperglycemia.

Mixed Meal Tolerance Test Versus Continuous Glucose Monitoring for an Effective Diagnosis of Persistent Post-Bariatric Hypoglycemia

Gastric bypass determines an increase in incretin secretion and glucose excursions throughout the day and may sometimes entail the development of severe post-bariatric hypoglycemia (PBH). However, there is no consensus on the gold standard method for its diagnosis. In this study, we evaluated the usefulness of a mixed meal tolerance test (MMTT) and continuous glucose monitoring (CGM) for the diagnosis of PBH, defined as glucose levels <54 mg/dL (3.0 mmol/L). We found that hypoglycemia occurred in 60% of patients after the MMTT and in 75% during CGM, and it was predominantly asymptomatic. The MMTT confirmed the diagnosis of PBH in 88.9%of patients in whom surgery had been performed more than three years ago, in comparison to 36.4% in cases with a shorter postsurgical duration. CGM diagnosed nocturnal asymptomatic hypoglycemia in 70% of patients, and daytime postprandial hypoglycemia in 25% of cases. The mean duration of asymptomatic hypoglycemia was more than 30 min a day. Patients with ≥2% of their CGM readings with hypoglycemia exhibited a higher degree of glucose variability than those with <1% of the time in hypoglycemia. Our results show that the MMTT may be a useful dynamic test to confirm the occurrence of hypoglycemia in a large number of patients with persistent and recurrent PBH during long-term follow-up after gastric bypass. CGM, on its part, helps identify hypoglycemia in the real-world setting, especially nocturnal asymptomatic hypoglycemia, bringing to light that PBH is not always postprandial.

The potential effect of metformin on fibroblast growth factor 21 in type 2 diabetes mellitus (T2DM)

Fibroblast growth factor 21 (FGF21) is a peptide hormone mainly synthesized and released from the liver. FGF21 acts on FGF21 receptors (FGFRs) and β-Klotho, which is a transmembrane co-receptor. In type 2 diabetes mellitus (T2DM), inflammatory disorders stimulate the release of FGF21 to overcome insulin resistance (IR). FGF21 improves insulin sensitivity and glucose homeostasis. Metformin which is used in the management of T2DM may increase FGF21 expression. Accordingly, the objective of this review was to clarify the metformin effect on FGF21 in T2DM. FGF21 level and expression of FGF2Rs are dysregulated in T2DM due to the development of FGF21 resistance. Metformin stimulates the hepatic expression of FGF21/FGF2Rs by different signaling pathways. Besides, metformin improves the expression of β-Klotho which improves FGF21 sensitivity. In conclusion, metformin advances FGF21 signaling and decreases FGF21 resistance in T2DM, and this might be an innovative mechanism for metformin in the enhancement of glucose homeostasis and metabolic disorders in T2DM patients.

Clinically-Similar Clusters of Daily CGM Profiles: Tracking the Progression of Glycemic Control Over Time

BACKGROUND

The adoption of CGM results in vast amounts of data, but their interpretation is still more art than exact science. The International Consensus on Time in Range (TIR) proposed the widely accepted TIR system of metrics, which we now take forward by introducing a finite and fixed set of clinically-similar clusters (CSCs), such that the TIR metrics of the daily CGM profiles within a cluster are homogeneous.

METHODS

CSC definition and validation used 204,710 daily CGM profiles in health, type 1 and type 2 diabetes (T1D, T2D), on different treatments. The CSCs were defined using 23,916 daily CGM profiles (Training set), and the final fixed set of CSCs was obtained using another 37,758 profiles (Validation set). The Testing set (143,036 profiles) was used to establish the robustness and generalizability of the CSCs.

RESULTS

The final set of CSCs contains 32 clusters. Any daily CGM profile was classifiable to a single CSC which approximated common glycemic metrics of the daily CGM profile, as evidenced by regression analyses with 0 intercept (R-squares≥0.83, e.g., correlation≥0.91), for all TIR and several other metrics. The CSCs distinguished CGM profiles in health, T2D, and T1D on different treatments, and allowed tracking of the daily changes in a person's glycemic control over time.

CONCLUSION

Daily CGM profiles can be classified into one of 32 prefixed CSCs, which enables a host of applications, e.g. tabulated data interpretation and algorithmic approaches to treatment, database indexing, pattern recognition, and tracking disease progression.

Continuous Glucose Monitoring in Patients Following Simultaneous Pancreas-Kidney Transplantation: Time in Range and Glucose Variability

Simultaneous pancreas-kidney transplantation (SPKT) can improve long-term patient survival and restore endogenous insulin secretion in recipients with type 1 diabetes (T1D). There are currently few data on glucose fluctuations assessed by continuous glucose monitoring (CGM) after SPKT. Aim: to evaluate CGM-derived time in range (TIR) and glucose variability (GV) in patients with T1D and functioning pancreatic grafts after SPKT. Fifty-four CGM recordings from 43 patients, 15 men and 28 women, aged 34 (31; 39) years were analyzed. Time since SKPT was up to 1 year (group 1, n = 13), from 1 to 5 years (group 2, n = 15), and from 5 to 12 years (group 3, n = 26). TIR (3.9-10 mmol/L), Time Above Range (TAR), Time Below Range (TBR), and GV parameters were estimated. There were no differences in mean glucose (5.5 [5.1; 6.2], 5.9 [5.4; 6.2], and 5.9 [5.6; 6.7] mmol/L), TIR (97.6 [92.8-99.1], 97.2 [93.2; 99.1], and 97.5 [93.4; 99]%); TAR (0, 1.8 [1.3; 3.7], and 2.5 [2; 5]%), TBR (5 [3.3; 12.7], 4.1 [2.2; 10.1], and 3.5 [1.3; 6.5]%) and GV parameters between three groups (all p > 0.05). Thus, recipients with functioning pancreatic grafts demonstrate remarkably high TIR and low GV after SPKT.

Hyperglycemia and Other Glycemic Measures Throughout Therapy for Pediatric Acute Lymphoblastic Leukemia and Lymphoma

Transient hyperglycemia during induction chemotherapy is associated with increased morbidity and mortality in patients with acute lymphoblastic leukemia (ALL). Treatment with glucocorticoids, asparaginase, and stress are the proposed causal factors. Although these risks are not exclusive to induction, glycemic control throughout the remainder of ALL/lymphoma (ALL/ALLy) therapy has not been described. Furthermore, prior research has been limited to transient hyperglycemia. This study aimed to characterize glycemic control throughout ALL/ALLy and to evaluate risk factors and outcomes associated with increased mean glucose and glucose coefficient of variation (glucose CV) during induction chemotherapy. The records for 220 pediatric/young adult patients, age 1 to 26 years, who underwent treatment for ALL/ALLy from 2010 to 2014 at Children's Hospital Colorado were retrospectively reviewed. Measures of glycemic control were calculated for each cycle. For the cycle with the highest mean glucose, induction (n=208), multivariable models were performed to identify potential risk factors and consequences of increased glucose. Highest mean glucose by cycle were induction 116 mg/dL, pretreatment 108 mg/dL, delayed intensification 96 mg/dL, and maintenance 93 mg/dL; these cycles also had the most glycemic variability. During induction, patients with Down syndrome, or who were ≥12 years and overweight/obese, had higher mean glucoses; age and overweight/obese status were each associated with increased glucose CV. In multivariable analysis, neither induction mean glucose nor glucose CV were associated with increased hazard of infection, relapse, or death.

A randomized trial on the effect of transcutaneous electrical nerve stimulator on glycemic control in patients with type 2 diabetes

Transcutaneous electrical nerve stimulator (TENS) has been demonstrated to be beneficial in glycemic control in animal models, but its application in humans has not been well studied. We randomly assigned 160 patients with type 2 diabetes on oral antidiabetic drugs 1:1 to the TENS study device (n = 81) and placebo (n = 79). 147 (92%) randomized participants (mean [SD] age 59 [10] years, 92 men [58%], mean [SD] baseline HbA_1c level 8.1% [0.6%]) completed the trial. At week 20, HbA_1c decreased from 8.1% to 7.9% in the TENS group (- 0.2% [95% CI - 0.4% to - 0.1%]) and from 8.1% to 7.8% in the placebo group (- 0.3% [95% CI - 0.5% to - 0.2%]) (P = 0.821). Glycemic variability, measured as mean amplitude of glycemic excursion (MAGE) at week 20 were significantly different in the TENS group vs. the placebo group (66 mg/dL [95% CI 58, 73] vs. 79 mg/dL [95% CI 72, 87]) (P = 0.009). Our study provides the clinical evidence for the first time in humans that TENS does not demonstrate a statistically significant HbA_1c reduction. However, it is a safe complementary therapy to improve MAGE in patients with type 2 diabetes.

The Association of Glucose Variability and Dementia Incidence in Latinx Adults with Type 2 Diabetes: A Retrospective Study

Latinx adults with both cognitive dysfunction and type 2 diabetes mellitus (T2DM) are significantly more likely than Latinx adults with diabetes alone to have complications such as cardiovascular disease. Glucose variability may be a risk for dementia, but the course of glucose variability in the time before a dementia diagnosis for Latinx adults with T2DM has not been examined. We used a 10-year retrospective cohort of medical records of Latinx patients with T2DM who had at least one use of a continuous glucose monitor. The objective was to examine how glucose variability was associated with future dementia diagnoses. A total of 116 charts were included. Mean of daily differences and mean amplitude of glycemic excursions were more strongly associated with dementia diagnoses than other variability indices (p < .01). Understanding the relationships between cognitive function, glucose variability, and barriers to health care can translate into improved interventions to enhance diabetes care.

Expert Consensus Recommendations on Time in Range for Monitoring Glucose Levels in People with Diabetes: An Indian Perspective

Keeping up with the global scenario, diabetes prevalence is on rise in India. Inadequate glycemic control is a major cause of diabetes-related morbidity and mortality. The conventional standards of care (SOC) in diabetes, including self-monitoring of blood glucose and measurement of glycated hemoglobin, have supported achievement of glycemic control, yet there are a few limitations. With the use of current technologies and metrics, such as continuous glucose monitoring (CGM) and standardized CGM data reporting, the continuous real-time glucose levels can be measured, and importantly, the percentage of time above, below, and within the target glucose range can be calculated, which facilitates patient-centric care, a current goal in diabetes management. International consensus recommendations endorse the incorporation of CGM and CGM data reporting in SOC for diabetes management. The guidelines provide time in range (TIR) thresholds for different patient populations and different types of diabetes. However, extrapolation of these global guidelines does not aptly cover the Indian population, which has diverse diet, culture, and religious practices. In this context, a consensus meeting was held in India in 2021 with experts in the field of diabetes care. The purpose of the meeting was to develop consensus recommendations for TIR thresholds for different patient profiles in India. Those expert recommendations, together with an evidence-based review, are reported here. The aim of this agreement is to aid clinicians across India to routinely use CGM and CGM data reports for optimizing individualized diabetes care, by implementing clinical targets for TIR.

Software Packages and Tools for the Analysis of Continuous Glucose Monitoring Data

The advancement of technology in the field of glycemic control has led to the widespread use of continuous glucose monitoring (CGM), which can be nowadays obtained from wearable devices equipped with a minimally invasive sensor, that is, transcutaneous needle type or implantable, and a transmitter that sends information to a receiver or smart device for data storage and display. This work aims to review the currently available software packages and tools for the analysis of CGM data. Based on the purposes of this work, 12 software packages have been identified from the literature, published until December 2021, namely: GlyCulator, EasyGV (Easy Glycemic Variability), CGM-GUIDE^© (Continuous Glucose Monitoring Graphical User Interface for Diabetes Evaluation), GVAP (Glycemic Variability Analyzer Program), Tidepool, CGManalyzer, cgmanalysis, GLU, CGMStatsAnalyser, iglu, rGV, and cgmquantify. Comparison of available software packages and tools has been done in terms of main characteristics (i.e., publication year, presence of a graphical user interface, availability, open-source code, number of citations, programming language, supported devices, supported data format and organization of the data structure, documentation, presence of a toy example, video tutorial, data upload and download, measurement-units conversion), preprocessing procedures, data display options, and computed metrics; also, each of the computed metrics has been analyzed in terms of its adherence to the American Diabetes Association (ADA) 2017 international consensus on CGM data analysis and the ADA 2019 international consensus on time in range. Eventually, the agreement between metrics computed by different software and tools has been investigated. Based on such comparison, usability and complexity of data management, as well as the possibility to perform customized or patients-group analyses, have been discussed by highlighting limitations and strengths, also in relation to possible different user categories (i.e., patients, clinicians, researchers). The information provided could be useful to researchers interested in working in the diabetic research field as to clinicians and endocrinologists who need tools capable of handling CGM data effectively.

Anagliptin twice-daily regimen improves glycaemic variability in subjects with type 2 diabetes: A double-blind, randomized controlled trial

AIM

To determine whether the twice-daily (BID) regimen is superior to the once-daily (QD) regimen for managing glycaemic variability by comparing the effects of anagliptin 100 mg BID versus sitagliptin 100 mg QD.

MATERIALS AND METHODS

A double-blinded, randomized, multicentre study was performed in 89 patients with type 2 diabetes treated with metformin alone (6.5% < HbA1c < 8.5%). Subjects were randomly assigned to anagliptin 100 mg BID or sitagliptin 100 mg QD in a 1:1 ratio for 12 weeks. Continuous glucose monitoring was used to measure the mean amplitude of glycaemic excursion (MAGE) and postprandial time in range (TIR) before and after dipeptidyl peptidase-4 (DPP-4) inhibitor treatment to compare glycaemic variability.

RESULTS

The decrease from baseline in MAGE at 12 weeks after DPP-4 inhibitor treatment was significantly greater in the anagliptin BID group than in the sitagliptin QD group (P < .05); -30.4 ± 25.6 mg/dl (P < .001) in the anagliptin group versus -9.5 ± 38.0 mg/dl (P = .215) in the sitagliptin group. The TIR after dinner increased by 33.0% ± 22.0% (P < .001) in the anagliptin group and by 14.6% ± 28.2% (P = .014) in the sitagliptin group, with a statistically significant difference (P = .009). No statistically significant differences were observed between the groups in the changes in HbA1c and fasting plasma glucose (FPG).

CONCLUSIONS

The anagliptin BID regimen for the treatment of type 2 diabetes was superior in blood glucose control after dinner to improve glycaemic variability, as indicated by MAGE and TIR, but was equivalent to the QD regimen in terms of HbA1c and FPG.

Impact of sleep and physical activity habits on real‐life glycaemic variability in patients with type 2 diabetes

The aim of this study was to better characterise whether sleep habits, eating schedule and physical activity in real-life are associated with glycaemic control in patients with type 2 diabetes. A total of 28 patients (aged 60 years [58; 66], 54% female) with type 2 diabetes treated with basal-bolus insulin therapy administered by insulin pumps were analysed. Glycaemic data measured by Flash Glucose Monitor System, physical activity and sleep data measured by accelerometer, and meal schedules were simultaneously collated with insulin pump administration data, for 7 days in real-life. Their respective impact on the time spent in target, in hypoglycaemia, in hyperglycaemia and on glycaemic variability was evaluated. Multiple regressions showed that the total daily dose of meal boluses of insulin was inversely associated with the coefficient of variation (CV; coefficient β = -0.073; 95% confidence interval: -0.130, -0.015; p = 0.016), as well as sleep duration. The higher the sleep duration, the lower the glycaemic variability (coefficient β = -0.012; 95% confidence interval: -0.023, -0.002; p = 0.027). The mean 7 days physical activity of the subjects was very low and was not associated with glycaemic control on the 7 days mean values. However, days with at least 1 hr spent in physical activity higher than 1.5 METs were associated with less glycaemic variability that same day. This real-life observation highlights the importance of sufficient sleep duration and regular physical activity to lessen the glycaemic variability of patients with type 2 diabetes.

The hemoglobin glycation index predicts the risk of adverse cardiovascular events in coronary heart disease patients with type 2 diabetes mellitus

Background

Previous studies have shown that the hemoglobin glycation index (HGI) can be used as a predictor of diabetic complications. However, limited information is currently available to indicate the correlation between HGI and comorbidity of coronary heart disease (CHD) and diabetes. This study aimed to evaluate the potential of HGI to predict major adverse cardiovascular events (MACEs) in CHD patients with type 2 diabetes mellitus (T2DM) undergoing percutaneous coronary intervention (PCI).

Materials and methods

A total of 918 CHD patients with T2DM were enrolled in a 3-year retrospective cohort study, from December 2017 to December 2020 at the First Affiliated Hospital of Zhengzhou University. Data including fasting blood glucose (FPG/FBG) and glycated hemoglobin A1c (HbA1c) were collected. HGI was calculated as actual measured HbA1c minus predicted HbA1c. Three groups were further divided based on the levels of HGI, including low, medium, and high levels.

Result

Kaplan Meier analysis indicated that elevated HGI was strongly associated with the occurence of MACE (log-rank P < 0.001). Multivariate Cox regression analysis revealed that elevated HGI was an independent risk factor for incident MACE in CHD patients with T2DM [adjusted hazard ratio (HR): 1.473; 95% confidence interval (CI): 1.365-1.589, P < 0.001].

Conclusions

Hemoglobin glycation index is an independent predictor of MACE events in CHD patients with T2DM. High HGI indicates a higher risk of MACE occurrence.

Essential Continuous Glucose Monitoring Metrics: The Principal Dimensions of Glycemic Control in Diabetes

Background: With the proliferation of continuous glucose monitoring (CGM), a number of metrics were developed to assess quality of glycemic control. Many of them are highly correlated. Thus, we aim to identify the principal dimensions of glycemic control-a minimal set of metrics, necessary and sufficient for comprehensive assessment of diabetes management. Methods: Seventy-five thousand five hundred sixty-three 2-week CGM profiles recorded in six studies by 790 individuals with type 1 or type 2 diabetes were used to compute mean glucose (MG), percentage time >180 mg/dL (TAR), >250 mg/dL (TAR2), <70 mg/dL (TBR), <54 mg/dL (TBR2), and coefficient of variation (CV). The true dimensionality of the glycemic-metric space was identified in a training set (53,380 profiles) and validated in an independent test set (22,183 profiles). Results: Correlation analysis identified two blocks of metrics-(MG, TAR, TAR2) and (TBR, TBR2, CV)-each with high internal correlation, but insignificant between-block correlation, suggesting that the true dimensionality of the glycemic-metric space is 2. Principal component analysis confirmed two essential metrics quantifying exposure to hyperglycemia (i.e., treatment efficacy) and risk for hypoglycemia (i.e., treatment safety), and explaining ∼90% of the variance in the training and test data. Conclusion: Two essential metrics, treatment efficacy and treatment safety, are necessary and sufficient to characterize glycemic control in diabetes. Thus, quantitatively, diabetes treatment optimization is reduced to a two-dimensional problem, meaning that minimizing both exposure to hyperglycemia and risk for hypoglycemia will lead to improvement in any other metric of glycemic control.

Patient-Tailored Decision Support System Improves Short- and Long-Term Glycemic Control in Type 2 Diabetes

BACKGROUND

The increasing prevalence of type 2 diabetes mellitus (T2D) and specialist shortage has caused a healthcare gap that can be bridged by a decision support system (DSS). We investigated whether a diabetes DSS can improve long- and/or short-term glycemic control.

METHODS

This is a retrospective observational cohort study of the Diabetiva program, which offered a patient-tailored DSS using Karlsburger Diabetes-Management System (KADIS) once a year. Glycemic control was analyzed at baseline and after 12 months in 452 individuals with T2D. Time in range (TIR; glucose 3.9-10 mmol/L) and Q-Score, a composite metric developed for analysis of continuous glucose profiles, were short-term and HbA1c long-term measures of glycemic control. Glucose variability (GV) was also measured.

RESULTS

At baseline, one-third of patients had good short- and long-term glycemic control. Q-Score identified insufficient short-term glycemic control in 17.9% of patients with HbA1c <6.5%, mainly due to hypoglycemia. GV and hyperglycemia were responsible in patients with HbA1c >7.5% and >8%, respectively. Application of DSS at baseline improved short- and long-term glycemic control, as shown by the reduced Q-Score, GV, and HbA1c after 12 months. Multiple regression demonstrated that the total effect on GV resulted from the single effects of all influential parameters.

CONCLUSIONS

DSS can improve short- and long-term glycemic control in individuals with T2D without increasing hypoglycemia. The Q-Score allows identification of individuals with insufficient glycemic control. An effective strategy for therapy optimization could be the selection of individuals with T2D most at need using the Q-Score, followed by offering patient-tailored DSS.

Glycemic Outcomes in Baseline Hemoglobin A1C Subgroups in the International Diabetes Closed-Loop Trial

Using a closed-loop system significantly improves time in range (TIR) 70-180 mg/dL in patients with type 1 diabetes (T1D). In a 6-month RCT, 112 subjects were randomly assigned to closed-loop control (Tandem Control-IQ) after obtaining 2 weeks of baseline Continuous glucose monitoring (CGM) data from sensor-augmented pump therapy. We compared glycemic outcomes from baseline to end of study among subgroups classified by baseline HbA1c levels. All HbA1c subgroups showed an improvement in TIR due to reduction of both hyperglycemia and hypoglycemia. Those with HbA1c <6.5% improved mostly by reducing nocturnal hypoglycemia due to the automated basal insulin adjustments. Those with HbA1c ≥8.5% improved mostly by reducing daytime and nocturnal hyperglycemia due to both automated basal insulin adjustments and correction boluses during the day. There does not appear to be any reason to exclude individuals with T1D from automated insulin delivery based on their HbA1c. Clinical Trial Identifier: NCT03563313.

Effect of high-protein vs. high-fat snacks before lunch on glycemic variability in prediabetes: A study protocol for a randomized controlled trial

Background

China has the largest number of patients with Type 2 Diabetes Mellitus (T2DM), and it tends to increasingly grow in the future, putting an enormous burden on disease control and prevention in China. While glycemic variability (GV) came to be an important indicator of blood glucose control in diabetic patients, studies suggested that premeal snacks may help blood glucose control, but there are still some problems to be researched. Therefore, we designed this trial to evaluate which kind of premeal snacks would lead to better effects on GV under two diet patterns in pre-diabetes subjects and to evaluate assessments of acceptability and compliance, behavior, and metabolism changes in individuals will be described.

Methods and analysis

The study is a single-center, open-label, multiparallel group, randomized controlled trial. A total of 32 male and female volunteers will be randomized into 4 groups in a single allocated ratio of soy milk (powder) snack, milk (powder) snack, almonds snack, and placebo control with 250 ml of water taken 30 min before lunch, respectively. The study consists of two intervention periods over 11 days. The first intervention period under habitual diet conditions from D3 to D6 (4 days), during which all subjects are asked to maintain their habitual eating and daily activities similar to the run-in period. The second intervention consists of prelunch snacks with standard meals. We will examine both the effect of GV and various metabolic and behavioral outcomes potentially associated with the interventions. At the end of this study, we will assess the acceptability and maintainability of the intervention through interviews.

Clinical trial registration

Chinese Clinical Trial Registry, identifier ChiCTR2200058935.

Preferences for Risks and Benefits of Islet Cell Transplantation for Persons With Type 1 Diabetes With History of Episodes of Severe Hypoglycemia: A Discrete-Choice Experiment to Inform Regulatory Decisions

BACKGROUND

The advisory panel for US Food and Drug Administration (FDA) recently endorsed pancreatic islet cell transplantation (ICT) therapy for suboptimally controlled type 1 diabetes (T1D), and FDA approval is under consideration. An important part of regulatory approval includes the patient perspective, through discrete choice. We developed a discrete-choice instrument and used it to determine how 90 people with T1D weigh the risks and benefits of ICT to inform regulatory decisions.

METHODS

Sawtooth software created a random, full-profile, balanced-overlap experimental design for a measure with 8 attributes of ICT risks/benefits, each with 3 to 5 levels. We asked 18 random task pairs, sociodemographics, diabetes management, and hypoglycemia questions. Analysis was performed using random parameters logistic regression technique.

RESULTS

The strongest preference was for avoiding the highest chance (15%) of serious procedure-related complications (β = -2.03, P < 0.001). The strongest positive preference was for gaining 5-y insulin independence (β = 1.75, P < 0.001). The desire for 5-y HbA1C-defined clinical treatment success was also strong (β = 1.39, P < 0.001). Subgroup analysis suggested strong gender differences with women showing much higher preferences for all benefits (68% higher for 5-y insulin independence), and men were generally more risk averse than women. Those with high versus low diabetes distress showed 3 times stronger preference for 5-y insulin independence but also twice preference to avoid risks of serious complications.

CONCLUSION

Despite showing the most preference for avoiding serious ICT complications, people with T1D had a strong preference for achieving ICT benefits, especially insulin independence. We identified important attributes of ICT and demonstrated that patients are willing to make these trade-offs, showing support for the introduction of ICT.

Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems

Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucose-related outcomes of such user-driven innovation. Initial OpenAPS studies include retrospective studies assessing high-level outcomes of average glucose levels and HbA1c, without in-depth analysis of glucose variability (GV). The OpenAPS Data Commons dataset, donated to by open-source AID users with insulin-requiring diabetes, is the largest freely available diabetes-related dataset with over 46,070 days’ worth of data and over 10 million CGM data points, alongside insulin dosing and algorithmic decision data. This paper first reviews the development toward the latest open-source AID and the performance of clinically approved GV metrics. We evaluate the GV outcomes using large-scale data analytics for the n = 122 version of the OpenAPS Data Commons. We describe the data cleaning processes, methods for measuring GV, and the results of data analysis based on individual self-reported demographics. Furthermore, we highlight the lessons learned from the GV outcomes and the analysis of a rich and complex diabetes dataset and additional research questions that emerged from this work to guide future research. This paper affirms previous studies’ findings of the efficacy of open-source AID.

Thrice daily consumption of a novel, premeal shot containing a low dose of whey protein increases time in euglycemia during 7 days of free-living in individuals with type 2 diabetes

INTRODUCTION

During acute feeding trials, consuming a large dose of whey protein (WP) before meals improves postprandial glucose regulation in people with type 2 diabetes. It is unclear if the reported benefits of premeal WP supplementation are translatable to everyday care or are associated with clinically meaningful, real-world glycemic outcomes. This study examined the application of a novel, premeal shot containing a low dose of WP on parameters of free-living glycemic control in people with type 2 diabetes.

RESEARCH DESIGN AND METHODS

In a randomized, placebo-controlled, single-blind crossover design, 18 insulin naive individuals with type 2 diabetes ((mean±SD) age, 50±6 years; HbA_1c (glycated hemoglobin), 7.4%±0.8%; duration of diabetes, 6±5 years) consumed a ready-to-drink WP shot (15 g of protein) or a nutrient-depleted placebo beverage 10 min before breakfast, lunch, and dinner over a 7-day free-living period. Free-living glucose control was measured by blinded continuous glucose monitoring and determined by the percentage of time spent above range (>10 mmol/L), in euglycemic range (3.9-10.0 mmol/L), below range (<3.9 mmol/L) and mean glucose concentrations.

RESULTS

Mealtime WP supplementation reduced the prevalence of daily hyperglycemia by 8%±19% (30%±25% vs 38%±28%, p<0.05), thereby enabling a 9%±19% (~2 hours/day) increase in the time spent in euglycemia (p<0.05). Mean 24-hour blood glucose concentrations were 0.6±1.2 mmol/L lower during WP compared with placebo (p<0.05). Similar improvements in glycemic control were observed during the waken period with premeal WP supplementation (p<0.05), whereas nocturnal glycemic control was unaffected (p>0.05). Supplemental compliance/acceptance was high (>98%), and no adverse events were reported.

CONCLUSIONS

Consuming a novel premeal WP shot containing 15 g of protein before each main meal reduces the prevalence of daily hyperglycemia, thereby enabling a greater amount of time spent in euglycemic range per day over 7 days of free-living in people with type 2 diabetes.

TRIAL REGISTRATION NUMBER

ISRCTN17563146; www.isrctn.com/ISRCTN17563146.

Doege-Potter syndrome due to endothoracic solitary hypoglycemic fibrous tumor

Doege-Potter syndrome leads to severe and sustained symptomatic hypoglycemia and is associated with the solitary fibrous tumor. It is a rare cause, and its diagnosis requires a clinical suspicion and other markers such as insulin-like growth factor II. Here, we describe a case of a patient with intrathoracic tumor and hypoglycemia.

Relation of glucose variability to vulnerable plaque formation in patients with coronary artery disease

BACKGROUND

Although glucose variability (GV) is reportedly associated with coronary plaque vulnerability, namely lipid-rich plaque, details are not fully understood. The aim of this study was to evaluate relations of GV after discharge to vulnerable plaque formation assessed by near-infrared spectroscopy intravascular ultrasound (NIRS-IVUS) in patients with and without diabetes.

METHODS

A total of 40 patients undergoing percutaneous coronary intervention under NIRS-IVUS guidance were included, among whom 13 (33%) had diabetes and 20 (50%) presented with acute myocardial infarction (MI). GV was evaluated by a flush glucose monitoring system, primarily with mean amplitude of glycemic excursion (MAGE). Lipid-rich plaque was assessed by maximum lipid core burden index in 4 mm (maxLCBI_4mm) in the target lesion using NIRS-IVUS.

RESULTS

Mean MAGE and maxLCBI_4mm were 69.7 ± 25.6 mg/dl and 508.0 ± 294.9. Intra-day GV was not significantly associated with maxLCBI_4mm in the entire study population, while MAGE was correlated with maxLCBI_4mm in non-diabetic patients (r = 0.46, p = 0.02). In patients with and without acute MI presentation, no significant relations were found between MAGE and maxLCBI_4mm.

CONCLUSION

GV was associated with lipid core plaque formation, especially in non-diabetic patients.

Correlation between the Variability of Glycosylated Hemoglobin and Cardiovascular Risk in New-Onset T2DM Patients

Objective

To investigate the relationship between glycosylated hemoglobin variant index and cardiovascular disease in patients with type 2 diabetes.

Methods

A total of 120 patients with type 2 diabetes who were admitted to the Department of Endocrinology in Chun'an Branch of Zhejiang Provincial People's Hospital from January 2014 to January 2017 were enrolled. The clinical data, fasting blood glucose, and glycosylated hemoglobin levels of the patients were collected, and HGI was obtained by calculating the FPG level into the formula. Follow-up for three years was performed to observe the cardiovascular disease (including coronary heart disease and ischemic stroke) in patients. The occurrence of CVD was analyzed in patients with different levels of HGI. Multivariate logistics regression analysis was used to analyze the risk factors of CVD in patients with T2DM.

Results

After three years of follow-up, 8 cases of 120 patients were lost to follow-up. In the end, 24 cases of CVD occurred in 112 patients, with an incidence rate of 21.43%. Comparing the clinical data of CVD patients and non-CVD patients, it was found that the proportion of age, FPG, HbA1c, HGI, and insulin control in the CVD group was higher than that of the non-CVD group, and the difference was statistically significant (P < 0.05). After grouping according to different HGI levels, it was found that with the increase of HGI level, the proportion of HbA1c, FPG, TC, CVD, and insulin use showed an upward trend (P < 0.05). Multivariate logistic regression analysis showed that high HGI level (OR = 4.660), older age (OR = 4.815), and higher FPG level (OR = 1.717) are independent risk factors that affect T2DM patients with cardiovascular disease (P < 0.05).

Conclusion

High HGI is independently associated with CVD events in patients with type 2 diabetes. HGI testing is helpful for clinical assessment of personalized assessment and prediction of cardiovascular risk in patients with diabetes.

Conversations and Reactions Around Severe Hypoglycemia (CRASH): Japan Results From a Global Survey of People with T1DM or Insulin-Treated T2DM and Caregivers

AIMS

The CRASH study examined severe hypoglycemia (SH) experiences among people with diabetes (PWD) and caregivers across eight countries. Here we report findings from the Japan cohort, with references to data from the United Kingdom (UK) cohort.

MATERIALS AND METHODS

Adults with type 1 (T1DM) or insulin-treated type 2 diabetes mellitus (T2DM) and caregivers (not necessarily related) were recruited from online patient panels. Participants who had experienced at least one SH event in the past 3 years were eligible for study inclusion. Participants completed an online survey regarding their experience with SH, its treatment, and actions during and after an event.

RESULTS

Of the 9367 PWD and caregivers from the online patient panels, 8475 participants were ineligible and a total of 53 Japanese participants (35 T1DM, 9 T2DM, 9 caregivers) completed the survey. Most SH incidents occurred at home and were unattended by a healthcare provider. For T1DM, 29% of Japan PWD and 13% of the UK PWD called an ambulance during an SH event; of these, 90% (Japan) and 50% (UK) were transported to hospital. Glucagon use was low (3% Japan and 10% UK for T1DM). Japanese respondents reported emotional impacts of SH, including feeling scared (86% T1DM, 56% T2DM), unprepared (63% T1DM, 78% T2DM), and helpless (60% T1DM, 33% T2DM). Despite the emotional burden, most PWD did not immediately discuss their SH event with a healthcare provider, with the majority (75% T1DM, 71% T2DM) waiting until their next doctor's appointment.

CONCLUSION

Conversations around SH between healthcare providers and PWD appear to be insufficient in Japan. An emotional burden of SH was reported by PWD and caregivers. Education regarding the prevention of SH and available treatment options may reduce SH events and improve treatment preparation, while alleviating PWD concerns.

Nonlinear Dynamics of Reaction Time and Time Estimation during Repetitive Test

(1) Background: In this research, we aimed to investigate a computational model of repetitive reaction time (RT) and virtual reaction time (VRT) testing. (2) Methods: The study involved 180 subjects (50 men, 130 women, mean age 31.61 ± 13.56 years). The data were statistically analyzed through the coefficient of variation (CV) and the Poincaré plot indicators. (3) Results: We obtained an excellent level of reliability for both sessions of testing and we put into evidence a relationship of association of the RT and VRT with the subjects' age, which was more pregnant for RT (p < 0.05). For both RT and VRT data series, we determined a consistent closer association between CV and the Poincaré plot descriptors SD1, SD2 (SD-standard deviation), and the area of the fitting ellipse (AFE) (p < 0.01). We reported an underestimation of the time interval of 2 s during the VRT session of testing, with an average value of CV of VRT, the equivalent of the Weber fraction, of 15.21 ± 8.82%. (4) Conclusions: The present study provides novel evidence that linear and nonlinear analysis of RT and VRT variability during serial testing bring complementary insights to the understanding of complex neurocognitive processes implied in the task execution.

Insulin dose reduction in dapagliflozin combination therapy for type 1 diabetes mellitus: the RISING-STAR study

To clarify the frequency of hypoglycemia in patients with type 1 diabetes mellitus receiving dapagliflozin combination therapy to reduce their basal insulin dose. Sixty subjects were assigned to two groups according to their basal insulin-to-total daily dose (TDD) ratio: group A (basal insulin/TDD <40%) and group B (≥40%). Reduction of the basal insulin dose was instituted in group B, but not in group A. The number of hypoglycemic events per day and ketosis frequency were the primary and secondary endpoints, respectively. The hypoglycemia frequency before and after the intervention was 0.23 and 0.26 times/day in group A and 0.19 and 0.23 times/day in group B, respectively, with no significant difference between the groups. The total insulin dose reduction was approximately 10% in both groups. Ketosis frequency increased significantly after the intervention (from 0.013 to 0.086 times/day in group A and 0.013 to 0.059 times/day in group B). Time-in-range, mean amplitude of glycemic excursion, and glycated hemoglobin A1c improved in both groups. No significant difference in hypoglycemia frequency was observed between patients with and without reduction of the basal insulin dose. The combination therapy improved glycemic control and patient satisfaction regarding hyperglycemia. Nevertheless, adequate attention to ketosis is crucial.

Glucose variability in subjects with normal glucose tolerance: Relations with body composition, insulin secretion and sensitivity

BACKGROUND AND AIMS

To estimate the determinants of glucose variability (GV) in young and middle-aged non-obese subjects with normal glucose tolerance (NGT) we assessed relations between GV parameters, body composition, insulin secretion and sensitivity indices.

METHODS

Thirty individuals with normal body mass index (BMI) and twenty overweight subjects were included. 24-hour mean glucose, time in range, time above range (TAR), time below range (TBR), standard deviation (SD), coefficient of variation (CV), mean amplitude of glucose excursions (MAGE), continuous overlapping net glycemic action (CONGA), J-index, lability index (LI), mean absolute glucose (MAG), M-value, high blood glucose index (HBGI), low blood glucose index (LBGI) were derived from continuous glucose monitoring. Body composition was assessed by DEXA. Insulin secretion and sensitivity was estimated by HOMA-IR and HOMA-B scores.

RESULTS

Overweight subjects demonstrated higher mean glucose, CONGA, J-index and lower TBR, M-value and LBGI values. Mean glucose correlated positively with total, trunk, gynoid and android fat mass, while M-value and LBGI demonstrated negative correlations with these parameters. In multiple stepwise regression analysis, android fat mass was a predictor of mean glucose, CONGA, J-index, SD and MAGE, gynoid fat mass predicted J-index only, and total fat mass was associated inversely with MAG. Fasting insulin was a predictor of TAR, SD, CV, MAGE, MAG, LI and HBGI. HOMA-B was associated with CONGA, M-value and LBGI.

CONCLUSION

In non-obese subjects with NGT mean glucose and GV parameters are related to fat mass and fat distribution. These relations can be mediated through insulin secretion and sensitivity.

Multicenter, Open-Label, 2-Arm, Pilot Trial for Safe Reduction of Basal Insulin Dose Combined with SGLT2 Inhibitor in Type 1 Diabetes Mellitus: Study Protocol for a RISING-STAR Trial

Background:

The safe method of instructing insulin dose reduction in combination with SGLT2 inhibitors, dapagliflozin for patients with type 1 diabetes mellitus has not been clarified. In this study, we conducted a stratified, 2-arm, parallel comparative study with the primary endpoint of decreasing the frequency of hypoglycemia by instructing basal insulin dose reduction.

Methods:

The study has a multicenter, open-label, 2-arm design; 60 type 1 diabetes mellitus patients are being recruited from 7 hospitals. Study subjects have been stratified into 2 groups based on the ratio of basal insulin daily dose (Basal) to total daily insulin dose (TDD). The subjects whose Basal/TDD ratio is <0.4 are instructed not to reduce Basal but to reduce bolus insulin dose by 10% (group A), and subjects with a Basal/TDD ratio >0.4 will be instructed to reduce Basal by 10% (group B). The primary outcome is the daily frequency of hypoglycemia during the intervention period (SGLT2 inhibitor administration), as determined by self-monitoring of blood glucose. We aimed to confirm a greater reduction in frequency of hypoglycemia in group B (reduced Basal), than in group A (non-reduction of Basal and reduced insulin effect levels by 10%). Baseline hypoglycemia was set at 7 ± 6 times/month. The minimum sample size required to achieve a significance of .05 for a 1-sided t-test with a statistical power at 80% is determined. When the sample size is 26 patients in 1 group, the percentage increase in hypoglycemia exceeds 60%, and the sample size is considered sufficient.

Discussion:

In this pilot study, we assumed that, given a sufficient Basal, hypoglycemia would be more frequent in patients with type 1 diabetes when combined with SGLT2 inhibitors, provided the Basal was not reduced.

Impact of glycemic variability on coronary and peripheral endothelial dysfunction in patients with coronary artery disease

BACKGROUND

Previous studies have reported that glucose variability leads to endothelial dysfunction and progression of coronary atherosclerosis. However, few studies have directly evaluated the relation between glucose variability and coronary endothelial function in patients with coronary artery disease (CAD).

METHODS

A total of 38 patients with chronic CAD and a history of coronary drug-eluting stent implantation were enroled. Coronary endothelial function was evaluated by measuring the coronary vasoreactivity using quantitative coronary angiography in the segment distal to implanted stent in response to intracoronary acetylcholine (ACh) infusion (10-7 mol/l). Peripheral endothelial function was also assessed with reactive hyperemia index (RHI). The mean amplitude of glycemic excursion (MAGE) was calculated as a primary metric of glucose variability using a flash glucose monitoring system.

RESULTS

Of 38 patients, 17 (45%) had diabetes mellitus. The mean levels of glycated hemoglobin, MAGE, and RHI were 6.3 ± 0.8%, 71.4 ± 29.8 mg/dl, and 1.85 ± 0.63. In the distal segment to coronary stent, lumen diameter was constricted by 0.6 ± 7.3% in response to intracoronary ACh infusion compared to that at baseline. While peripheral endothelial function assessed with RHI was not significantly associated with MAGE (r = -0.16, p = 0.35), coronary endothelial function was correlated with MAGE (r = -0.38, p = 0.02).

CONCLUSION

Greater glucose variability was significantly associated with coronary rather than peripheral endothelial dysfunction in patients with CAD, suggesting an impact of glucose variability on coronary atherosclerosis.

Time in range correlates glycated albumin measured immediately after 2 weeks of continuous glucose monitoring

AIMS

Time in range (TIR), an index of glycemic control and also blood glucose fluctuation, obtained from continuous glucose monitoring (CGM), has been increasing its importance along with the spread of CGM in recent years. For a while, glycated albumin (GA) has been also used as a glycemic control index during about 2-weeks in routine clinical practice. It has not yet been confirmed under optimal condition whether TIR and GA correlates. Clarification of the correlation between TIR and GA, which was measured immediately after 2-weeks of CGM, might be a finding that further supports the utility of TIR.

METHODS

GA was measured at the conclusion of 2-week CGM in 71 diabetes outpatients at our hospital, and the correlation between GA and indices such as TIR obtained from CGM was statistically analyzed.

RESULTS

It was found that TIR and time above range (TAR) were significantly correlated with GA. Upon performing multiple regression analysis, TIR, TAR and BMI. indicated a significant regression coefficient with respect to GA.

CONCLUSIONS

These findings further support the utility of TIR as a marker of glycemic control that it might also be correlated with GA, and also suggest a relation between GA and blood glucose fluctuation.