Ageing well with diabetes: the role of technology.

Over the past two decades there has been a substantial rise in the adoption of diabetes therapeutic technology among children, adolescents and younger adults with type 1 diabetes, and its use is now also advocated for older individuals. Older people with diabetes are more prone to experience hypoglycaemia because of numerous predisposing factors and are at higher risk of hypoglycaemic events requiring third-party assistance as well as other adverse sequelae. Hypoglycaemia may also have long-term consequences, including cognitive impairment, frailty and disability. Diabetes in older people is often characterised by marked glucose variability related to age-associated changes such as variable appetite and levels of physical activity, comorbidities and polypharmacotherapy. Preventing hypoglycaemia and mitigating glucose excursions may have considerable positive impacts on physical and cognitive function and general well-being and may even prevent or improve frailty. Technology for older people includes continuous glucose monitoring systems, insulin pumps, automated insulin delivery systems and smart insulin pens. Clinical trials and real-world studies have shown that older people with diabetes benefit from technology in terms of glucose management, reductions in hypoglycaemic events, emergency department attendance and hospital admissions, and improvement in quality of life. However, ageing may bring physical impairments and other challenges that hinder the use of technology. Healthcare professionals should identify older adults with diabetes who may benefit from therapeutic technology and then adopt an individualised approach to education and follow-up for individuals and their caregivers. Future research should explore the impact of diabetes technology on outcomes relevant to older people with diabetes.

High blood glucose variability may predict poor outcomes in patients with spontaneous cerebellar hemorrhage undergoing surgical operation: a retrospective study.

BACKGROUND: Elevated blood glucose (BG) variability has been reported as an independent risk factor for poor prognosis in a variety of diseases. This study aimed to investigate the association between BG variability and clinical outcomes in patients with spontaneous cerebellar hemorrhage (SCH) undergoing surgical operation. METHODS: This retrospective cohort study of the consecutive patients admitted to the department of Neurosurgery, the Affiliated Hospital of Qingdao University between January 2014 and June 2022 with the diagnosis of SCH underwent surgical intervention. BG analysis was continuously and routinely performed. BG variability was represented by the standard deviation (SD) of the serial measurements within the first 7 days. The general characteristics, imageological information, blood glucose level, and surgical information were reviewed and compared through medical records. RESULTS: A total of 115 patients (65 male and 50 female) were enrolled. Out of all 115 patients, the overall clinical outcomes according to the modified Rankin Scale (mRS) were poor (mRS 3-6) in 31 patients (26.96%) and good (mRS 0-2) in 84 patients (73.04%). Twelve of the 115 patients died during hospitalization, and the mortality rate was 10.43%. Multivariate logistic regression analysis showed that SD of BG (odds ratio (OR), 4.717; 95% confidence interval (CI), 1.054-21.115; P = 0.043), GCS (OR, 0.563; 95% CI, 0.330-0.958; P = 0.034), and hematoma volume (OR, 1.395; 95% CI, 1.118-1.748; P = 0.003) were significant predictors. The area under the ROC curve of SD of BG was 0.911 (95% CI, 0.850-0.973; P < 0.001) with a sensitivity and specificity of 90.3% and 83.3%, respectively, and the cut-off value was 1.736. CONCLUSIONS: High BG Variability is independently correlated with the 6-month poor outcomes in patients with SCH undergoing surgical operation.

High sugar consumption for seven days in adult mice increased blood glucose variability, induced an anxiolytic effect and triggered oxidative stress in cerebral cortex.

Brain function is highly altered by glucose toxicity related to diabetes. High consumption of sugar in normal conditions is suspected to affect as well brain integrity. The present study investigates the possible effects of short-term exposure to high sugar diet on brain redox homeostasis in healthy mice. Male adult healthy mice were divided into two groups: control (CG) and sugar-exposed group (SG), that was exposed continually to 10% of glucose in drinking water for 7 days and 20% sucrose pellets food. Behavior, blood glucose variability and cerebral cortex oxidative stress biomarkers were measured at the end of exposure. Animals exposed to the high sugar diet expressed a significant increase in blood glucose levels and high glucose variability compared to control. These animals expressed as well anxiolytic behavior as revealed by the plus maze test. Exposure to the sugar diet altered redox homeostasis in the brain cortex as revealed by an increase in lipid peroxidation and the activity of antioxidant enzymes superoxide dismutase (SOD) and glutathione-s-transferase (GST). On the other hand, catalase (CAT) activity was decreased, and reduced glutathione (GSH) level was not altered compared to control. Further studies are required to understand the mechanisms trigging oxidative stress (OS) in the brain in response to short term exposure to high sugar diet and glucose fluctuations.

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.

Correlation between blood glucose level and poor wound healing after posterior lumbar interbody fusion in patients with type 2 diabetes.

To investigate the correlation of blood glucose level with poor wound healing (PWH) after posterior lumbar interbody fusion (PLIF) in patients with type 2 diabetes (T2D). From January 2016 to January 2023, a case-control study was conducted to analyse the clinical data of 400 patients with T2D who were treated by PLIF and internal fixation at our hospital. The following data were recorded: gender; age; body mass index (BMI); surgical stage; average perioperative blood glucose level; perioperative blood glucose variance; perioperative blood glucose coefficient of variation; glycated haemoglobin level; preoperative levels of total protein, albumin and haemoglobin; postoperative levels of total protein, albumin and haemoglobin; surgical time; intraoperative bleeding volume; operator; postoperative drainage volume; and postoperative drainage tube removal time of each group. The indicators for monitoring blood glucose variability (GV) included the SD of blood glucose level (SDBG), coefficient of variation (CV) and maximum amplitude of variation (LAGE) before and after surgery. According to the diagnostic criteria for PWH, patients with postoperative PWH were determined and assigned to two groups: Group A (good wound healing group; n = 330 patients) and Group B (poor wound healing group; n = 70 patients). The preoperative and postoperative blood GV indicators, namely SDBG, CV and LAGE, were compared between these two groups. We also determined the relationship between perioperative blood GV parameters and PWH after PLIF surgery and its predictive value through correlation analysis and receiver-operating characteristic curve. Of the 400 enrolled patients, 70 patients had PWH. Univariate analysis revealed significant differences between the two groups in the course of diabetes, mean fasting blood glucose (MFBG), SDBG, CV, LAGE, preoperative hypoglycaemic program, surgical segment, postoperative drainage time, incision length and other factors (p < 0.05). However, no significant differences were noted in factors such as gender, age, body mass index, hypertension, coronary heart disease, admission fasting blood glucose, preoperative haemoglobin A1c, surgical time, intraoperative bleeding volume, intraoperative blood transfusion volume and postoperative drainage volume (p > 0.05). The area under the curve (AUC) values of preoperative SDBG, CV and LAGE were 0.6657, 0.6432 and 0.6584, respectively. The cut-off values were 1.13 mmol/L, 6.97% and 0.75 mmol/L, respectively. The AUC values for postoperative SDBG, CV and LAGE were 0.5885, 0.6255 and 0.6261, respectively. The cut-off values were 1.94 mmol/L, 24.32% and 2.75 mmol/L, respectively. The multivariate ridge regression analysis showed that preoperative MFBG, SDBG, CV and LAGE; postoperative SDBG, CV and LAGE; postoperative long drainage time; and multiple surgical segments were independent risk factors for T2D patients to develop surgical site infection after PLIF (p < 0.05). The perioperative blood GV in patients with T2D is closely related to the occurrence of PWH after PLIF. Reducing blood GV may help to reduce the occurrence of PWH after PLIF.

Nutritional Prescription in ICU Patients: Does it Matter?

Background: The nutritional status of the patients before critical illness and nutrition support given during the critical illness play an important role in the recovery. We aimed to evaluate the nutritional prescription and its effect on ICU mortality. Materials and methods: This was a prospective observational study conducted after institutional ethical committee approval (IEC 94/2018, CTRI/2018/06/014625) in a case-mixed (medical and surgical) ICU. Patients admitted to the ICU were enrolled within 24 hours of admission. The amount of calories and proteins prescribed and received by the patients was collected for 7 days. The primary outcome was ICU mortality. Results: A total of 100 patients were included. The mean age was 48.63 (16.25) years, and 62% were males. The acute physiology and chronic health evaluation (APACHE II), sequential organ failure assessment (SOFA), and modified Nutric (mNUTRIC) scores were comparable between the two groups. The ICU mortality was 30%. The calorie and protein deficits were comparable between survivors and non-survivors. Among the secondary outcomes, a significant time effect (p = 0.013) and interaction effect (p = 0.004) were noted for maximum glucose levels. The glucose variability calculated by coefficient of variation (CV) was significantly higher in non-survivors than survivors (p = 0.031). Conclusion: The calorie and protein deficits did not affect ICU mortality. The maximum glucose variability and CV were significant parameters associated with ICU mortality. How to cite this article: Havaldar AA, Selvam S. Nutritional Prescription in ICU Patients: Does it Matter? Indian J Crit Care Med 2024;28(7):657-661.

Continuous glucose monitoring-derived time in range and CV are associated with altered tissue characteristics of the carotid artery wall in people with type 2 diabetes.

AIMS/HYPOTHESIS: Previous studies have suggested that glucose variability may accelerate atherosclerosis progression in people with type 2 diabetes. Current guidelines recommend assessing glycaemic control using continuous glucose monitoring (CGM), which provides a comprehensive glycaemic profile to supplement HbA1c measurement. However, the association between CGM-derived metrics and atherosclerosis progression is not entirely clear. METHODS: This exploratory study used baseline data and data obtained after 104 weeks from an ongoing prospective, multicentre, observational study. Six hundred study participants with type 2 diabetes and no apparent history of symptomatic cardiovascular disease underwent CGM and ultrasonographic atherosclerosis measurements of the carotid arteries, including the intima-media thickness (IMT) and grey-scale median (GSM), at baseline and 104 weeks. Non-invasive ultrasonic tissue characterisation of the carotid artery wall or plaque using the GSM reflects vascular composition. Multivariate regression models were used to analyse the association between CGM-derived indices, mainly time in range (TIR) and CV, and changes in carotid atherosclerosis index values. RESULTS: Over the 104-week study period, there were modest increases in mean IMT (from 0.759±0.153 to 0.773±0.152 mm, p<0.001) and thickened-lesion GSM (from 43.5±19.5 to 53.9±23.5 units, p<0.001), but no significant changes in common carotid artery maximum-IMT (from 1.109±0.442 to 1.116±0.469 mm, p=0.453) or mean GSM (from 48.7±19.3 to 49.8±20.8 units, p=0.092). In a linear regression model with adjustment for possible atherosclerotic risk factors, including HbA1c, TIR and CV at baseline were significantly associated with the annual change in mean GSM (regression coefficient per 10% increase in TIR 0.52; 95% CI 0.06, 0.98; Hochberg-adjusted p value 0.038; regression coefficient per 1% increase in CV -0.12; 95% CI -0.22, -0.02; Hochberg-adjusted p value 0.038). TIR and CV at baseline were also significantly associated with the annual change in thickened-lesion GSM (regression coefficient per 10% increase in TIR 0.95; 95% CI 0.12, 1.79; Hochberg-adjusted p value 0.038; regression coefficient per 1% increase in CV -0.19; 95% CI -0.36, -0.01; Hochberg-adjusted p value 0.038). Participants who achieved target CGM-derived metrics at baseline, as proposed by an international consensus, showed significant annual changes in mean GSM compared with those who did not (0.94±6.88 vs -0.21±6.19 units/year, p=0.007). CONCLUSIONS/INTERPRETATION: TIR and CV were significantly associated with changes in the tissue characteristics of the carotid artery wall. TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry, number UMIN000032325.

Importance of beta cell mass for glycaemic control in people with type 1 diabetes.

AIMS/HYPOTHESIS: The role of beta cell mass in the balance of glucose control and hypoglycaemic burden in people with type 1 diabetes is unclear. We applied positron emission tomography (PET) imaging with radiolabelled exendin to compare beta cell mass among people with type 1 diabetes and either low glucose variability (LGV) or high glucose variability (HGV). METHODS: All participants with either LGV (n=9) or HGV (n=7) underwent a mixed-meal tolerance test to determine beta cell function and wore a blinded continuous glucose monitor for a week. After an i.v. injection with [68Ga]Ga-NODAGA-exendin-4, PET images were acquired for the quantification of pancreatic uptake of radiolabelled exendin. The mean standardised uptake value (SUVmean) of the pancreas was used to determine the amount of beta cell mass. RESULTS: Participants with LGV had lower HbA1c (46.0 mmol/mol [44.5-52.5] [6.4% (6.3-7)] vs 80 mmol/mol [69.0-110] [9.5% (8.5-12.2)], p=0.001) and higher time in range (TIR) (75.6% [73.5-90.3] vs 38.7% [25.1-48.5], p=0.002) than those with HGV. The SUVmean of the pancreas was higher for the LGV than for the HGV group (5.1 [3.6-5.6] vs 2.9 [2.1-3.4], p=0.008). The AUCC-peptide:AUCglucose ratio was numerically, but not statistically, higher in the LGV compared with the HGV group (2.7×10-2 [6.2×10-4-5.3×10-2] vs 9.3×10-4 [4.7×10-4-5.2×10-3], p=0.21). SUVmean correlated with the AUCC-peptide:AUCglucose ratio (Pearson r=0.64, p=0.01), as well as with the TIR (r=0.64, p=0.01) and the SD of interstitial glucose levels (r=-0.66, p=0.007). CONCLUSION/INTERPRETATION: Our data show higher beta cell mass in people with type 1 diabetes and LGV than in those with HGV, independent of beta cell function.

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 ß = -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 ß = -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.

Inverse association between glucose variability and body fat in type 2 diabetes with impaired endogenous insulin secretion assessed using continuous glucose monitoring: A prospective observational study.

AIM: To evaluate the contribution of body fat mass and serum adiponectin concentration to glucose variability (GV) stability in people with type 2 diabetes with impaired versus preserved endogenous insulin secretion. MATERIALS AND METHODS: This multicentre prospective observational study included 193 people with type 2 diabetes who underwent ambulatory continuous glucose monitoring, abdominal computed tomography and fasting blood sampling. A fasting C-peptide (FCP) concentration >2 ng/mL was defined as preserved endogenous insulin secretion. The participants were divided into high (FCP > 2 ng/mL) and low FCP subgroups (FCP ≤ 2 ng/mL). Multivariate regression analysis was performed in each subgroup. RESULTS: In the high FCP subgroup, the coefficient of variation (CV) in GV was unrelated to abdominal fat area. In the low FCP subgroup, a high CV was significantly related to small abdominal visceral fat area (ß = -0.11, standard error 0.03; P < 0.05) and to small subcutaneous fat area (ß = -0.09, standard error 0.04; P < 0.05). No significant relationship between serum adiponectin concentration and continuous glucose monitoring-related variables was found. CONCLUSIONS: The contribution of body fat mass to GV depends on the endogenous insulin secretion residue. A small body fat area has independent adverse effects on GV in people with type 2 diabetes and impaired endogenous insulin secretion.

Association of fasting blood glucose variability with all-cause mortality in heart transplant recipients.

BACKGROUND: Fasting blood glucose (FBG) variability, an emerging marker of glycemic control, has been shown to be related to the risk of cardiovascular events and all-cause mortality in subjects with or without diabetes. However, whether FBG variability is independently associated with a higher all-cause mortality in heart transplant recipients remains unknown. METHODS: We performed a retrospective cohort study including 373 adult recipients who survived for at least 1 year after heart transplantation with a functioning graft and measured FBG more than three times within first year after transplantation. Multivariable adjusted Cox regression analyses were performed to assess the association between FBG variability and all-cause mortality. RESULTS: Patients were categorized into three groups according to the coefficient of variation of FBG level: ≤7.0%, 7.0%-13.5%, and >13.5%. During a median follow-up of 44.4 months (interquartile range [IQR], 22.6-63.3 months), 31 (8.3%) participants died. In univariate analyses, FBG variability was associated with an increased all-cause mortality (hazard ratio [HR]: 3.00, 95% confidence interval [CI]: 1.67, 5.38; p < .001). This association remained materially unchanged in the multivariable model adjusted for components of demographics, cardiovascular history and lifestyle, hospital information, immunosuppressive therapy, and post-transplant renal function (HR: 2.75, 95% CI: 1.43, 5.28; p = .004). CONCLUSIONS: After heart transplantation, high FBG variability is strongly and independently associated with an increased risk of all-cause mortality. Our findings suggest that FBG variability is a novel risk factor and prognostic marker for heart transplantation recipients in outpatient clinic.

Glucose variability increases during minimally invasive procedures in very preterm infants.

The objective of this study is to assess the effect of neonatal procedures on glucose variability in very preterm infants. Preterm infants (≤ 32 weeks gestation and/or birthweight ≤ 1500 g) were started on continuous glucose monitoring (CGM) on day 2 of birth and monitored for 5 days. Minimally invasive (heel stick, venipunctures) and non-invasive (nappy change, parental presence) procedures were recorded. CGM data were analyzed 30 min before and after each procedure. The primary outcome was the coefficient of glucose variation (CV = SD/mean) before and after the procedure; SD and median glucose were also evaluated. We analyzed 496 procedures in 22 neonates (GA 30.5 weeks [29-31]; birthweight 1300 g [950-1476]). Median glucose did not change before and after each procedure, while CV and SD increased after heel prick (p = 0.017 and 0.030), venipuncture (p = 0.010 and 0.030), and nappy change (p < 0.001 and < 0.001), in the absence of a difference during parental presence. CONCLUSIONS: Non-invasive and minimally invasive procedures increase glucose variability in the absence of changes of mean glucose. WHAT IS KNOWN: • Minimally invasive procedures - including nappy change - may increase neonatal stress in preterm infants. WHAT IS NEW: • Continuous glucose monitoring provides a quantitative measure of neonatal stress during neonatal care procedures demonstrating an increase of glucose variability.

Glycemic control and blood gas sampling frequency during continuous glucose monitoring in the intensive care unit: A before-and-after study.

BACKGROUND: Whether subcutaneous continuous glucose monitoring (CGM) can safely replace intermittent arterial blood gas glucose analyses in intensive care unit (ICU) patients remains uncertain. We aimed to compare CGM to blood gas glucose values and assess whether CGM use reduces blood gas sampling frequency and glucose variability in ICU patients with type 2 diabetes managed with liberal glucose control. METHODS: We used the FreeStyle Libre CGM in 15 ICU patients and compared their blood glucose metrics with a pre-CGM control population of 105 ICU patients with type 2 diabetes. Both groups received insulin to target glucose range of 10-14 mmol/L. We used linear regression analysis adjusted for illness severity to assess the association of CGM use with blood gas sampling frequency and glucose variability. We used mean absolute relative difference (MARD) and Clarke error grid analysis to assess accuracy of matched CGM-blood glucose values overall, across glucose stata (<10, 10-14, >14 mmol/L), and over time (≤48, 48-96, >96 h). RESULTS: We analyzed 483 matched glucose values. Overall MARD was 11.5 (95% CI, 10.7-12.3)% with 99% of readings in Clarke zones A and B. MARD was 15.5% for glucose values <10 mmol/L, 11.1% at 10-14 mmol/L, and 11.4% >14 mmol/L. MARD was 13.8% in the first 48 h, 10.9% at 48-96 h, and 8.9% beyond 96 h. CGM use was associated with 30% reduction in blood gas sampling frequency. CGM use was not associated with glucose variability as determined by glycemic lability index or standard deviation of blood glucose. CONCLUSIONS: In our cohort of ICU patients with type 2 diabetes receiving liberal glycemic control, CGM showed acceptable accuracy and was associated with a reduction in blood gas sampling frequency without compromising glucose control. Lowest accuracy was observed at glucose values below 10 mmol/L and during the first 48 h of CGM use.

Effect of Repeated Bolus and Continuous Glucose Infusion on DNA Damage and Oxidative Stress Biomarkers in Healthy Male Volunteers.

Glucose variability (GV), which describes fluctuations in blood glucose levels within the day, is a phenomenon that is increasingly becoming the target of scientific attention when it comes to increased risk of coronary heart disease. Effects of GV may contribute to the development of metabolic syndrome and type 2 diabetes. Hyperglycemia can lead to oxidative stress resulting in molecular damage due to accumulation of reactive oxygen species (ROS). To discover more about the immediate effects of GV, continuous vs. bolus intravenous glucose administration was applied to 10 healthy men aged 21-30 years over a time frame of 48 h. Whole blood and plasma were analyzed for DNA damage using a comet assay with 3 different treatments (lysis buffer, H2O2, and the lesion-specific enzyme formamidopyrimidine DNA glycosylase (FPG)) as well as for the oxidative stress markers protein carbonyls (PC), unconjugated bilirubin (UCB), and ferric reducing antioxidant power (FRAP). A significant time effect was found in the three DNA damage treatments as well as in PC and UCB possibly due to circadian changes on oxidative stress, but no intervention group effect was observed for any of the markers. In conclusion, bolus vs. continuous glucose administration had no significant acute effect on DNA damage and markers of oxidative stress in healthy men.

Altered muscle mitochondrial, inflammatory and trophic markers, and reduced exercise training adaptations in type 1 diabetes.

Growing evidence of impaired skeletal muscle health in people with type 1 diabetes points toward the presence of a mild myopathy in this population. However, this myopathic condition is not yet well characterised and often overlooked, even though it might affect the whole-body glucose homeostasis and the development of comorbidities. This study aimed to compare skeletal muscle adaptations and changes in glycaemic control after 12 weeks of combined resistance and aerobic (COMB) training between people with type 1 diabetes and healthy controls, and to determine whether the impaired muscle health in type 1 diabetes can affect the exercise-induced adaptations. The COMB training intervention increased aerobic capacity and muscle strength in both healthy and type 1 diabetes sedentary participants, although these improvements were higher in the control group. Better glucose control, reduced glycaemic fluctuations and fewer hypoglycaemic events were recorded at post- compared to pre-intervention in type 1 diabetes. Analysis of muscle biopsies showed an alteration of muscle markers of mitochondrial functions, inflammation, ageing and growth/atrophy compared to the control group. These muscular molecular differences were only partially modified by the COMB training and might explain the reduced exercise adaptation observed in type 1 diabetes. In brief, type 1 diabetes impairs many aspects of skeletal muscle health and might affect the exercise-induced adaptations. Defining the magnitude of diabetic myopathy and the effect of exercise, including longer duration of the intervention, will drive the development of strategies to maximise muscle health in the type 1 diabetes population. KEY POINTS: Type 1 diabetes negatively affects skeletal muscle health; however, the effect of structured exercise training on markers of mitochondrial function, inflammation and regeneration is not known. Even though participants with type 1 diabetes and healthy control were comparable for cardiorespiratory fitness ( V̇O2max${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ ) and muscle strength at baseline, molecular markers related to muscle health were decreased in type 1 diabetes. After training, both groups increased V̇O2max${\dot{V}_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ and muscle strength; however, a larger improvement was achieved by the control group. The training intervention decreased glucose fluctuations and occurrence of hypoglycaemic events in type 1 diabetes, while signs of mild myopathy found in the muscle of participants with type 1 diabetes only partially improved after training Improving muscle health by specific exercise protocols is of considerable clinical interest in therapeutic strategies for improving type 1 diabetes management and preventing or delaying long-term complications.

Insulin secretion and action affect glucose variability in the early stages of glucose intolerance.

AIMS: Since it is unknown whether glucose variability (GV) is increased and whether this is related to worsening of insulin secretion and action in prediabetes, we have assessed insulin secretion and sensitivity, and daily GV in early stages of dysglycemia. MATERIALS AND METHODS: Twenty subjects with normal glucose tolerance (NGT; age 45.0 ± 9.5 years; BMI 31.1 ± 6.4 kg/m2), 25 with NGT and 1hrOGTT>8.6 mmol/L (1hrOGTT; 45.7 ± 8.5 years; 32.4 ± 7.0 kg/m2), and 59 with isolated impaired glucose tolerance (iIGT; 47.7 ± 11.2 years; 31.3 ± 6.1 kg/m2) underwent OGTT and MMTT. CGM was performed with blinded FreeStyle Libre Pro for 24 h under standard conditions. Parameters of beta-cell function, insulin sensitivity and GV were calculated. RESULTS: Overall insulin secretion and action as well as GV progressively worsened across glucose tolerance categories. On a matrix analysis, GV parameters were inversely related to ISSI-2; r = -0.37 to -0.52; p < 0.0001; and IGI; r = -0.28 to -0.48; p < 0.0001 for CV, SD, J-index, LI, HBGI and MAGE. Insulin secretion (IGI) and b-cell function (ISSI-2) emerged as independent contributors to GV in early stage of dysglycemia accounting for about 16%-38% of its variability. CONCLUSIONS: Our results show that daily GV worsens already with mild impairment of glucose tolerance. The increase in GV is inversely related to insulin secretion and action.

Lipohypertrophy Monitoring Study (LIMO): Effect of single use of 4 mm pen needles combined with education on injection site rotation on glycaemic control: Confirmation of an unpleasant truth.

AIMS: To investigate whether single use of 4 mm needles combined with education about injection technique and lipohypertrophy affects HbA1c, hypoglycaemia and glucose variability. METHODS: Insulin-injecting people with diabetes recruited from nine Belgian diabetes centres were prospectively followed for 6 months. They were provided 4 mm pen needles and education concerning injection technique using an online platform (BD and Me™) based on the international Forum for Injection Technique & Therapy Recommendations focused on avoidance of lipohypertrophy zones and reduction of needle reuse. RESULTS: A total of 171 people with diabetes were included of which 146 completed the study. At baseline, lipohypertrophy was present in 63.0% of those who completed the study, with 51.4% injecting in zones of lipohypertrophy, 37.0% incorrectly rotating and 95.9% reusing needles. After the intervention, 7.5% still injected in a lipohypertrophy zone, 4.1% rotated incorrectly and needle reuse decreased to 21.2%. The number of participants with severe hypoglycaemias (from 15.8% to 4.1%, p < 0.001), unexplained hypoglycaemias (from 46.6% to 16.4%, p < 0.001) and high glucose variability (from 64.4% to 29.5%, p < 0.001) was significantly reduced. HbA1c and total daily insulin dose remained stable. CONCLUSION: The combination of 4 mm pen needles and online education on injection techniques significantly reduced the number of people with severe hypoglycaemic episodes, unexplained hypoglycaemia and high glucose variability but did not improve HbA1c control nor lower insulin needs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04659330.

Real world hypoglycaemia related to glucose variability and Flash glucose scan frequency assessed from global FreeStyle Libre data.

AIM: Flash glucose monitoring provides a range of glucose metrics. In the current study, we aim to identify those that indicate that glycaemic targets can be consistently met and contrast the total (t-CV) and within-day coefficient of variation (wd-CV) to guide the assessment of glucose variability and hypoglycaemia exposure. METHODS: De-identified data from Flash readers were collected. The readers were sorted into 10 equally sized groups of scan frequency followed by quartiles of estimated A1c (eA1c). A similar grouping was performed for the total coefficient of variation (t-CV) and within-day coefficient of variation (wd-CV). In addition, analysis of the association of time below 54 mg/dl and glucose variability measured by t-CV and wd-CV was performed. RESULTS: The dataset included 1 002 946 readers. Readers sorted by 10 equal groups of scan rate and quartiles by eA1c, t-CV and wd-CV represented 25 074 readers per group. The association of lower eA1c with higher time in range and reduced time above range was clear. The correlation of eA1c quartiles and time below range was not consistent. An association between glucose variability and hypoglycaemia was found. Both wd-CV and t-CV were associated with time below range. For achieving the consensus target of <1% time below 54 mg/dl, the associated wd-CV and t-CV values were 33.5% and 39.5%, respectively. CONCLUSIONS: The type of CV reported by the different continuous glucose monitoring systems should be acknowledged. CV <36% might not be adequate to ensure low hypoglycaemia exposure. To our knowledge, the majority of continuous glucose monitoring reports the t-CV. Appropriate thresholds should be used to identify patients that would probably meet time below range targets (t-CV <40% or wd-CV <34%).

Glucose variability: A physiological correlate of eating disorder behaviors among individuals with binge-spectrum eating disorders.

OBJECTIVES: Elevated glucose variability may be one mechanism that increases risk for significant psychological and physiological health conditions among individuals with binge-spectrum eating disorders (B-EDs), given the impact of eating disorder (ED) behaviors on blood glucose levels. This study aimed to characterize glucose variability among individuals with B-EDs compared with age-matched, sex-matched, and body mass index-matched controls, and investigate the association between frequency of ED behaviors and glucose variability. METHODS: Participants were 52 individuals with B-EDs and 22 controls who wore continuous glucose monitors to measure blood glucose levels and completed ecological momentary assessment surveys to measure ED behaviors for 1 week. Independent samples t-tests compared individuals with B-EDs and controls and multiple linear regression models examined the association between ED behaviors and glucose variability. RESULTS: Individuals with B-EDs demonstrated numerically higher glucose variability than controls (t = 1.42, p = .08, d = 0.43), although this difference was not statistically significant. When controlling for covariates, frequency of ED behaviors was significantly, positively associated with glucose variability (t = 3.17, p = .003) with medium effect size (f2  = 0.25). Post hoc analyses indicated that binge eating frequency was significantly associated with glucose variability, while episodes of 5+ hours without eating were not. DISCUSSION: Glucose variability among individuals with B-EDs appears to be positively associated with engagement in ED behaviors, particularly binge eating. Glucose variability may be an important mechanism by which adverse health outcomes occur at elevated rates in B-EDs and warrants future study. PUBLIC SIGNIFICANCE: This study suggests that some individuals with binge ED and bulimia nervosa may experience elevated glucose variability, a physiological symptom that is linked to a number of adverse health consequences. The degree of elevation in glucose variability is positive associated with frequency of eating disorder behaviors, especially binge eating.

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 (maxLCBI4mm) in the target lesion using NIRS-IVUS. RESULTS: Mean MAGE and maxLCBI4mm were 69.7 ± 25.6 mg/dl and 508.0 ± 294.9. Intra-day GV was not significantly associated with maxLCBI4mm in the entire study population, while MAGE was correlated with maxLCBI4mm 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 maxLCBI4mm. CONCLUSION: GV was associated with lipid core plaque formation, especially in non-diabetic patients.