Measures Of Glycemic Variability Research Articles

Safety and tolerability of a low glycemic load dietary intervention in adults with cystic fibrosis: a pilot study.

To achieve and maintain adequate weight, people with cystic fibrosis (CF) May often consume energy-dense, nutrient-poor foods high in added sugars and refined carbohydrates; however, little is known about the glycemic and metabolic effects of dietary composition in this patient population. The objective of this pilot study was to investigate the safety and tolerability of a low glycemic load (LGL) diet in adults with CF and abnormal glucose tolerance (AGT). Ten adults with CF and AGT completed this prospective, open-label pilot study. Mean age was 27.0 ± 2.1 years, 64% were female, and all had pancreatic insufficiency. Each participant followed his/her typical diet for 2 weeks, then transitioned to a LGL diet via meal delivery service for 8 weeks. The primary outcome was change in weight from baseline to study completion, with safety established if no significant decline was noted. Other key safety outcomes included change in hypoglycemia measured by patient report and continuous glucose monitoring (CGM). Exploratory outcomes included changes in other CGM measures, body composition by dual energy X-ray absorptiometry (DXA), and patient reported outcomes. There were no significant changes in weight or in subjectively-reported or objectively-measured hypoglycemia. Favorable non-significant changes were noted in CGM measures of hyperglycemia and glycemic variability, DXA measures of fat mass, and gastrointestinal symptom surveys. A LGL dietary intervention was safe and well tolerated in adults with CF and AGT. These results lay the groundwork for future trials investigating the impact of low-glycemic dietary interventions on metabolic outcomes in the CF population.

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

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

Impact of Diet Composition and Quality on Continuous Glucose Monitor-Derived Measures of Glycemic Variability in Free-Living Adults

Impact of Diet Composition and Quality on Continuous Glucose Monitor-Derived Measures of Glycemic Variability in Free-Living Adults

A low-glucose eating pattern is associated with improvements in glycemic variability among women at risk for postmenopausal breast cancer: an exploratory analysis.

High glycemic variability (GV) is a biomarker of cancer risk, even in the absence of diabetes. The emerging concept of chrononutrition suggests that modifying meal timing can favorably impact metabolic risk factors linked to diet-related chronic disease, including breast cancer. Here, we examined the potential of eating when glucose levels are near personalized fasting thresholds (low-glucose eating, LGE), a novel form of timed-eating, to reduce GV in women without diabetes, who are at risk for postmenopausal breast cancer. In this exploratory analysis of our 16-week weight loss randomized controlled trial, we included 17 non-Hispanic, white, postmenopausal women (average age = 60.7 ± 5.8 years, BMI = 34.5 ± 6.1 kg/m2, HbA1c = 5.7 ± 0.3%). Participants were those who, as part of the parent study, provided 3-7 days of blinded, continuous glucose monitoring data and image-assisted, timestamped food records at weeks 0 and 16. Pearson's correlation and multivariate regression were used to assess associations between LGE and GV, controlling for concurrent weight changes. Increases in LGE were associated with multiple unfavorable measures of GV including reductions in CGM glucose mean, CONGA, LI, J-Index, HBGI, ADDR, and time spent in a severe GV pattern (r = -0.81 to -0.49; ps < 0.044) and with increases in favorable measures of GV including M-value and LBGI (r = 0.59, 0.62; ps < 0.013). These associations remained significant after adjusting for weight changes. Low-glucose eating is associated with improvements in glycemic variability, independent of concurrent weight reductions, suggesting it may be beneficial for GV-related disease prevention. Further research in a larger, more diverse sample with poor metabolic health is warranted.Clinical trial registration: ClinicalTrials.gov, NCT03546972.

Effect of glycemic variability on infectious outcomes in critically Ill burn patients

After acute burn injury, patients experience a hypermetabolic state often complicated by a stress-induced hyperglycemia. Recent research points towards glycemic variability as a contributing factor in adverse outcomes in critically ill patients. In burn patients, greater glycemic variability has been associated with increased rates of mortality and sepsis. However, no studies to date have examined the impact of glycemic variability on rates of infection in this population or determined which measure may be most useful. Infection, and subsequent sepsis, remains the leading contributor to morbidity and mortality after burn injury. The primary objective of this study is to evaluate the relationship between different measures of glycemic variability and infectious complications in burn patients. This retrospective study included patients admitted to a single American Burn Association-verified burn center between January 1, 2020 and December 31, 2020 with burn or inhalation injury. The primary outcome was a composite of autograft loss, mortality, and proven infection. Secondary outcomes included hospital length of stay and a further analysis of the proven infection component of the composite primary outcome. In addition to mean glucose, several different measures of glycemic variability were used for comparison, including standard deviation, coefficient of variation, mean amplitude of glycemic excursions, and J-index. Outcomes were analyzed using multiple logistic regression analysis while controlling for revised Baux score. A quantile analysis was performed to do determine the optimal mean threshold. Three hundred and ninety-two patients were admitted and screened for inclusion during the study period. Most patients were excluded due to a LOS less than 72 h. 112 patients were included in the study. Of the 112 patients, 22.3% experienced an infectious complication (25 patients with 28 complications). Mean glucose (OR 1.024; 95% CI 1.004–1.045) and J-index (OR 1.044; 95% CI 1.003–1.087) were associated with occurrence of infectious complications. Regarding target mean glucose threshold, a daily mean glucose above 150 mg/dL showed the strongest association with infectious complications (OR 3.634; 95% CI 1.008–13.101). Mean glucose, standard of deviation, and J-index were all independently associated with proven infection.

Improved glycaemic control induced by evening activity breaks does not persist overnight amongst healthy adults: A randomized crossover trial.

To compare the effects of 4 hours of laboratory-based regular activity breaks (RABs) and prolonged sitting (SIT) on subsequent 48-h free-living interstitial glucose levels in a group of healthy adults. In this randomized crossover trial, participants completed two 4-h laboratory-based interventions commencing at ~5:00 pm: (1) SIT and (2) SIT interrupted with 3 min of body weight resistance exercise activity breaks every 30 min (RABs). Continuous glucose monitoring was performed during the intervention and for 48-h after, during which time participants returned to a free-living setting. Twenty-eight adults (female n = 20, mean ± SD age 25.5 ± 5.6 years, body mass index 29.2 ± 6.9 kg/m2) provided data for this analysis. During the intervention period, RABs lowered mean interstitial glucose by 8.3% (-0.47 mmol/L/4 h, 95% confidence interval [CI] -0.74 to -0.20; p = 0.001) and area under the curve (AUC) by 8.9% (-2.01 mmol/L/4 h, 95% CI -3.05 to -0.97; p < 0.001) compared to SIT. Measures of glycaemic variability were not significantly different during the intervention. There were no significant differences in mean glucose and AUC between conditions during the first nocturnal period and 24-h post intervention. When compared to SIT, RABs increased continuous overall net action of glucose at 1 h and SD glucose by 22% (0.18 mmol/L, 95% CI 0.03 to 0.29; p = 0.018) and 26% (95% CI 4.9 to 42.7; p = 0.019) in the first nocturnal period and by 10% (0.09 mmol/L, 95% CI 0.01, 0.17; p = 0.025) and 15% (95% CI 6.6 to 22.4; p = 0.001) in the 24-h post intervention period, respectively. Performing activity breaks in the evening results in acute reductions in interstitial glucose concentrations; however, the magnitude of these changes is not maintained overnight or into the following 48 hours.

IDF23-0136 Association of physical activity and sleep quality with measures of glycemic variability in adults with type 2 diabetes

IDF23-0136 Association of physical activity and sleep quality with measures of glycemic variability in adults with type 2 diabetes

Glycemic variability assessed using continuous glucose monitoring in individuals without diabetes and associations with cardiometabolic risk markers: A systematic review and meta-analysis

Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for ≥24h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome. Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes.

Glycemic Variability As a Prognostic Factor for Mortality in Patients With Critical Illness: A Systematic Review and Meta-Analysis.

To perform a systematic review and meta-analysis to evaluate the association of various measures of glycemic variability, including time-domain and complexity-domain, with short-term mortality in patients with critical illness. We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to November 3, 2023. We included English language studies that assessed metrics of glycemic variation or complexity and short-term mortality in patients admitted to the ICU. Two authors performed independent data abstraction and risk-of-bias assessments. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios and mean difference. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty of pooled estimates. We included 41 studies (n = 162,259). We demonstrate that increased sd, coefficient of variance, glycemic lability index, and decreased time in range are probably associated with increased mortality in critically ill patients (moderate certainty) and that increased mean absolute glucose, mean amplitude of glycemic excursion, and detrended fluctuation analysis may be associated with increased mortality (low certainty). We found a consistent association between increased measures of glycemic variability and higher short-term mortality in patient with critical illness. Further research should focus on standardized measurements of glycemic variation and complexity, along with their utility as therapeutic targets and prognostic markers.

Glycemic variability after mechanical thrombectomy for anterior circulation acute ischemic stroke.

Morbidity remains high among patients who undergo successful mechanical thrombectomy (MT) for anterior circulation large vessel occlusion (LVO). Stress hyperglycemia worsens the prognosis after acute ischemic stroke (AIS), but aggressively treating hyperglycemia does not improve the outcome. There is no consensus on how to best manage glycemia after AIS. Glycemic variability (GV) reflects glycemic fluctuations over time and could be the culprit. We aimed to elucidate how GV impacts outcome of AIS patients treated with MT. This was a single-center retrospective study. We consecutively included AIS patients who received MT for anterior circulation LVO. We recorded discrete blood glucose measurements within the first 24 hours post thrombectomy, from which we calculated two measures of GV: standard deviation (SD) and coefficient of variation. Univariate and multivariate analyses were conducted to identify predictors of poor functional outcome (modified Ranking scale score 3-6) and mortality at 3-month follow-up. We included 657 patients. Patients with poor functional outcome (42.5%) and patients that died (14.8%) had significantly higher GV as measured by SD. In a multivariable model adjusted for confounders, higher SD was associated with mortality -adjusted odds ratio: 1.020 (95% CI 1.001-1.040)- but not with functional outcome -adjusted odds ratio for modified Ranking scale score 3-6: 1.007 (95% CI 0.990-1.025)-. Our results suggest that higher GV after MT for anterior circulation AIS is an independent risk factor for 3-month mortality. Future trials should evaluate the benefit of reducing GV in this setting.

Study of Glycemic Variability in Well-controlled Type 2 Diabetic Patients Using Continuous Glucose Monitoring System.

The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS). To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c. A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over a period of 7 days by using FreeStyle® Libre Pro™, which is a flash glucose monitoring system. The CGM sensor was attached to the left upper arm of the patient on day 0 and removed on day 7. The data recorded in the sensor was then retrieved using pre-installed computer software and analyzed using standard CGM metrics like standard deviation (SD), percentage coefficient of variation (%CV), time above range (TAR), time below range (TBR), and time in range (TIR), out of which %CV was used to quantify GV. %CV has been used to cluster patients into four cohorts from best to worst, namely: best/low CV ≤ 10%, intermediate CV from 10 to 20%, high CV from 20 to 30%, and very high CV of >30%. Scatterplots are used to establish correlations between various parameters. Data from a total of 30 patients were analyzed using CGMS and thus used for calculating standard CGM metrics; glucose readings every 15 minutes were recorded consecutively for 7-day periods, making it a total of 672 readings for each patient. Interpreting the CGM data of all 30 patients, the following results were found: the mean blood glucose of all cases is 134.925 ± 22.323 mg/dL, the mean SD of blood glucose of all cases is 35.348 ± 9.388 mg/dL, the mean of %CV of all cases is 26.376 ± 6.193%. CGM parameters of time are used in the form of percentages, and the following results were found: the mean of TAR, TBR, and TIR is 14.425 ± 13.211, 5.771 ± 6.808, and 82.594 ± 12.888%, respectively. Clustering the patients into cohorts, the proportion of patients exhibiting best/low %CV (10%) is 0, intermediate %CV (10-20%) is 16.67% (five out of 30 patients), high %CV (20-30%) is 50% (15 out of 30 patients) and very high %CV (>30%) is 33.33% (10 out of 30 patients). Also, there is no significant correlation found between HbA1c and %CV (ρ = 0.076, p-value = 0.690); a significant negative correlation was found between %CV and TIR (ρ = -0.604, p < 0.001S); a positive correlation of %CV with TAR and TBR is significant (ρ = 0.816, p-value of <0.001). Using a flash CGMS device and considering %CV as the parameter and primary measure of GV, the study demonstrated the overall instability of a person's glycemic control, making note of unrecognized events of hypoglycemia and hyperglycemia in asymptomatic well-controlled T2DM patients, revealing the overall volatile glycemic control. The most important finding of this study is that even those diabetics who are considered well-controlled experience a great degree of GV as assessed by CGM-derived metrics. This study also demonstrated that there is no significant correlation between HbA1c and GV, suggesting that patients may not have optimal control of their diabetes despite having "normal HbA1c" values; hence, GV can be considered an HbA1c-independent danger factor, having more harmful effects than sustained hyperglycemia in the growth of diabetic complications. So, by using CGM-derived metrics, the measurement of GV has the potential to complement HbA1c data. In this manner, a more comprehensive assessment of glycemic excursions can be provided for better treatment decisions, thereby facilitating optimal glycemic control, which is essential for reducing overall complications and promoting good quality of life.

The effect of bodyweight exercise on 24-h glycemic responses determined by continuous glucose monitoring in healthy inactive adults: a randomized crossover study

Vigorous intermittent exercise can improve indices of glycemia in the 24 h postexercise period in apparently healthy individuals. We examined the effect of a single session of bodyweight exercise (BWE) on glycemic responses using continuous glucose monitoring (CGM) under controlled dietary conditions. Healthy inactive adults (n = 27; 8 males, 19 females; age: 23 ± 3 years) completed 2 virtually supervised trials spaced ~ 1 week apart in a randomized, crossover manner. The trials involved an 11-min BWE protocol that consisted of 5 × 1-min bouts performed at a self-selected pace interspersed with 1-min active recovery periods or a non-exercise sitting control period (CON). Mean heart rate during the BWE protocol was 147 ± 14 beats per min (75% of age-predicted maximum). Mean 24 h glucose after BWE and CON was not different (5.0 ± 0.4 vs 5.0 ± 0.5 mM respectively; p = 0.39). There were also no differences between conditions for measures of glycemic variability or the postprandial glucose responses after ingestion of a 75 g glucose drink or lunch, dinner, and breakfast meals. This study demonstrates the feasibility of conducting a remotely supervised BWE intervention using CGM under free-living conditions. Future studies should investigate the effect of repeated sessions of BWE training or responses in people with impaired glycemic control.

Effects of Low-Calorie Sweetener Restriction on Glycemic Variability and Cardiometabolic Health in Children with Type 1 Diabetes: Findings of a Pilot and Feasibility Study.

Low-calorie sweeteners (LCS) are commonly consumed by children with type 1 diabetes (T1D), yet their role in cardiometabolic health is unclear. This study examined the feasibility, acceptability, and preliminary effects of 12 weeks of LCS restriction among children with T1D. Children (n = 31) with T1D completed a two-week run-in (n = 28) and were randomly assigned to avoid LCS (LCS restriction, n = 15) or continue their usual LCS intake (n = 13). Feasibility was assessed using recruitment, retention, and adherence rates percentages. Acceptability was assessed through parents completing a qualitative interview (subset, n = 15) and a satisfaction survey at follow-up. Preliminary outcomes were between-group differences in change in average daily time-in-range (TIR) over 12 weeks (primary), and other measures of glycemic variability, lipids, inflammatory biomarkers, visceral adiposity, and dietary intake (secondary). Linear regression, unadjusted and adjusted for age, sex, race, and change in BMI, was used to compare mean changes in all outcomes between groups. LCS restriction was feasible and acceptable. No between-group differences in change in TIR or other measures of glycemic variability were observed. However, significant decreases in TNF-alpha (-0.23 ± 0.08 pg/mL) and improvements in cholesterol (-0.31 ± 0.18 mmol/L) and LDL (-0.60 ± 0.39 mmol/L) were observed with usual LCS intake, compared with LCS restriction. Those randomized to LCS restriction did not report increases in total or added sugar intake, and lower energy intake was reported in both groups (-190.8 ± 106.40 kcal LCS restriction, -245.3 ± 112.90 kcal usual LCS intake group). Decreases in percent energy from carbohydrates (-8.5 ± 2.61) and increases in percent energy from protein (3.2 ± 1.16) and fat (5.2 ± 2.02) were reported with usual LCS intake compared with LCS restriction. Twelve weeks of LCS restriction did not compromise glycemic variability or cardiometabolic outcomes in this small sample of youth with T1D. Further examination of LCS restriction among children with T1D is warranted.

Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial

IntroductionDo-it-yourself artificial pancreas system (DIY APS) is built using commercially available insulin pump, continuous glucose monitoring (CGM) and an open-source algorithm. Compared with commercial products, DIY systems are affordable, allow...

62 Effect of Glycemic Variability on Infectious Outcomes in Patients with Severe Burn Injuries

Abstract Introduction Stress-induced hyperglycemia is a common manifestation of severe burn injury, due to increased catecholamines, glucagon, corticosteroids, and cytokines. The primary objective of this study was to evaluate the relationship between different measures of glycemic variability and infectious outcomes in burn patients. Methods This retrospective electronic chart review included patients admitted to a single American Burn Association-verified burn center for the year of 2020. Infectious complication was defined as occurrence of proven infection, autograft loss, or death. Glycemic variability indices tested include standard deviation, mean amplitude of glycemic excursions, J-index, and coefficient of variability. Demographics were compared utilizing Fisher’s exact or Mann-Whitney U test, depending on dichotomy. Logistic regression analysis was utilized to control for revised Baux score. Likelihood ratio test statistic was utilized to compare strength of association. Results Three-hundred and ninety-two patients were admitted during 2020 and screened for inclusion. After applying exclusion criteria, 112 patients remained in the study group. More than half were excluded for length of stay less than 3 days. Twenty-five (22%) had at least one infectious complication (21 infections, 3 with graft loss, and 4 deaths). Revised Baux, age, percent total body surface area burned, history of diabetes, and admission blood glucose were all higher in the group with an infectious complication. Out of the indices tested, only mean glucose (Odds ratio, 95% confidence interval: 1.024, 1.004-1.045) and J-index (1.044, 1.002-1.087) were significantly associated with higher risk of an infectious complication. Quantile analysis of mean glucose thresholds indicated &amp;gt; 150 mg/dL to have the strongest association with infectious complications in burn patients. Conclusions Although J-index was significantly associated with infectious complications, mean glucose was also and has a simpler derivation. Applicability of Research to Practice A liberal glucose control strategy should continue to be avoided in patients with burn injuries due to higher risk of infectious complication.

Longitudinal MRI Shows Progressive Decline in Pancreas Size and Altered Pancreas Shape in Type 1 Diabetes.

Individuals with type 1 diabetes (T1D) have a smaller pancreas, but longitudinal changes in pancreas size and shape are unclear. We monitored changes in pancreas size and shape after diagnosis with T1D. We conducted a prospective cohort study at an academic medical center between 2014 and 2022. Individuals with T1D (n = 91) or controls (n = 90) underwent magnetic resonance imaging (MRI) of the pancreas, including longitudinal MRI in 53 individuals with new-onset T1D. Interventions included MRI and continuous glucose monitoring (CGM). Pancreas size and shape were measured from MRI. For participants who used CGM, measures of glycemic variability were calculated. On longitudinal imaging, pancreas volume and pancreas volume index normalized for body weight declined during the first year after diagnosis. Pancreas volume index continued to decline through the fifth year after diagnosis. A cross-sectional study of individuals with diabetes duration up to 60 years demonstrated that pancreas size in adults negatively correlated with age and disease duration, whereas pancreas volume and pancreas volume index remained stable in controls. Pancreas volume index correlated inversely with low blood glucose index, a measure of risk for hypoglycemia. Pancreas shape was altered in individuals with T1D and further diverged from controls over the first 5 years after diagnosis. Pancreas size and shape are altered in nondiabetic individuals at genetic risk for T1D. Combined pancreas size and shape analysis better distinguished the pancreas of individuals with T1D from controls than size alone. Pancreas size declines most rapidly near the clinical diagnosis of T1D and continues to decline throughout adulthood. Declines in pancreas size are accompanied by changes in pancreas shape.

The impact of physical inactivity on glucose homeostasis when diet is adjusted to maintain energy balance in healthy, young males

It is unclear if dietary adjustments to maintain energy balance during reduced physical activity can offset inactivity-induced reductions in insulin sensitivity and glucose disposal to produce normal daily glucose concentrations and meal responses. Therefore, the aim of the present study was to examine the impact of long-term physical inactivity (60 days of bed rest) on daily glycemia when in energy balance. Interstitial glucose concentrations were measured using Continuous Glucose Monitoring Systems (CGMS) for 5 days before and towards the end of bed rest in 20 healthy, young males (Age: 34±8 years; BMI: 23.5±1.8kg/m2). Energy intake was reduced during bed rest to match energy expenditure, but the types of foods and timing of meals was maintained. Fasting venous glucose and insulin concentrations were determined, as well as the change in whole-body glucose disposal using a hyperinsulinemic-euglycemic clamp (HIEC). Following long-term bed rest, fasting plasma insulin concentration increased 40% (p=0.004) and glucose disposal during the HIEC decreased 24% (p<0.001). Interstitial daily glucose total area under the curve (tAUC) from pre-to post-bed rest increased on average by 6% (p=0.041), despite a 20 and 25% reduction in total caloric and carbohydrate intake, respectively. The nocturnal period (00:00-06:00) showed the greatest change to glycemia with glucose tAUC for this period increasing by 9% (p=0.005). CGMS measures of daily glycemic variability (SD, J-Index, M-value and MAG) were not changed during bed rest. Reduced physical activity (bed rest) increases glycemia even when daily energy intake is reduced to maintain energy balance. However, the disturbance to daily glucose homeostasis was much more modest than the reduced capacity to dispose of glucose, and glycemic variability was not negatively affected by bed rest, likely due to positive mitigating effects from the contemporaneous reduction in dietary energy and carbohydrate intake. NCT03594799 (registered July 20, 2018) (https://clinicaltrials.gov/ct2/show/NCT03594799).

ISPAD Clinical Practice Consensus Guidelines 2022: Glycemic targets and glucose monitoring for children, adolescents, and young people with diabetes.

ISPAD Clinical Practice Consensus Guidelines 2022: Glycemic targets and glucose monitoring for children, adolescents, and young people with diabetes.

Effects of structured Ramadan Nutrition Plan on glycemic control and variability using continuous glucose monitoring in individuals with type 2 diabetes: A pilot study

Background and aimsContinuous glucose monitoring (CGM) has been increasingly used in recent years to evaluate glycemic control and variability in individuals with diabetes observing Ramadan fasting. However, the effectiveness of the Ramadan Nutrition Plan (RNP) in individuals with type 2 diabetes (T2D) using CGM-derived measures has not been investigated. The study aimed to evaluate the effects of structured RNP versus standard care using CGM in individuals with T2D. MethodsThis parallel non-randomized interventional study with patients’ preference design involved 21 individuals with T2D (mean age: 49 ± 10 years, BMI: 30.0 ± 6.2 kg/m2). Participants chose to receive either structured RNP (sRNT; structured Ramadan Nutrition Therapy group; n = 14) or standard care (SC; n = 7). Participants wore CGM 5 days before Ramadan and during Ramadan. CGM-derived measures of glycemic variability were calculated using Glyculator version 2.0. ResultsCompared to the SC group, the sRNT group significantly reduced their fasting blood glucose levels, HbA1c, total cholesterol, diastolic blood pressure, and increased dietary fiber intake. CGM data showed the sRNT group had significantly lower average sensor glucose, peak sensor value, estimated A1c, percentage and duration of time-above-range, J-index, mean amplitude of glycemic excursion (MAGE), and continuous overall net glycemic action (CONGA); and a significantly higher percentage of time-in-range (TIR). ConclusionsThe structured RNP significantly improved clinical outcomes, glycemic control and variability in individuals with T2D. The study highlights the importance of utilizing CGM sensor data to monitor glycemic excursions during Ramadan fasting. Adequately powered randomized controlled trials are needed to confirm the findings.

Circulating osteocalcin is associated with time in range and other metrics assessed by continuous glucose monitoring in type 2 diabetes

BackgroundOsteocalcin, a protein secreted mainly by mature osteoblasts, has been shown to be involved in glucose metabolism through various pathways. However, few studies has explored the association between osteocalcin and Time in range (TIR). Continuous glucose monitoring (CGM) -derived metrics, such as TIR and other indexes have been gradually and widely used in clinical practice to assess glucose fluctuations. The main purpose of this study was to investigate the correlation between osteocalcin and indexes from CGM in patients with type 2 diabetes mellitus (T2DM).MethodThe total number of 376 patients with T2D were enrolled, all of them performed three consecutive days of monitoring. They were divided into four groups on account of the quartile of osteocalcin. Time in range, Time below range (TBR), Time above range(TAR) and measures of glycemic variability (GV) were assessed for analysing. After a 100 g standard steamed bread meal, blood glucose (Glu0h Glu0.5 h, Glu1h, Glu2h, GLu3h), C-peptide (Cp0h, Cp0.5 h, Cp1h, Cp2h, Cp3h), serum insulin (INS0h, INS0.5 h, INS1h, INS2h, INS3h) concentrations at different time points were obtained. HOMA-IS, HOMA-βwas calculated to evaluate insulin sensitivity and insulin secreting of the participants.ResultsPatients with higher osteocalcin level had higher TIR (P < 0.05). Spearman correlation analysis showed that osteocalcin was positively correlated with TBR (although the P value for TBR was greater than 0.05) (r = 0.227, P < 0.001 r = 0.068, P = 0.189) and negatively correlated with TAR (− 0.229, P < 0.001). Similarly, there was a negative correlation between osteocalcin and glycemic variability (GV) indicators, including SD, MBG, MODD, ADDR, and MAGE (P value of MAGE > 0.05). Multiple stepwise regression showed that osteocalcin was an independent contributor to TIR, TAR and HOMA-IS.ConclusionCirculating osteocalcin is positively correlated with TIR and negatively correlated with MODD, ADDR, and MAGE. Osteocalcin may have a beneficial impact on glucose homeostasis in T2DM patients.