Glucose fluctuations in subjects with normal glucose tolerance, impaired glucose regulation and newly diagnosed type 2 diabetes mellitus

Association between gastrectomy and the risk of type 2 diabetes in gastric cancer survivors: A nationwide cohort study

AIM

Postprandial glycemic fluctuations after gastrectomy are seen in patients with gastric cancer but, no studies have investigated the association between gastrectomy and type 2 diabetes mellitus (T2DM) in gastric cancer survivors. This study aimed to elucidate the relationship between gastrectomy (total or subtotal) and incident T2DM. In addition, we explored whether vitamin B12 supplementation modulates this risk among patients who have undergone total gastrectomy.

METHODS

In this large nationwide population-based retrospective cohort study using the National Health Insurance Service database of South Korea, we identified patients aged >20 years who underwent gastrectomy from 2008 to 2015 (n = 150,074) and age- and sex-matched controls without gastrectomy (n = 301,508). A Cox proportional hazards model was used.

RESULTS

During the median follow-up duration of 4.4 years after the 2-year time lag after gastrectomy, of the 78,006 subjects, 4,597 (5.9 %) developed T2DM. Compared with matched controls, the adjusted hazard ratio (AHR[95 % confidence interval]) for T2DM of patients with total gastrectomy was 1.34[1.23;1.47]. The corresponding AHR after subtotal gastrectomy was 0.81[0.76;0.86]. Among the patients with total gastrectomy, the risk of T2DM was significantly increased in those who did not receive any vitamin B12 supplementation (AHR=1.60[1.33;1.92]), whereas the risk of T2DM was lower (close to being statistically significant) in those who received continuous vitamin B12 supplementation after gastrectomy (AHR=0.70[0.49;1.01]).

CONCLUSION

These results show a significantly reduced risk of T2DM in gastric cancer patients undergoing subtotal gastrectomy and a significantly increased risk of T2DM in gastric cancer patients undergoing total gastrectomy, which is mitigated by continuous vitamin B12 supplementation.

Risk factors for prediabetes in community-dwelling adults: A generalized estimating equation logistic regression approach with natural language processing insights

The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes during their lifetimes. We aimed to classify community-dwelling adults with a high risk for prediabetes based on prediabetes-related symptoms and to identify their characteristics, which might be factors associated with prediabetes. We analyzed homecare nursing records (n = 26,840) of 1628 patients aged over 20 years. Using a natural language processing algorithm, we classified each nursing episode as either low-risk or high-risk for prediabetes based on the detected number and category of prediabetes-symptom words. To identify differences between the risk groups, we employed t-tests, chi-square tests, and data visualization. Risk factors for prediabetes were identified using multiple logistic regression models with generalized estimating equations. A total of 3270 episodes (12.18%) were classified as potentially high-risk for prediabetes. There were significant differences in the personal, social, and clinical factors between groups. Results revealed that female sex, age, cancer coverage as part of homecare insurance coverage, and family caregivers were significantly associated with an increased risk of prediabetes. Although prediabetes is not a life-threatening disease, uncontrolled blood glucose can cause unfavorable outcomes for other major diseases. Thus, medical professionals should consider the associated symptoms and risk factors of prediabetes. Moreover, the proposed algorithm may support the detection of individuals at a high risk for prediabetes. Implementing this approach could facilitate proactive monitoring and early intervention, leading to reduced healthcare expenses and better health outcomes for community-dwelling adults.

Continuous Glucose Monitoring for Prediabetes: What Are the Best Metrics?

BACKGROUND

Continuous glucose monitoring (CGM) has transformed the care of type 1 and type 2 diabetes, and there is potential for CGM to also become influential in prediabetes identification and management. However, to date, we do not have any consensus guidelines or high-quality evidence to guide CGM goals and metrics for use in prediabetes.

METHODS

We searched PubMed for all English-language articles on CGM use in nonpregnant adults with prediabetes published by November 1, 2023. We excluded any articles that included subjects with type 1 diabetes or who were known to be at risk for type 1 diabetes due to positive islet autoantibodies.

RESULTS

Based on the limited data available, we suggest possible CGM metrics to be used for individuals with prediabetes. We also explore the role that glycemic variability (GV) plays in the transition from normoglycemia to prediabetes.

CONCLUSIONS

Glycemic variability indices beyond the standard deviation and coefficient of variation are emerging as prominent identifiers of early dysglycemia. One GV index in particular, the mean amplitude of glycemic excursion (MAGE), may play a key future role in CGM metrics for prediabetes and is highlighted in this review.

Association of blood glucose change with postoperative delirium after coronary artery bypass grafting in patients with diabetes mellitus: a study of the MIMIC-IV database

Aim

Study results on blood glucose and the risk of delirium in patients receiving cardiac surgery are inconsistent, and there is also a gap in how to manage blood glucose after coronary artery bypass grafting (CABG). This study focused on patients with diabetes mellitus (DM) undergoing CABG and explored the associations of different blood glucose-related indexes and blood glucose change trajectory with postoperative delirium (POD), with the aim of providing some information for the management of blood glucose in this population.

Methods

Data of patients with DM undergoing CABG were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database in this retrospective cohort study. The blood glucose-related indexes included baseline blood glucose, mean blood glucose (MBG), mean absolute glucose (MAG), mean amplitude of glycemic excursions (MAGE), glycemic lability index (GLI), and largest amplitude of glycemic excursions (LAGE). The MBG trajectory was classified using the latent growth mixture modeling (LGMM) method. Univariate and multivariate logistic regression analyses were utilized to screen covariates and explore the associations of blood glucose-related indexes and MBG trajectory with POD. These relationships were also assessed in subgroups of age, gender, race, estimated glomerular filtration rate (eGFR), international normalized ratio (INR), sepsis, mechanical ventilation use, and vasopressor use. In addition, the potential interaction effect between blood glucose and hepatorenal function on POD was investigated. The evaluation indexes were odds ratios (ORs), relative excess risk due to interaction (RERI), attributable proportion of interaction (AP), and 95% confidence intervals (CIs).

Results

Among the eligible 1,951 patients, 180 had POD. After adjusting for covariates, higher levels of MBG (OR = 3.703, 95% CI: 1.743-7.870), MAG >0.77 mmol/L/h (OR = 1.754, 95% CI: 1.235-2.490), and GLI >2.6 (mmol/L)2/h/per se (OR = 1.458, 95% CI: 1.033-2.058) were associated with higher odds of POD. The positive associations of MBG, MAG, and GLI with POD were observed in patients aged <65 years old, male patients, White patients, those with eGFR <60 and INR <1.5, patients with sepsis, and those who received mechanical ventilation and vasopressors (all p < 0.05). Patients with class 3 (OR = 3.465, 95% CI: 1.122-10.696) and class 4 (OR = 3.864, 95% CI: 2.083-7.170) MBG trajectory seemed to have higher odds of POD, compared to those with a class 1 MBG trajectory. Moreover, MAG (RERI = 0.71, 95% CI: 0.14-1.27, AP = 0.71, 95% CI: 0.12-1.19) and GLI (RERI = 0.78, 95% CI: 0.19-1.39, AP = 0.69, 95% CI: 0.16-1.12) both had a potential synergistic effect with INR on POD.

Conclusion

Focusing on levels of MBG, MAG, GLI, and MBG trajectory may be more beneficial to assess the potential risk of POD than the blood glucose level upon ICU admission in patients with DM undergoing CABG.

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

BACKGROUND & AIMS

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.

METHODS

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 ≥24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome.

RESULTS

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.

CONCLUSION

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.

Factors that determine glucose variability, defined by the coefficient of variation in continuous glucose monitoring values, in a Chinese population with type 2 diabetes

AIMS

To elucidate the clinical determinants of the coefficient of variation (CV) of glucose by analysing the pancreatic β-cell function of subjects with type 2 diabetes mellitus (T2DM).

METHODS

A total of 716 Chinese subjects with T2DM were included. Continuous glucose monitoring (CGM) was used to assess blood glucose, and the CV was calculated. C-peptide concentration at 0, 0.5, 1, 2 and 3 hours (Cp0h, Cp0.5h, Cp1h, Cp2h and Cp3h, respectively) was measured after a standard 100-g steamed bun meal test to assess pancreatic β-cell function. The determinants of glucose variability defined by the CV of CGM values were explored from two perspectives: the CV of qualitative variables and the CV of quantitative variables.

RESULTS

Our data revealed that C-peptide concentration (Cp0h, Cp0.5h, Cp1h, Cp2h, Cp3h), area under the curve for C-peptide concentration at 0.5 and 3 hours (AUC-Cp0.5h and AUC-Cp3h) decreased with increasing CV quartile (P < 0.05). The CV was negatively correlated with homeostatic model assessment of β-cell function index, C-peptide concentration at all timepoints, and AUC-Cp0.5h and AUC-Cp3h (P < 0.001). Quantile regression analysis showed that AUC-Cp0.5h had an overall negative effect on the CV in the 0.05 to 0.95 quartiles, and AUC-Cp3h tended to have a negative effect on the CV in the 0.2 to 0.65 quartiles. After adjusting for confounders, multinomial logistic regression showed that each 1-unit increase in AUC-Cp0.5h was associated with a 31.7% reduction in the risk of unstable glucose homeostasis (CV > 36%; P = 0.036; odds ratio 0.683; 95% confidence interval 0.478-0.976). We also identified the AUC-Cp0.5h (0.735 ng/mL) and AUC-Cp3h (13.355 ng/mL) cut-off values for predicting unstable glucose homeostasis (CV >36%) in T2DM subjects.

CONCLUSION

Our study suggests that impaired pancreatic β-cell function may be a clinical determining factor of CV of glucose in people with T2DM.

Diabetes and Parkinson's Disease: Understanding Shared Molecular Mechanisms

Aging is a major risk factor for Parkinson's disease (PD). Genetic mutations account for a small percentage of cases and the majority appears to be sporadic, with yet unclear causes. However, various environmental factors have been linked to an increased risk of developing PD and, therefore, understanding the complex interplay between genetic and environmental factors is crucial for developing effective disease-modifying therapies. Several studies identified a connection between type 2 diabetes (T2DM) and PD. T2DM is characterized by insulin resistance and failure of β-cells to compensate, leading to hyperglycemia and serious comorbidities. Both PD and T2DM share misregulated processes, including mitochondrial dysfunction, oxidative stress, chronic inflammation, altered proteostasis, protein aggregation, and misregulation of glucose metabolism. Chronic or recurring hyperglycemia is a T2DM hallmark and can lead to increased methylglyoxal (MGO) production, which is responsible for protein glycation. Glycation of alpha-synuclein (aSyn), a central player in PD pathogenesis, accelerates the deleterious aSyn effects. Interestingly, MGO blood plasma levels and aSyn glycation are significantly elevated in T2DM patients, suggesting a molecular mechanism underlying the T2DM - PD link. Compared to high constant glucose levels, glycemic variability (fluctuations in blood glucose levels), can be more detrimental for diabetic patients, causing oxidative stress, inflammation, and endothelial damage. Accordingly, it is imperative for future research to prioritize the exploration of glucose variability's influence on PD development and progression. This involves moving beyond the binary classification of patients as diabetic or non-diabetic, aiming to pave the way for the development of enhanced therapeutic interventions.

Glucose variability: a new risk factor for cardiovascular disease

AIMS AND DATA SYNTHESIS

Glucose variability (GV) is increasingly considered an additional index of glycemic control. Growing evidence indicates that GV is associated with diabetic vascular complications, thus being a relevant point to address in diabetes management. GV can be measured using various parameters, but to date, a gold standard has not been identified. This underscores the need for further studies in this field also to identify the optimal treatment.

CONCLUSIONS

We reviewed the definition of GV, the pathogenetic mechanisms of atherosclerosis, and its relationship with diabetic complications.

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.

Oscillating Glucose Induces the Increase in Inflammatory Stress through Ninjurin-1 Up-Regulation and Stimulation of Transport Proteins in Human Endothelial Cells

Clinical data implicate fluctuations of high levels of plasma glucose in cardiovascular diseases. Endothelial cells (EC) are the first cells of the vessel wall exposed to them. Our aim was to evaluate the effects of oscillating glucose (OG) on EC function and to decipher new molecular mechanisms involved. Cultured human ECs (EA.hy926 line and primary cells) were exposed to OG (5/25 mM alternatively at 3 h), constant HG (25 mM) or physiological concentration (5 mM, NG) for 72 h. Markers of inflammation (Ninj-1, MCP-1, RAGE, TNFR1, NF-kB, and p38 MAPK), oxidative stress (ROS, VPO1, and HO-1), and transendothelial transport proteins (SR-BI, caveolin-1, and VAMP-3) were assessed. Inhibitors of ROS (NAC), NF-kB (Bay 11-7085), and Ninj-1 silencing were used to identify the mechanisms of OG-induced EC dysfunction. The results revealed that OG determined an increased expression of Ninj-1, MCP-1, RAGE, TNFR1, SR-B1, and VAMP-3 andstimulated monocyte adhesion. All of these effects were induced bymechanisms involving ROS production or NF-kB activation. NINJ-1 silencing inhibited the upregulation of caveolin-1 and VAMP-3 induced by OG in EC. In conclusion, OG induces increased inflammatory stress, ROS production, and NF-kB activation and stimulates transendothelial transport. To this end, we propose a novel mechanism linking Ninj-1 up-regulation to increased expression of transendothelial transport proteins.

Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlated with deteriorating glucose regulation

Most information used to evaluate diabetic statuses is collected at a special time-point, such as taking fasting plasma glucose test and providing a limited view of individual's health and disease risk. As a new parameter for continuously evaluating personal clinical statuses, the newly developed technique "continuous glucose monitoring" (CGM) can characterize glucose dynamics. By calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropy analysis of the CGM data, the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes (P for trend < 0.01). Furthermore, CGI was significantly associated with various parameters such as insulin sensitivity/secretion (all P < 0.01), and multiple linear stepwise regression showed that the disposition index, which reflects β-cell function after adjusting for insulin sensitivity, was the only independent factor correlated with CGI (P < 0.01). Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.

Association between visit-to-visit fasting glycemic variability and depression: a retrospective cohort study in a representative Korean population without diabetes

Glycemic variability (GV) is a risk factor for depression in patients with diabetes. However, whether it is also a predictor of incident depression in people without diabetes remains unclear. We aimed to investigate the association between visit-to-visit variability in fasting serum glucose (FSG) levels and the incidence of depression among Koreans without diabetes. This retrospective cohort study included data of people without diabetes who did not have depression at baseline and had at least three FSG measurements (n = 264,480) extracted from the 2002-2007 Korean National Health Insurance Service-National Health Screening Cohort. GV was calculated as the average successive variability of FSG. Among 264,480 participants, 198,267 were observed during 2008-2013 and their hazard ratios (HR) of incident depression were calculated. Participants with the highest GV showed a higher risk of depression in fully adjusted models than those with the lowest GV (HR, 1.09; 95% CI, 1.02-1.16). The risk of incident depression heightened with increasing GV (p for trend < 0.001). Greater visit-to-visit GV may be associated with the risk of developing depression in people without diabetes. Conversely, maintaining steady FSG levels may reduce the risk of incident depression in people without diabetes.

Association of Time in Range with Endothelial Injury in Patients with Type 2 Diabetes Treated with Exenatide

INTRODUCTION

We aimed to investigate whether treatment with exenatide could increase time in range (TIR) and decrease glycemic variability, and to evaluate the association between TIR and endothelial injury in patients with type 2 diabetes mellitus (T2DM).

METHODS

Two-hundred patients with T2DM treated with exenatide for 16 weeks were included in this study. Seven-point fingerstick blood glucose was used to evaluate derived TIR and glycemic variability. The serum levels of soluble endothelial cell protein C receptor (sEPCR) and von Willebrand factor (vWF) were measured. Ninety-three patients having the data of endothelial injury markers were categorized as derived TIR > 70% or ≤ 70% after the treatment and the association between TIR and endothelial injury were evaluated.

RESULTS

Treatment with exenatide for 16 weeks resulted in a significant reduction in fasting blood glucose, postprandial 2 h blood glucose, and glycated hemoglobin A1c (HbA1c) levels in patients with T2DM. Compared with baseline, derived TIR value was significantly increased [85.7 (57.1, 100.0) % vs. 42.9 (14.9, 71.4) %, P < 0.001], and the parameters of glycemic variability were remarkably decreased after the treatment. After the treatment, serum sEPCR level was significantly decreased from baseline in patients with TIR > 70% [74.5 (32.8, 122.5) ng/mL vs. 96.9 (48.5, 150.9) ng/mL, P = 0.006] but not in those with TIR ≤ 70%; serum vWF level was remarkably decreased in patients with TIR > 70% [from 1166.2 (848.1, 1335.5) mIU/mL to 907.4 (674.3, 1335.1) mIU/mL, P = 0.001] while this effect was modest in those with TIR ≤ 70%.

CONCLUSIONS

Treatment with exenatide increases TIR and decreases glycemic variability in patients with T2DM. Moreover, the amelioration of endothelial injury is more pronounced in patients with TIR > 70% after the treatment.

TRIAL REGISTRATION

ChiCTR-IPR-15006558 (registered, 27 May 2015).

Testing a very low-carbohydrate adaption of the Diabetes Prevention Program among adults with prediabetes: study protocol for the Lifestyle Education about prediabetes (LEAP) trial

BACKGROUND

The Center for Disease Control and Prevention's National Diabetes Prevention Program (NDPP) aims to help individuals with prediabetes avoid progression to type 2 diabetes mellitus (T2DM) through weight loss. Specifically, the NDPP teaches individuals to follow a low-fat, calorie-restricted diet and to engage in regular physical activity to achieve ≥ 5% body weight loss. Most NDPP participants, however, do not achieve this weight loss goal, and glycemic control remains largely unchanged. One promising opportunity to augment the NDPP's weight loss and glycemic effectiveness may be to teach participants to follow a very low-carbohydrate diet (VLCD), which can directly reduce post-prandial glycemia and facilitate weight loss by reducing circulating insulin and enabling lipolysis. To date, there have been no high-quality, randomized controlled trials to test whether a VLCD can prevent progression to T2DM among individuals with prediabetes. The aim of this study is to test the effectiveness of a VLCD version the NDPP (VLC-NDPP) versus the standard NDPP. We hypothesize the VLC-NDPP will demonstrate greater improvements in weight loss and glycemic control.

METHODS

We propose to conduct a 12-month, 1:1, randomized controlled trial that will assign 300 adults with overweight or obesity and prediabetes to either the NDPP or VLC-NDPP. The primary outcome will be glycemic control as measured by change in hemoglobin A1c (HbA1c) from baseline to 12 months. Secondary outcomes will include percent body weight change and changes in glycemic variability, inflammatory markers, lipids, and interim HbA1c. We will evaluate progression to T2DM and initiation of anti-hyperglycemic agents. We will conduct qualitative interviews among a purposive sample of participants to explore barriers to and facilitators of dietary adherence. The principal quantitative analysis will be intent-to-treat using hierarchical linear mixed effects models to assess differences over time.

DISCUSSION

The NDPP is the dominant public health strategy for T2DM prevention. Changing the program's dietary advice to include a carbohydrate-restricted eating pattern as an alternative option may enhance the program's effectiveness. If the VLC-NDPP shows promise, this trial would be a precursor to a multi-site trial with incident T2DM as the primary outcome.

TRIAL REGISTRATION

NCT05235425. Registered February 11, 2022.

Continuous glucose monitoring metrics for earlier identification of pre-diabetes: protocol for a systematic review and meta-analysis

INTRODUCTION

Glycaemic variability and other metrics are not well characterised in subjects without diabetes. More comprehensive sampling as obtained with continuous glucose monitoring (CGM) may improve diagnostic accuracy of the transition from health to pre-diabetes. Our goal is to investigate the glycaemic system as it shifts from health to pre-disease in adult patients without diabetes using CGM metrics. New insights may offer therapeutic promise for reversing dysglycaemia more successfully with dietary, nutritional and lifestyle change before progression occurs to pre-diabetes and diabetes.

METHODS AND ANALYSIS

This systematic review will include comprehensive searches of the PubMed, Scopus, Cochrane Library and ClinicalTrials.gov databases, with restrictions set to studies published in the last 10 years in English and planned search date 10 March 2022. Reference lists of studies that meet eligibility criteria in the screening process will subsequently be screened for the potential inclusion of additional studies. We will include studies that examine CGM use and report diagnostic criteria such as fasting glucose and/or haemoglobin A1c such that we can assess correlation between CGM metrics and established diagnostic criteria and describe how CGM metrics are altered in the transition from health to pre-diabetes. The screening and data extraction will be conducted by two independent reviewers using Covidence. All included papers will also be evaluated for quality and publication bias using Cochrane Collaboration risk of bias tools. If there are two or more studies with quantitative estimates that can be combined, we will conduct a meta-analysis after assessing heterogeneity.

ETHICS AND DISSEMINATION

The systematic review methodology does not require formal ethical review due to the nature of the study design. Study findings will be publicly available and published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42022308222.

Glycemic variability and all-cause mortality in a large prospective southern European cohort of patients with differences in glycemic status

Background

Few studies have analyzed the relationship between glucose variability (GV) and adverse health outcomes in patients with differences in glycemic status. The present study tests the hypothesis that GV predicts all-cause mortality regardless of glycemic status after simple adjustment (age and sex) and full adjustment (age, sex, cardiovascular disease, hypertension, use of aspirin, statins, GLP-1 receptor agonists, SGLT-2 inhibitors and DPP-4 inhibitors, baseline FPG and average HbA1c).

Methods

Prospective cohort study with 795 normoglycemic patients, 233 patients with prediabetes, and 4,102 patients with type 2 diabetes. GV was measured using the coefficient of variation of fasting plasma glucose (CV-FPG) over 12 years of follow-up. The outcome measure was all-cause mortality.

Results

A total of 1,223 patients (657 men, 566 women) died after a median of 9.8 years of follow-up, with an all-cause mortality rate of 23.35/1,000 person-years. In prediabetes or T2DM patients, the fourth quartile of CV-FPG exerted a significant effect on all-cause mortality after simple and full adjustment. A sensitivity analysis excluding participants who died during the first year of follow-up revealed the following results for the highest quartile in the fully adjusted model: overall, HR (95%CI) = 1.54 (1.26–1.89); dysglycemia (prediabetes and T2DM), HR = 1.41 (1.15–1.73); T2DM, HR = 1.36 (1.10–1.67).

Conclusion

We found CV-FPG to be useful for measurement of GV. It could also be used for the prognostic stratification of patients with dysglycemia.

Comparison of the Impact of Insulin Degludec U100 and Insulin Glargine U300 on Glycemic Variability and Oxidative Stress in Insulin-Naive Patients With Type 2 Diabetes Mellitus: Pilot Study for a Randomized Trial

Background

There is an ongoing discussion about possible differences between insulin degludec (IDeg-100) and glargine U300 (IGlar-300). There is little data and head-to-head comparison of IDeg-100 and IGlar-300 regarding their simultaneous impact on glycemic variability and oxidative stress in patients with type 2 diabetes mellitus (T2DM).

Objective

In our randomized, open-label, crossover study, we compared the impact of IDeg-100 and IGlar-300 on glycemic variability and oxidative stress in insulin-naive patients with T2DM.

Methods

We recruited a total of 25 adult patients with T2DM (7 females) whose diabetes was uncontrolled (HbA1c ≥7.5%) on two or more oral glucose-lowering drugs; a total of 22 completed the study. Mean age was 57.3 (SD 6.99) years and duration of diabetes was 9.94 (SD 5.01) years. After the washout period, they were randomized alternately to first receive either IDeg-100 or IGlar-300 along with metformin. Each insulin was administered for 12 weeks and then switched. At the beginning and end of each phase, biochemical and oxidative stress parameters were analyzed. On 3 consecutive days prior to each control point, patients performed a 7-point self-monitoring of blood glucose profile. Oxidative stress was assessed by measuring thiol groups and hydroperoxides (determination of reactive oxygen metabolites test) in serum.

Results

IGlar-300 reduced mean glucose by 0.02-0.13 mmol/L, and IDeg-100 reduced glucose by 0.10-0.16 mmol/L, with no significant difference. The reduction of the coefficient of glucose variation also did not show a statistically significant difference. IGlar-300 increased thiols by 0.08 µmol/L and IDeg-100 increased thiols by 0.15 µmol/L, with no significant difference (P=.07) between them. IGlar-300 reduced hydroperoxides by 0.040 CARR U and IDeg-100 increased hydroperoxides by 0.034 CARR U, but the difference was not significant (P=.12).

Conclusions

The results of our study do not show a significant difference regarding glycemic variability between patients receiving either insulin IDeg-100 or IGlar-300, although IGlar-300 showed greater dispersion of data. No significant difference in oxidative stress was observed. In a larger study, doses of insulins should be higher to achieve significant impact on glycemic parameters and consequently on glycemic variability and oxidative stress.

Trial Registration

ClinicalTrials.gov, NCT04692415; https://clinicaltrials.gov/ct2/show/NCT04692415

In vitro toxic interaction of arsenic and hyperglycemia in mitochondria: an important implication of increased vulnerability in pre-diabetics

Environmental pollutants and lifestyle both contribute to the rapidly increasing prevalence of type 2 diabetes mellitus (T2DM) worldwide. Evidence suggests that exposure to environmental contaminants such as arsenic is associated with impaired glucose metabolism and insulin signaling. In the present study, isolated rat liver mitochondria (1 mg/ml) were co-exposed to low concentration of arsenic trioxide (ATO) ( IC₂₅ = 40 µM) and hyperglycemic condition (20, 40, 80, 160 mM glucose or 20, 40, 80, 160 mM pyruvate (PYR)). Mitochondrial dehydrogenase activity (complex II), glutathione content (GSH), reactive oxygen species (ROS), lipid peroxidation, mitochondrial membrane potential (ΔΨ), and mitochondrial swelling were then evaluated in the presence of ATO 40 µM and PYR 40 mM. Unexpectedly, glucose alone (20, 40, 80, 160 mM) had no toxic effect on mitochondria, even at very high concentrations and even when combined with ATO. Interestingly, PYR at low concentrations (≤ 10 mM) has a protective effect on mitochondria, but at higher concentrations (≥ 40 mM) with ATO, it decreased the complex II activity and increased mitochondrial ROS production, lipid peroxidation, GSH depletion, mitochondrial membrane damage, and swelling (p < 0.05). In conclusion, PYR but not glucose increased ATO mitochondrial toxicity even at low concentrations. These results suggest that pre-diabetics with non-clinical hyperglycemia, who are inevitably exposed to low concentrations of arsenic through food and water, may develop mitochondrial dysfunction that accelerates their progression to diabetes over time.

Cross-Sectional and Individual Relationships between Physical Activity and Glycemic Variability

Introduction/Purpose

Overweight or obese adults spend more time sedentary and less time performing physical activity (PA) and are at an increased risk for developing impaired glycemic health. Free-living environments may provide insight into glycemic health in addition to clinical assessments. The purpose of this study was to examine the relationship between PA and glycemic health assessed by continuous glucose monitoring (CGM).

Methods

Twenty-eight overweight or obese adults each wore an accelerometer and CGM over the same 7 consecutive days. Average daily time (minutes and metabolic-equivalent minutes (MET-minutes)) and associated energy expenditure performing light (LPA), moderate-to-vigorous (MVPA), total PA, and standard deviation (SD) across days were calculated. Average daily 24-h and waking glycemia, mean glucose concentration, glycemic variability measured as the continuous overlapping net glycemic action, mean amplitude of glycemic excursions, and mean of daily difference were assessed.

Results

LPA MET-minutes per day was positively associated with 24-h and waking glycemia time-in-range and negatively associated with 24-h and waking time in hyperglycemia. Total PA time and the SD of MVPA and total PA time were negatively associated with 24-h mean glucose concentration. Individual-level analysis identified that most participants (50%-71%) expressed negative associations between LPA and MVPA time with 24-h mean glucose concentration, mean amplitude of glycemic excursion, and 4-h continuous overlapping net glycemic action.

Conclusions

Expectedly, greater total PA time and intensity-specific PA time were associated with lower 24-h and waking mean glucose concentration, greater glycemia time-in-range, and less time in hyperglycemia. The relationship between glucose concentrations and PA time SD was unexpected, whereas most participants expressed hypothesized relationships, which necessitates further exploration.

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.

The northeast glucose drift: Stratification of post-breakfast dysglycemia among predominantly Hispanic/Latino adults at-risk or with type 2 diabetes

BACKGROUND

There is minimal experience in continuous glucose monitoring (CGM) among underserved racial/ethnic minority populations with or at risk of type 2 diabetes (T2D), and therefore a lack of CGM-driven insight for these individuals. We analyzed breakfast-related CGM profiles of free-living, predominantly Hispanic/Latino individuals at-risk of T2D, with pre-T2D, or with non-insulin treated T2D.

METHODS

Starting February 2019, 119 participants in Santa Barbara, CA, USA, (93 female, 87% Hispanic/Latino [predominantly Mexican-American], age 54·4 [±12·1] years), stratified by HbA_1c levels into (i) at-risk of T2D, (ii) with pre-T2D, and (iii) with non-insulin treated T2D, wore blinded CGMs for two weeks. We compared valid CGM profiles from 106 of these participants representing glucose response to breakfast using four parameters.

FINDINGS

A "northeast drift" was observed in breakfast glucose responses comparing at-risk to pre-T2D to T2D participants. T2D participants had a significantly higher pre-breakfast glucose level, glucose rise, glucose incremental area under the curve (all p < 0·0001), and time to glucose peak (p < 0·05) compared to pre-T2D and at-risk participants. After adjusting for demographic and clinical covariates, pre-breakfast glucose and time to peak (p < 0·0001) were significantly associated with HbA_1c. The model predicted HbA_1c within (0·55 ± 0·67)% of true laboratory HbA_1c values.

INTERPRETATION

For predominantly Hispanic/Latino adults, the average two-week breakfast glucose response shows a progression of dysglycemia from at-risk of T2D to pre-T2D to T2D. CGM-based breakfast metrics have the potential to predict HbA_1c levels and monitor diabetes progression.

FUNDING

US Department of Agriculture (Grant #2018-33800-28404), a seed grant from the industry board fees of the NSF Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (Award #1648451), and the Elsevier foundation.

Glycemic variability of acute stroke patients and clinical outcomes: a continuous glucose monitoring study

Introduction:

Glycemic variability (GV) has been associated with worse prognosis in critically ill patients. We sought to evaluate the potential association between GV indices and clinical outcomes in acute stroke patients.

Methods:

Consecutive diabetic and nondiabetic, acute ischemic or hemorrhagic stroke patients underwent regular, standard-of-care finger-prick measurements and continuous glucose monitoring (CGM) for up to 96 h. Thirteen GV indices were obtained from CGM data. Clinical outcomes during hospitalization and follow-up period (90 days) were recorded. Hypoglycemic episodes disclosed by CGM but missed by finger-prick measurements were also documented.

Results:

A total of 62 acute stroke patients [48 ischemic and 14 hemorrhagic, median NIHSS score: 9 (IQR: 3–16) points, mean age: 65 ± 10 years, women: 47%, nondiabetic: 79%] were enrolled. GV expressed by higher mean absolute glucose (MAG) values was associated with a lower likelihood of neurological improvement during hospitalization before and after adjusting for potential confounders (OR: 0.135, 95% CI: 0.024–0.751, p = 0.022). There was no association of GV indices with 3-month clinical outcomes. During CGM recording, 32 hypoglycemic episodes were detected in 17 nondiabetic patients. None of these episodes were identified by the periodic blood glucose measurements and therefore they were not treated.

Conclusions:

Greater GV of acute stroke patients may be related to lower odds of neurological improvement during hospitalization. No association was disclosed between GV indices and 3-month clinical outcomes.

Alternative Dietary Patterns for Americans: Low-Carbohydrate Diets

The decades-long dietary experiment embodied in the Dietary Guidelines for Americans (DGA) focused on limiting fat, especially saturated fat, and higher carbohydrate intake has coincided with rapidly escalating epidemics of obesity and type 2 diabetes (T2D) that are contributing to the progression of cardiovascular disease (CVD) and other diet-related chronic diseases. Moreover, the lack of flexibility in the DGA as it pertains to low carbohydrate approaches does not align with the contemporary trend toward precision nutrition. We argue that personalizing the level of dietary carbohydrate should be a high priority based on evidence that Americans have a wide spectrum of metabolic variability in their tolerance to high carbohydrate loads. Obesity, metabolic syndrome, and T2D are conditions strongly associated with insulin resistance, a condition exacerbated by increased dietary carbohydrate and improved by restricting carbohydrate. Low-carbohydrate diets are grounded across the time-span of human evolution, have well-established biochemical principles, and are now supported by multiple clinical trials in humans that demonstrate consistent improvements in multiple established risk factors associated with insulin resistance and cardiovascular disease. The American Diabetes Association (ADA) recently recognized a low carbohydrate eating pattern as an effective approach for patients with diabetes. Despite this evidence base, low-carbohydrate diets are not reflected in the DGA. As the DGA Dietary Patterns have not been demonstrated to be universally effective in addressing the needs of many Americans and recognizing the lack of widely available treatments for obesity, metabolic syndrome, and T2D that are safe, effective, and sustainable, the argument for an alternative, low-carbohydrate Dietary Pattern is all the more compelling.

Dysglycemia in adults at risk for or living with non-insulin treated type 2 diabetes: Insights from continuous glucose monitoring

BACKGROUND

Continuous glucose monitoring (CGM) has demonstrable benefits for people living with diabetes, but the supporting evidence is almost exclusively from White individuals with type 1 diabetes. Here, we have quantified CGM profiles in Hispanic/Latino adults with or at-risk of non-insulin treated type 2 diabetes (T2D).

METHODS

100 participants (79 female, 86% Hispanic/Latino [predominantly Mexican], age 54·6 [±12·0] years) stratified into (i) at risk of T2D, (ii) with pre-diabetes (pre-T2D), and (iii) with non-insulin treated T2D, wore blinded CGMs for 2 weeks. Beyond standardized CGM measures (average glucose, glucose variability, time in 70-140 mg/dL and 70-180 mg/dL ranges), we also examined additional CGM measures based on the time of day.

FINDINGS

Standardized CGM measures were significantly different for participants with T2D compared to at-risk and pre-T2D participants (p<0·0001). In addition, pre-T2D participants spent more time between 140 and 180 mg/dL during the day than at-risk participants (p<0·01). T2D participants spent more time between 140 and 180 mg/dL both during the day and overnight compared to at-risk and pre-T2D participants (both p<0·0001). Time in 70-140 mg/dL range during the day was significantly correlated with HbA_1c (r=-0·72, p<0·0001), after adjusting for age, sex, BMI, and waist circumference (p<0·0001).

INTERPRETATION

Standardized CGM measures show a progression of dysglycemia from at-risk of T2D, to pre-T2D, and to T2D. Stratifying CGM readings by time of day and the range 140-180 mg/dL provides additional metrics to differentiate between the groups.

FUNDING

US Department of Agriculture (Grant #2018-33800-28404) and NSF PATHS-UP ERC (Award #1648451).

A single arm trial using passive simulated jogging for blunting acute hyperglycemia

Glycemic fluctuations increase oxidative stress, promote endothelial dysfunction and cardiovascular disease. Reducing glycemic fluctuations is beneficial. We previously reported that a portable motorized passive simulated jogging device, (JD) reduces 24 h glycemic indices in type 2 and non-diabetic subjects. This study evaluates effectiveness and feasibility of JD in blunting large glycemic fluctuation induced by an oral glucose tolerance test (OGTT). The study was performed in 10 adult participants mean age 41.3 ± 13.5 year using interstitial glucose monitor (IG). Each participant fasted for 8 h. followed by an OGTT (Pre-JD), thereafter JD was used for 90 min per day for 7 days, without change to diet or activities of daily living. A repeat OGTT (Post-JD) was performed after completion. The integrated area under the curve (iAUC_2h–4h) was computed for the OGTT Pre-JD and Post-JD. Seven days of JD blunted the glucose fluctuation produced by OGTT. JD decreased AUC_2h by 17 ± 4.7% and iAUC_4h by 15 ± 5.9% (p < 0.03). In healthy mostly obese participants 7 days of JD blunts the hyperglycemic response produced by an OGTT. JD may be an adjunct to current glycemic management, it can be applied in different postures for those who cannot (due to physical or cognitive limitations) or will not exercise.

Trial registration:ClinicalTrials.gov NCT03550105 (08-06-2018).

Glycemic deviation index: a novel method of integrating glycemic numerical value and variability

BACKGROUND

There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established.

METHODS

In this study, we proposed the glycemic deviation index (GDI) as a novel integrating characteristic, which mainly incorporates the assessment of the glycemic numerical value and variability. To verify its effectiveness, GDI was applied to the simulated 24 h glycemic profiles and the CGM data of type 2 diabetes (T2D) patients (n = 30).

RESULTS

Evaluation of the GDI of the 24 h simulated glycemic profiles showed that the occurrence of hypoglycemia was numerically the same as hyperglycemia in increasing GDI. Meanwhile, glycemic variability was added as an independent factor. One-way ANOVA results showed that the application of GDI showed statistically significant differences in clinical glycemic parameters, average glycemic parameters, and glycemic variability parameters among the T2D groups with different glycemic levels.

CONCLUSIONS

In conclusion, GDI integrates the characteristics of the numerical value and the variability in blood glucose levels and may be beneficial for the glycemic management of diabetic patients undergoing CGM treatment.

Oscillatory pattern of glycemic control in patients with diabetes mellitus

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

The relationship between glycemic variability and blood pressure variability in normoglycemic normotensive individuals

BACKGROUND AND AIM

Glycemic fluctuations around a mean glucose level, referred as glycemic variability and blood pressure variability (BPV) are considered as independent risk factors for cardiovascular diseases, all-cause mortality, and cardiovascular disease-mortality. With this background in mind, we aimed to investigate the association between glycemic variability and BPV and their association in normoglycemic and normotensive individuals.

MATERIALS AND METHOD

Twenty-seven normotensive normoglycemic individuals were recruited. Twenty-four hour Holter devices were utilized to measure ambulatory blood pressure (BP) while continuous glucose monitoring (CGM) devices were applied to measure glycemic variability simultaneously to the subjects. These devices were kept on for 48 h. For BP recordings, daytime, nighttime, and 24-h BP determinations, their mean and SD were calculated. From CGM measurements, mean blood glucose (MBG), SD of blood glucose, the mean amplitude of glycemic excursions (MAGE), the mean of daily differences (MODD), coefficient of variation (correction of variability for the MBG), and daytime and nighttime blood glucose were determined.

RESULTS

The mean age of the subjects was 23.8 ± 2.7 years and 66% were women (18/27). In the correlation analysis between glycemic variability parameters and BPV parameters, SD of 24-h SBP was correlated with the SD of MBG (r = 0.52, P = 0.006), MAGE (r = 0.49, P = 0.009), and MODD (r = 0.46, P = 0.015). SD of daytime SBP was correlated with, MAGE (r = 0.42, P = 0.03) and MODD (r = 0.43, P = 0.02).

CONCLUSION

We report correlation between glycemic variability and BPV variables in normoglycemic and normotensive healthy individuals.

Short-term glycemic variability and hemorrhagic transformation after successful endovascular thrombectomy

BACKGROUND

Glycemic variability (GV) is a risk factor for poor outcomes after ischemic stroke. However, its effect on hemorrhagic transformation after endovascular recanalization therapy (ERT) remains to be elucidated.

METHODS

Patients with acute ischemic stroke due to large vessel occlusion with successful recanalization after ERT (modified thrombolysis in cerebral infarction 2b or 3) were enrolled between January 2013 and November 2019. Blood glucose level data were obtained during the first 36 h after ERT, and ten GV parameters including time rate (TR) of glucose variation were assessed. The TR of glucose variation reflects the speed of glucose fluctuations over time (mg/dL/hour) during the monitoring period. Symptomatic intracerebral hemorrhage (sICH) and unfavorable outcomes at 3 months after ERT were analyzed. The sICH was defined as parenchymal hematoma type 2 with a neurological deterioration of 4 points or more on the National Institute of Health Stroke Scale. Moreover, a modified Rankin Scale of 3-6 at 3 months was considered an unfavorable outcome.

RESULTS

Among all patients (n = 176; mean age, 69.3 years; 47.7 % female), sICH developed after successful ERT in 16 (9.1%) patients. In addition, 54% (n = 95) patients had an unfavorable outcome at 3 months. Patients with sICH and unfavorable outcome had higher the TR of glucose variation. After adjusting for potential confounders, the TR of glucose (per 1 mg/dL/h increase) variation was independently associated with sICH (odds ratio, 1.17; 95% confidence interval [CI], 1.012-1.343) and 3-month unfavorable outcome (OR 1.14, 95% CI, 1.000-1.297).

CONCLUSIONS

Time-related GV during the first 36 h after successful ERT has a stronger correlation with sICH and poor functional outcomes compared to any GV parameters. This suggests that maintaining stable glucose may be an important factor in the prevention of sICH after undergoing successful ERT.

The Beta-Cell Function and Glucose Profile of Newly Diagnosed Acromegalic Patients with Normal Glucose Tolerance

OBJECTIVES

Untreated acromegaly is a nature model for unveiling the diabetogenic effects of GH. CGMS can uncover more glucose profile of acromegaly. This study aimed to evaluate the insulin resistance (IR), β-cell function, and glycemic spectrum of patients with newly diagnosed acromegaly with normal glucose tolerance (NGT).

METHODS

This study was conducted in Huashan Hospital from January 2015 to February 2019. Eight newly diagnosed acromegalic patients without history of diabetes and eight age- and gender-matched healthy subjects were enrolled. All participants underwent oral glucose tolerance test (OGTT) and 72 h continuous glucose monitoring (CGM). Parameters on β-cell function and IR were calculated. Mean blood glucose (MBG) in 24 hours was adopted for the evaluation of the glycemic level, and standard deviation of blood glucose (SDBG) and mean amplitude of glycemic excursion (MAGE) were used for glucose fluctuation.

RESULTS

HbA1c in the acromegaly group was significantly higher than in the control. During OGTT, glucose peaked at 60 min in acromegaly and at 30 min in controls. After glucose load, the acromegaly group had significantly higher insulin levels than controls, especially in 120 min and 180 min. Both insulin sensitivity index and disposal index after glucose load of acromegaly were significantly lower than those of controls. Moreover, acromegalic subjects had significantly higher MBG than controls.

CONCLUSIONS

The newly diagnosed acromegalic patients with NGT were characterized by IR and impaired β-cell function after glucose load. CGM showed that MBG of NGT acromegaly patients was higher than that of normal people.

The dawn phenomenon across the glycemic continuum: Implications for defining dysglycemia

AIMS

To investigate the frequency of dawn phenomenon (DP) and its relationship with time in range (TIR) and glycemic variability (GV) using continuous glucose monitoring (CGM).

METHODS

781 subjects of a multicenter CGM study in China were included: those with normal glucose tolerance (NGT n = 360); impaired glucose regulation (IGR n = 173); newly diagnosed type 2 diabetes mellitus (T2D n = 248). Analysis of the magnitude of DP (ΔG) was conducted with the primary definition of 1.11 mmol/L and a secondary definition of 0.56 mmol/L.

RESULTS

The frequency of DP was 8.9%, 30.1% and 52.4% in NGT, IGR and T2D group, respectively, using the primary definition. In all three groups, TIR was lower (all P < 0.05), coefficient of variation (CV) was higher in DP subgroup (all P < 0.05). In DP subgroup of T2D, TIR was 7.0% (1.68 h) lower and CV was 3.0% higher, and HbA_1c was 0.6% (7 mmol/mol) higher using the primary definition (all P < 0.05).

CONCLUSIONS

DP was present in a high percent of subjects with NGT and IGR. In newly diagnosed T2D group, the presence of DP was associated with poorer overall glycemic control.

Small changes in glucose variability induced by low and high glycemic index diets are not associated with changes in β-cell function in adults with pre-diabetes

Oscillating glucose levels can increase oxidative stress and may contribute to β-cell dysfunction. We tested the hypothesis that increased glycemic variability contributes to β-cell dysfunction by experimentally altering glucose variability with controlled diets varying in glycemic index (GI). Fifty-two adults with prediabetes received a 2-week moderate GI (GI = 55-58) control diet followed by randomization to a four-week low GI (LGI: GI < 35) or high GI (HGI HI > 70) diet. Those on the HGI diet were randomized to placebo or the antioxidant N-acetylcysteine (NAC). Participants underwent blinded CGMS, fasting oxidative stress markers and an intravenous glucose tolerance test to estimate β-cell function (disposition index: DI). On the control diet, DI was inversely correlated with SD glucose (r = -0.314, p = 0.03), but neither DI nor glucose variability were associated with oxidative stress markers. The LGI diet decreased SD glucose (Control 0.96 ± 0.08 vs. LGI 0.79 ± 0.06, p = 0.02) while the HGI diet increased it (Control 0.88 ± 0.06 vs. HGI 1.06 ± 0.07, p = 0.03). Neither DI nor oxidative stress markers changed after the LGI or HGI diets. NAC had no effect on DI, glucose variability or oxidative stress markers. We conclude small changes in glucose variability induced by dietary GI in adults with pre-diabetes are unlikely to contribute to β-cell dysfunction.

A basal-bolus insulin regimen integrated microneedle patch for intraday postprandial glucose control

Multiple daily insulin injections have been a common regimen worldwide for the management of diabetes mellitus but involved potential safety and compliance problems. In this context, a single integrated microneedle patch (IMP) with multiple release kinetics is demonstrated to provide better physiologic insulin coverage for postprandial glycemic excursion in a convenient and pain-free manner. The combination of rapid separating technique and multiple individual microneedle arrays provides the combined ability to efficiently deliver insulin into the skin within seconds and to independently control insulin release kinetics. In addition, the diabetic rats with a traditional breakfast-lunch-dinner lifestyle exhibit obvious intraday glucose fluctuations, while the hypoglycemic experiments indicate that the IMP is capable of simultaneous bolus and sustained insulin delivery to closely match the glucose rise that occurs in response to meals and efficiently minimize excessive fluctuations, suggesting the potential of this new transdermal insulin delivery system as substitutes for multiple daily injections.

Glucose Variability Assessed with Continuous Glucose Monitoring: Reliability, Reference Values, and Correlations with Established Glycemic Indices-The Maastricht Study

Background: Glucose variability (GV) measured by continuous glucose monitoring (CGM) has become an accepted marker of glycemic control. Nevertheless, several methodological aspects of GV assessment require further study. We, therefore, investigated the minimum number of days needed to reliably measure GV, assessed GV reference values, and studied the correlation of GV with established glycemic indices (i.e., HbA_1c, seven-point oral glucose tolerance test [OGTT]-derived indices). Methods: We used cross-sectional data from The Maastricht Study, an observational population-based cohort enriched with type 2 diabetes. Participants with more than 48 h of CGM (iPro2; Medtronic) were included for analysis (n = 851; age: 60 ± 9years; 49% women; 23% type 2 diabetes). We used mean sensor glucose (MSG), standard deviation (SD), and coefficient of variation (CV) as CGM-derived indices (the latter two for GV quantification). We calculated reliability using the Spearman-Brown prophecy formula, established reference values by calculating 2.5th-97.5th percentiles, and studied correlations using Spearman's rho. Results: Sufficient reliability (R > 0.80) was achieved with two (MSG and SD), or three monitoring days (CV). The reference ranges, assessed in individuals with normal glucose metabolism (n = 470), were 90.5-120.6 mg/dL (MSG), 7.9-24.8 mg/dL (SD), and 7.74%-22.45% (CV). For MSG, the strongest correlation was found with fasting plasma glucose (rho = 0.65 [0.61; 0.69]); for SD, with the 1-h OGTT value (rho = 0.61 [0.56; 0.65]); and for CV, with both the incremental glucose peak (IGP) during the OGTT (rho = 0.50 [0.45; 0.55]) and the 1-h OGTT value (rho = 0.50 [0.45; 0.55]). Conclusions: The reliability findings and reference values are relevant for studies that aim to investigate CGM-measured GV. One-hour OGTT and IGP values can be used as GV indices when CGM is unavailable.

Glucose Variability as Measured by Inter-measurement Percentage Change is Predictive of In-patient Mortality in Aneurysmal Subarachnoid Hemorrhage

BACKGROUND

Critically ill aneurysmal subarachnoid hemorrhage (aSAH) patients suffer from systemic complications at a high rate. Hyperglycemia is a common intensive care unit (ICU) complication and has become a focus after aggressive glucose management was associated with improved ICU outcomes. Subsequent research has suggested that glucose variability, not a specific blood glucose range, may be a more appropriate clinical target. Glucose variability is highly correlated to poor outcomes in a wide spectrum of critically ill patients. Here, we investigate the changes between subsequent glucose values termed "inter-measurement difference," as an indicator of glucose variability and its association with outcomes in patients with aSAH.

METHODS

All SAH admissions to a single, tertiary referral center between 2002 and 2016 were screened. All aneurysmal cases who had more than 2 glucose measurements were included (n = 2451). We calculated several measures of variability, including simple variance, the average consecutive absolute change, average absolute change by time difference, within subject variance, median absolute deviation, and average or median consecutive absolute percentage change. Predictor variables also included admission Hunt and Hess grade, age, gender, cardiovascular risk factors, and surgical treatment. In-patient mortality was the main outcome measure.

RESULTS

In a multiple regression analysis, nearly all forms of glucose variability calculations were found to be correlated with in-patient mortality. The consecutive absolute percentage change, however, was most predictive: OR 5.2 [1.4-19.8, CI 95%] for percentage change and 8.8 [1.8-43.6] for median change, when controlling for the defined predictors. Survival to ICU discharge was associated with lower glucose variability (consecutive absolute percentage change 17% ± 9%) compared with the group that did not survive to discharge (20% ± 15%, p < 0.01). Interestingly, this finding was not significant in patients with pre-admission poorly controlled diabetes as indicated by HbA1c (OR 0.45 [0.04-7.18], by percentage change). The effect is driven mostly by non-diabetic patients or those with well-controlled diabetes.

CONCLUSIONS

Reduced glucose variability is highly correlated with in-patient survival and long-term mortality in aSAH patients. This finding was observed in the non-diabetic and well-controlled diabetic patients, suggesting a possible benefit for personalized glucose targets based on baseline HbA1c and minimizing variability. The inter-measure percentage change as an indicator of glucose variability is not only predictive of outcome, but is an easy-to-use tool that could be implemented in future clinical trials.

The impact of shift work on glycemic characteristics assessed by CGM and its association with metabolic indices in non-diabetic subjects

AIM

To explore the glycemic characteristics of non-diabetic shift workers and associations with metabolic indices.

METHODS

In this cross-sectional study, 450 non-diabetic males, including 238 shift workers, aged 23-58 years, were recruited after a screening oral glucose tolerance test. Blood samples and anthropometric data were collected. Hundred and fifty of them finished a continuous glucose monitoring for 3-7 days.

RESULTS

Compared to daytime workers, shift workers presented with larger WHR (p < 0.001), higher HOMA-IR (p < 0.001), higher hs-CRP level (p < 0.001) and worse lipid profiles. In glycemic characteristics, shift workers with normal glucose regulation had a similar mean blood glucose (MBG), daytime MBG, percentage of time of hyperglycemia, hypoglycemia, euglycemia, and fluctuation parameters, including standard deviation of blood glucose (SDBG), mean amplitude of glycemic excursions (MAGE) and mean of daily differences (p > 0.05, respectively), while they had a higher nighttime MBG (p = 0.026) and blood glucose (BG) at 3 a.m. (p = 0.015). For subjects with impaired glucose regulation, both groups had no difference in any clinical characteristics or glycemic parameters (p > 0.05, respectively). Further regression analysis revealed the association between MBG/SDBG/MAGE/nighttime MBG/BG at 3 a.m. and age/WHR/hs-CRP/TC.

CONCLUSION

For non-diabetic shift workers, the glycemic characteristic was the elevated nighttime glycemia, presented as higher nighttime MBG and BG at 3 a.m. And both metrics were closely associated with central obesity. Elevated nighttime glycemia was an early signal of glucose metabolism disorder in shift workers.

Efficacy and safety of a needle-free injector in Chinese patients with type 2 diabetes mellitus treated with basal insulin: a multicentre, prospective, randomised, crossover study

Objective: To evaluate the efficacy and safety of a needle-free injector in Chinese patients with type 2 diabetes mellitus treated with basal insulin. Methods: 62 patients with type 2 diabetes were enrolled in a multicenter, randomised, prospective, open-label, crossover study. All patients received subcutaneous insulin glargine administered by a needle-free injector or a glargine pen for 7 ~ 14 days, and were then crossed over after wash out. Results: Patients in the insulin needle-free injector (NFI) and glargine pen (GP) groups achieved similar fasting blood glucose control . However, the dosage of insulin required to achieve the target FBG level in the NFI group was lower than in the GP group (16.14 ± 5.13 U/day vs 19.25 ± 6.20 U/day, respectively; p = 0.0046). This difference was more significant in patients who received higher insulin dosages compared with those receiving lower dosages. Use of the needle-free injector was also associated with significantly less pain (p < 0.001) and less fear of injection (p < 0.001) than glargine pens. Conclusion: The use of a needle-free injector can significantly lower the dosage of insulin required to achieve good glycemic control and reduce topical adverse reactions and the fear of injections as well, which help to improve patient compliance. Clinical Trial Registration Number KY20172077-1; NCT03420040.

Effects of long-term glycemic variability on incident cardiovascular disease and mortality in subjects without diabetes: A nationwide population-based study

Increased glycemic variability (GV) is an independent risk factor for cardiovascular complications in patients with diabetes. We evaluated the risk of future development of cardiovascular disease (CVD) and death according to GV in a general population without diabetes.We used the National Health Insurance Service, providing a population-based, nationwide database of Koreans. We included individuals without diabetes who underwent glucose measurement at least 3 times during 2002 to 2006. GV was calculated as standard deviation (SD) of fasting plasma glucose (FPG) levels. We observed development of CVD or all-cause death from 2007 to 2015, and also evaluated the mortality within 1 year after CVD.Among 3,211,319 people, we found 23,374 incident cases of myocardial infarction (MI), 27,705 cases of stroke, and 63,275 deaths during 8.3 years of follow-up. After multivariate adjustment, GV was found to be a significant predictor of MI, stroke and all-cause death for their highest quartile, with corresponding hazard ratios (HR) of 1.08 (95% confidence interval, CI 1.04-1.11), 1.09 (95% CI 1.06-1.13), and 1.12 (95% CI 1.10-1.15), respectively. The risk of death increased more in those who had both impaired fasting glucose and the highest quartile of GV (HR 1.24 [95% CI 1.21-1.28]). Moreover, early death rate after 1 year of CVD was higher in the highest quartile of GV compared to the lowest quartile (HR 1.21 [95% CI 1.03-1.41]).Long-term FPG variation was independently associated with CVD and mortality in a general population without diabetes.

Assessment of glucose variability in subjects with prediabetes

The aim of the study was to assess glucose variability in subjects with prediabetes by means of CGM.

MATERIAL AND METHODS

32 subjects with prediabetes - mean age 56.6 ± 9.6 years, mean BMI 30.3 ± 5.3 kg/m² and 18 subjects with normal glucose tolerance (NGT) - mean age 54.4 ± 9.9 years, mean BMI 24.8 ± 6.9 kg/m², were enrolled. Glucose tolerance was studied during OGTT. HbA1c was measured by NGSP certified method. CGM was performed with FreeStyle Libre Pro sensor.

RESULTS

The following indices of glucose variability were significantly higher in the prediabetes group - CV (p < 0.041), J-index (p < 0.014), CONGA (p < 0.047) and GRADE (p < 0.036). A significant increase in HbA1c (p < 0.036), mean interstitial glucose (p < 0.025), time above range (p < 0.018) and a significant decrease in time in range (p < 0.014) was found in prediabetes compared to NGT. Significant correlations between HbA1c and LBGI (r = -0.33, p = 0.02), HBGI (r = 0.31, p = 0.03), CONGA (r = 0.36, p = 0.01), J-index (r = 0.37, p = 0.01) and M-value (r = -0.34, p = 0.02) were established.

CONCLUSION

Glucose variability is significantly increased in prediabetes and is an additional parameter in the assessment of glucose homeostasis even at these early stages of glucose dysregulation.

Effects of Moderate Cycling Exercise on Blood Glucose Regulation Following Successful Clinical Islet Transplantation

CONTEXT

Islet transplantation is effective in preventing hypoglycemia in patients with type 1 diabetes (T1D). However, it is unknown whether transplanted islets regulate plasma glucose concentrations appropriately during and after exercise in human islet transplant recipient (ITxs).

OBJECTIVE

To determine the effect of exercise on plasma glucose, insulin, and glucagon concentrations in ITxs compared with control subjects (CONs) without diabetes.

INTERVENTION

Participants completed two conditions in random order: 45 minutes of aerobic exercise (60% VO2peak) and 45 minutes of seated rest. Blood samples were drawn at baseline, immediately after exercise or rest, and every 15 minutes throughout a 60-minute recovery period. Postexercise (24 hours) interstitial glucose was monitored with continuous glucose monitoring (CGM).

RESULTS

Twenty-four participants (12 ITxs, 12 CONs) completed the protocol. Plasma glucose decreased more over time with exercise in ITxs compared with CONs [main effects of treatment (P = 0.019), time (P = 0.001), and group (P = 0.012)]. Plasma glucose was lower during exercise vs rest in ITxs but not CONs [treatment by group interaction (P = 0.028)]. Plasma glucose decreased more during exercise than during rest [treatment by time interaction (P = 0.001)]. One ITx and one CON experienced plasma glucose concentrations <3.5 mmol/L at the end of exercise, both of whom returned above that threshold within 15 minutes. Nocturnal CGM glucose <3.5 mmol/L was detected in two CONs but no ITxs.

CONCLUSION

Despite a greater plasma glucose decline during exercise in ITxs, hypoglycemia risk was similar during and after exercise in ITxs compared with CONs.

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

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

Glycemic Profiling in Patients with Drug-Naïve Type 2 Diabetes by Continuous Glucose Monitoring

The purpose of this study was to determine the glycemic profiles of drug-naïve type 2 diabetes patients according to hemoglobin A1c (HbA1c) level using continuous glucose monitoring. We aimed to clarify factors associated with HbA1c and average blood glucose level. Patients were divided into three groups according to their HbA1c level (< 7.0% n=23, 7.0% ≤ HbA1c < 8.0% n=17 and ≥ 8.0% n=31), and the factors associated with HbA1c and average glucose of each group were evaluated. Pre-meal glucose levels were the highest before lunch, and the 2 hour postprandial blood glucose level was the lowest after lunch. The pre-meal and postprandial blood glucose levels increased after each meal with increases in HbA1c. Average glucose level was the most significant determinant of HbA1c, whereas pre-meal glucose level at dinner was the most significant determinant of average glucose level, and the range of increase in glucose from pre-meal at dinner was the most significant determinant of standard deviation (SD) of 24 hour glucose levels. HbA1c subgroup analysis indicated that pre-meal glucose level at lunch significantly correlated with average glucose level in the HbA1c < 8.0% group, while pre-meal glucose level at dinner significantly correlated with average glucose level in the HbA1c ≥ 8.0% group. The range of increase in glucose from pre-meal in the morning significantly correlated with SD of 24 hour glucose levels in the HbA1c < 8.0% group, and the postprandial peak glucose level at lunch significantly correlated with SD of 24 hour glucose levels in the HbA1c ≥ 8.0% group. The results suggest that improvement of the average glucose level is necessary to improve the HbA1c levels. For patients with HbA1c < 7.0%, it is important to improve blood glucose level after breakfast and before lunch to decrease the average glucose level. For patients with 7.0% ≤ HbA1c < 8.0%, it is important to improve blood glucose level before lunch and after dinner to decrease the average glucose level. For patients with HbA1c ≥ 8.0%, it is important to improve blood glucose levels after lunch and before dinner to decrease the average glucose level.

Continuous glucose monitoring is more sensitive than HbA1c and fasting glucose in detecting dysglycaemia in a Spanish population without diabetes

AIMS

To investigate whether continuous glucose monitoring (CGM) reveals patterns of glycaemic behaviour, the detection of which might improve early diagnosis of dysglycaemia.

METHODS

A total 1521 complete days of valid CGM data were recorded under real-life conditions from a healthy sample of a Spanish community, as were matching FPG and HbA1_C data. No participant was pregnant, had a history of kidney or liver disease, or was taking drugs known to affect glycaemia.

RESULTS

CGM and fingerstick measurements showed a mean relative absolute difference of 6.9 ± 2.2%. All subjects were normoglycaemic according to FPG and HbA_1C except 21% who were prediabetic. The normoglycaemic subjects had a 24-hour mean blood glucose concentration (MBG) of 5.7 ± 0.4 mmol/L, spending a median of 97% of their time within the target range (3.9-7.8 mmol/L). 73% of them experienced episodes with blood glucose levels above the threshold for impaired glucose tolerance, and 5% levels above the threshold for diabetes. These normoglycaemic participants with episodes of high glycaemia had glycaemic variabilities similar to those of prediabetic subjects with episodes of similar intensity or combined duration.

CONCLUSIONS

CGM is a better indicator of possible early dysglycaemia than either FPG or HbA1c.

New insights from continuous glucose monitoring into the route to diabetes

AIM

Type 2 diabetes mellitus (T2DM) is preceded by a period of impaired glucoregulation. We investigated if continuous glucose monitoring system (CGMS) (1) could improve our capacity to predict the development of T2DM in subjects at risk. (2) Find out if impaired fasting glucose/impaired glucose tolerance differentiation through CGMS would also elucidate differences in clinical phenotypes.

MATERIAL AND METHODS

Observational study of 209 hypertensive patients, aged 18 to 85 years who wore at entry a CGMS. Two CGMS metrics, percent of time under the 100 mg/dL glycaemic threshold (TU100) (impaired fasting glucose surrogate phenotype) and area above the 140 mg/dL glycemic threshold (AO140) (impaired glucose tolerance surrogate phenotype) were measured. The median follow-up was 32 months (6-72 mo), and there were 17 new cases of T2DM.

RESULTS

In a multivariate Cox proportional hazard survival analysis including the conventional prediabetes-defining criteria and the 2 CGMS-derived variables, only TU100 and HbA_1c were significant and independent variables in predicting T2DM development. An increase in 0.1 in TU100 resulted in a 0.69 (95% CI, 0.54-0.88; P < .01) odds ratio of developing T2DM. With cut-off points of 0.5 for TU100 and 5.7% for HbA_1c , the test "TU < 0.5 and HbA_1c  > 5.7%" had a sensitivity of 0.81 (SD, 0.10), a specificity of 0.83 (SD, 0.03), and a likelihood ratio of 4.82 (SD, 1.03) for T2DM development.

CONCLUSIONS

Continuous glucose monitoring system allows for a better T2DM risk-development categorization than fasting glucose and HbA_1c in a high-risk population. Continuous glucose monitoring system-derived phenotyping reveals clinical differences, not disclosed by conventional fasting plasma glucose/HbA_1c categorization. These differences may correlate with distinct pathophysiological mechanisms.

Association of lower body mass index with increased glycemic variability in patients with newly diagnosed type 2 diabetes: a cross-sectional study in China

Previous studies have indicated that the pathogenesis of diabetes differs between obese and lean patients. We investigated whether newly diagnosed Chinese diabetic patients with different body mass indices (BMIs) have different glycemic variability, and we assessed the relationship between BMI and glycemic variability. This was a cross-sectional study that included 169 newly diagnosed and drug-naïve type 2 diabetic patients (mean age, 51.33 ± 9.83 years; 110 men). The clinical factors and results of the 75-g oral glucose tolerance test were all recorded. Glycemic variability was assessed using continuous glucose monitoring. Compared with overweight or obese patients (BMI ≥ 24 kg/m2), underweight or normal-weight patients (BMI < 24 kg/m2) had higher levels of blood glucose fluctuation parameters, particularly in terms of mean amplitude of glycemic excursion (MAGE 6.64 ± 2.38 vs. 5.67 ± 2.05; P = 0.007) and postprandial glucose excursions (PPGEs) (PPGE at breakfast, 7.72 ± 2.79 vs. 6.79 ± 2.40, P = 0.028; PPGE at lunch, 5.53 ± 2.70 vs. 5.07 ± 2.40, P = 0.285; PPGE at dinner, 5.96 ± 2.24 vs. 4.87 ± 2.50, P = 0.008). BMI was negatively correlated with glycemic variability (r = −0.243, P = 0.002). On multiple linear regression analyses, BMI (β = −0.231, P = 0.013) and Insulin Secretion Sensitivity Index-2 (β = −0.204, P = 0.048) were two independent predictors of glycemic variability. In conclusion, lower BMI was associated with increased glycemic variability, characterized by elevated PPGEs, in newly diagnosed Chinese type 2 diabetic patients.

The effect of diurnal distribution of carbohydrates and fat on glycaemic control in humans: a randomized controlled trial

Diurnal carbohydrate and fat distribution modulates glycaemic control in rodents. In humans, the optimal timing of both macronutrients and its effects on glycaemic control after prolonged consumption are not studied in detail. In this cross-over trial, 29 non-obese men were randomized to two four-week diets: (1) carbohydrate-rich meals until 13.30 and fat-rich meals between 16.30 and 22.00 (HC/HF) versus (2) inverse sequence of meals (HF/HC). After each trial period two meal tolerance tests were performed, at 09.00 and 15.40, respectively, according to the previous intervention. On the HF/HC diet, whole-day glucose level was increased by 7.9% (p = 0.026) in subjects with impaired fasting glucose and/or impaired glucose tolerance (IFG/IGT, n = 11), and GLP-1 by 10.2% (p = 0.041) in normal glucose-tolerant subjects (NGT, n = 18). Diet effects on fasting GLP-1 (p = 0.009) and PYY (p = 0.034) levels were observed in IFG/IGT, but not in NGT. Afternoon decline of glucose tolerance was more pronounced in IFG/IGT and associated with a stronger decrease of postprandial GLP-1 and PYY levels, but not with changes of cortisol rhythm. In conclusion, the HF/HC diet shows an unfavourable effect on glycaemic control in IFG/IGT, but not in NGT subjects. Consequently, large, carbohydrate-rich dinners should be avoided, primarily by subjects with impaired glucose metabolism.

Glucose time series complexity as a predictor of type 2 diabetes

BACKGROUND

Complexity analysis of glucose profile may provide valuable information about the gluco-regulatory system. We hypothesized that a complexity metric (detrended fluctuation analysis, DFA) may have a prognostic value for the development of type 2 diabetes in patients at risk.

METHODS

A total of 206 patients with any of the following risk factors (1) essential hypertension, (2) obesity or (3) a first-degree relative with a diagnosis of diabetes were included in a survival analysis study for a diagnosis of new onset type 2 diabetes. At inclusion, a glucometry by means of a Continuous Glucose Monitoring System was performed, and DFA was calculated for a 24-h glucose time series. Patients were then followed up every 6 months, controlling for the development of diabetes.

RESULTS

In a median follow-up of 18 months, there were 18 new cases of diabetes (58.5 cases/1000 patient-years). DFA was a significant predictor for the development of diabetes, with ten events in the highest quartile versus one in the lowest (log-rank test chi2 = 9, df = 1, p = 0.003), even after adjusting for other relevant clinical and biochemical variables. In a Cox model, the risk of diabetes development increased 2.8 times for every 0.1 DFA units. In a multivariate analysis, only fasting glucose, HbA_1c and DFA emerged as significant factors.

CONCLUSIONS

Detrended fluctuation analysis significantly performed as a harbinger of type 2 diabetes development in a high-risk population. Complexity analysis may help in targeting patients who could be candidates for intensified treatment. Copyright © 2016 The Authors. Diabetes/Metabolism Research and Reviews Published by John Wiley & Sons Ltd.

Effects of sitagliptin as initial therapy in newly diagnosed elderly type 2 diabetics: A randomized controlled study

The objective of this study was to investigate the characteristics of blood glycemic excursion, incretins and pancreatic hormone secretion in elderly people with newly diagnosed type 2 diabetes mellitus (T2DM) and to study the effects of sitagliptin on glycemic excursion in these subjects. A total of 129 newly diagnosed T2DM patients were enrolled in the study from March 2012 to August 2013. Clinical data, serum incretin, pancreatic hormone and continuous glucose monitoring data were collected. Among these subjects, elderly patients (NEDM) randomly received metformin combined with sitagliptin phosphate or glimepiride for 24 weeks. The blood glucose, glycosylated hemoglobin A_1c (GHbA_1c), serum incretins and pancreatic hormone levels were determined. During the oral glucose tolerance test (OGTT), 30 min insulin and C-peptide levels, 120 min insulin levels and ratio of the increases of insulin and blood glucose levels after 30 min of sugar loading (∆Ins30/∆Glu30) were significantly lower in elderly patients than in middle-aged patients (P<0.05). In addition, the glucagon elevation at 30 min was higher and the glucagon-like peptide-1 (GLP-1) at 30 min was lower in the elderly patients (P<0.05). Glucose excursion indices, including the standard deviation of the average blood glucose, intraday mean average glucose excursions (MAGE), and mean of daily differences (MODD), were significantly higher in the elderly patients (P<0.05). During the OGTT, insulin, C-peptide and ∆Ins30/∆Glu30 results at 30 min and GLP-1 levels at 120 min in NEDM subjects were significantly increased (P<0.05) and glucagon levels at 30 min was significantly lower after sitagliptin treatment (P<0.05) compared with glimepiride. Moreover, MAGE and MODD were significantly lower in the sitagliptin group after treatment compared to those in the glimepiride group (P<0.05). No severe hypoglycemia or cardiovascular diseases were observed. Strong blood glucose excursions occur in elderly patients with newly diagnosed T2DM. Sitagliptin phosphate combined with metformin effectively and safely improves glycemic excursion and carbohydrate metabolism in NEDM patients by promoting the first phase of insulin and incretin secretion and inhibiting glucagon secretion of.

Glycemic Variability Is Associated with Markers of Vascular Stress in Adolescents

OBJECTIVES

We used continuous glucose monitoring to test the hypothesis that mean amplitude of glycemic excursions (MAGE) is associated with circulating markers of oxidative and vascular stress in adolescents with habitually low physical activity classified as healthy weight, healthy obese, or obese with type 2 diabetes mellitus (T2DM).

STUDY DESIGN

A group of 13- to 21-year-olds (healthy weight = 12, healthy obese = 10, T2DM = 12) wore a continuous glucose monitor and step activity monitor for 5 days.

RESULTS

Physical activity was similar among groups (6551 ± 401 steps/d), but aerobic fitness (peak rate of oxygen consumption) was lower (P < .05) in T2DM (15.6 ± 1.8 mL/kg/min) than either healthy weight (26.2 ± 2.2) or healthy obese (24.4 ± 2.5). MAGE (mg/dL) was higher (P < .01) in T2DM (82 ± 10) vs healthy obese (33 ± 3) and healthy weight (30 ± 3). Average glucose followed a similar pattern as MAGE. Oxidized low density lipoprotein was higher (P < .05) in T2DM (70.3 ± 5.0 U/L) and healthy obese (58.1 ± 3.8) than healthy weight (48.4 ± 2) and positively correlated with MAGE (r = 0.77). Other stress markers that were both elevated in T2DM and correlated with MAGE included E-selectin (r = 0.50), intercellular adhesion molecule 1 (r = 0.35), and C-reactive protein (r = 0.52); soluble receptor for advanced glycosylation end product was lower in T2DM and inversely correlated with MAGE (r = -0.38).

CONCLUSIONS

MAGE is highest in obese youth with T2DM. The associations between MAGE and oxidative stress markers support the proposed contribution of glycemic variability to risk for future cardiovascular disease.