'Glycaemic variability': a new therapeutic challenge in diabetes and the critical care setting

Fasting plasma glucose variability and all-cause mortality among type 2 diabetes patients: a dynamic cohort study in Shanghai, China

The study aims to examine whether the variation of fasting plasma glucose (FPG), represented by coefficient of variation (CV), independently predicts all-cause mortality among Chinese type 2 diabetes patients. This retrospective cohort study was designed based on a standardized electronic management system of diabetes patients in Shanghai, China. 8871 type 2 diabetes patients were enrolled between 1 January 2007 and 31 December 2007 and were followed-up for all-cause mortality until 31 December 2014. All patients were grouped by the quartiles of CV of FPG. 1136 patients deceased during following-up. After adjusting for other risk factors, CV of FPG was not independently associated with all-cause mortality. Stratified analysis by mean FPG levels (<7 mmol/L and ≥7 mmol/L) observed a significant modifying effect of CV of FPG (P for interact test <0.01). CV of FPG was independently associated with all-cause mortality in patients whose glucose control was poor, with the HRs (95% CI) for the second, third, fourth vs first quartiles of CV of FPG being 1.23(0.94–1.61), 1.23(0.94–1.61), and 1.63(1.25–2.13), respectively. Our results suggest that variability of FPG may be an important predictor of mortality among type 2 diabetes in China, particularly for those with their glycemic status uncontrolled.

Visit-to-visit variation of fasting plasma glucose is a predictor of hip fracture in older persons with type 2 diabetes: the Taiwan Diabetes Study

We investigated the association between fasting plasma glucose variability (FPG-CV) and the risk of hip fracture in elderly diabetic patients. Our finding showed a temporal association between FPG-CV and hip fracture as patients categorized as FPG-CV greater than 25.4 % showed an increased risk in hip fractures.

INTRODUCTION

Hip fracture is a major health burden in the population and is associated with high rates of mortality and morbidity especially in elderly. It is evident that diabetes mellitus is a risk factor of osteoporosis which is a significant risk factor of hip fracture. However, epidemiological studies exploring the risks of hip fracture among type 2 diabetic patients are limited.

METHODS

A retrospective study of 26,501 ethnic Chinese older persons enrolled in the National Diabetes Care Management program in Taiwan was conducted; related factors were analyzed with extended Cox proportional hazards regression models to competing risk data on hip fracture incidence.

RESULTS

The results show a temporal association between FPG-CV and hip fracture as patients categorized as FPG-CV greater than 25.4 % showed an increased risk in hip fractures, confirming a linear relationship between the two. After multivariate adjustment, the risk of hip fracture increased among patients with FPG-CV of 25.4-42.3 % and >42.3 % compared with patients with FPG-CV of ≦ 14.3 % (hazard ratio, 1.35; 95 % confidence interval 1.14-1.60 and 1.27; 1.07-1.52, respectively). Significant linear trends among various FPG-CV were observed.

CONCLUSIONS

Thus, the present study demonstrated the importance of glucose stability for fracture prevention in older persons with type 2 diabetes. Future studies should be conducted to explore whether reduction in glucose oscillation in older adults with diabetes mellitus can reduce the risk of hip fracture.

Association of variability in hemoglobin A1c with cardiovascular diseases and mortality in Chinese patients with type 2 diabetes mellitus - A retrospective population-based cohort study

AIMS

This study aimed to investigate the association between variability in HbA1c and incidence of cardiovascular disease (CVD) event and mortality among Chinese primary care patients with Type 2 diabetes mellitus (T2DM).

METHODS

A retrospective cohort study was conducted on 91,866 T2DM patients aged ≥18years without any history of CVD. Variability in HbA1c, was measured by standard deviation (SD), associated with the risks of CVD and all-cause mortality were evaluated using Cox proportional hazards regression analysis by age groups ( 65 and ≥ 65 years old)." to "Variability in HbA1c was measured by standard deviation (SD) The association between Variability in HbA1c and the incidence of CVD and all-cause mortality were evaluated using Cox proportional hazards regression analysis by age groups ( 65 and ≥ 65 years old).

RESULTS

Over a median follow-up of 58.5months, our study identified a positive linear relationship between variability in HbA1c and incidence of CVD and all-cause mortality in the younger and older groups. For every 1-SD increase in HbA1c, the risk of CVD events in the older group only increased by 15.2% (95% CI: 1.026-1.293), and the risks of all-cause mortality in both age groups increased by 49.5% (95% CI: 1.154-1.936) and 77.8% (95% CI: 1.563-2.024), respectively.

CONCLUSIONS

The HbA1c variability independently of the mean HbA1c level may provide additional valuable information as a potential predictor for the development of CVD and all-cause mortality in diabetic patients, particularly for the elderly patients.

miR-1273g-3p participates in acute glucose fluctuation-induced autophagy, dysfunction, and proliferation attenuation in human umbilical vein endothelial cells

Acute glucose fluctuations (AGF) often cause high mortality among critically ill patients, but the mechanisms induced by AGF are not clear. Recent studies suggest that endothelial dysfunction is a key factor that leads to high mortality among critically ill patients. Our goal is to evaluate the phenomenon and mechanisms of endothelial dysfunction induced by AGF. In this study, the functions of human umbilical vein endothelial cells (HUVECs) were compared after treatment with sustained high glucose (SHG), AGF in two groups (AGF1 fluctuations between 5 and 16 mM and AGF2 fluctuations between 5 and 25 mM), and normal glucose levels as a control group (CTR). The medium of the groups was changed every 4 h. The influence of AGF on wound healing was also tested on C57BL/6 mice. The results show that cell proliferation, angiogenesis, and migration functions were injured in the SHG and both AGF groups. AGF2 group shows the worse condition in vitro. In vivo, the wound healing was delayed after the AGF treatment. Furthermore, the markers of apoptosis and autophagy were analyzed. We observed that the autophagy changed in all treatment groups, but apoptosis showed no change. To get to know the mechanism of dysfunction and autophagy, we performed the microRNA chip assay and real-time PCR and found miR-1273g-3p remarkably changed in AGF2 group. After the mimic and inhibitor of miR-1273g-3p were transfected during the AGF2 treatment, we found that the dysfunction and autophagy were partially enhanced by miR-1273g-3p mimic and reversed by miR-1273g-3p inhibitor in AGF2 group. Thus, we conclude that AGF can induce more dysfunction and autophagy, and miR-1273g-3p is also an important factor that leads to the injury.

Insulin Pump Therapy Is Associated with Lower Rates of Retinopathy and Peripheral Nerve Abnormality

OBJECTIVE

To compare rates of microvascular complications in adolescents with type 1 diabetes treated with continuous subcutaneous insulin infusion (CSII) versus multiple daily injections (MDI).

RESEARCH DESIGN AND METHODS

Prospective cohort of 989 patients (aged 12-20 years; diabetes duration >5 years) treated with CSII or MDI for >12 months. Microvascular complications were assessed from 2000-14: early retinopathy (seven-field fundal photography), peripheral nerve function (thermal and vibration threshold testing), autonomic nerve abnormality (heart rate variability analysis of electrocardiogram recordings) and albuminuria (albumin creatinine ratio/timed overnight albumin excretion). Generalized estimating equations (GEE) were used to examine the relationship between treatment and complications rates, adjusting for socio-economic status (SES) and known risk factors including HbA1c and diabetes duration.

RESULTS

Comparing CSII with MDI: HbA1C was 8.6% [70mmol/mol] vs. 8.7% [72 mmol/mol]) (p = 0.7), retinopathy 17% vs. 22% (p = 0.06); microalbuminuria 1% vs. 4% (p = 0.07), peripheral nerve abnormality 27% vs. 33% (p = 0.108) and autonomic nerve abnormality 24% vs. 28% (p = 0.401). In multivariable GEE, CSII use was associated with lower rates of retinopathy (OR 0.66, 95% CI 0.45-0.95, p = 0.029) and peripheral nerve abnormality (OR 0.63, 95% CI 0.42-0.95, p = 0.026), but not albuminuria (OR 0.46, 95% CI 0.10-2.17, p = 0.33). SES was not associated with any of the complication outcomes.

CONCLUSIONS

In adolescents, CSII use is associated with lower rates of retinopathy and peripheral nerve abnormality, suggesting an apparent benefit of CSII over MDI independent of glycemic control or SES.

Effect of glucose variability on pathways associated with glucotoxicity in diabetes: Evaluation of a novel in vitro experimental approach

AIMS

Glycaemic variability (GV) has been hypothesized to increase the risk of diabetes complications; however, results of clinical studies are contradictory. The effect of GV on cell phenotypes has been investigated in vitro showing that GV may have more deleterious effect on cells that high glucose itself. However, methodology used to study GV in vitro differs significantly between studies and does not reflect in vivo situation. Therefore we aimed to establish clinically relevant an in vitro experimental approach for the study of GV that reflects intra-day glucose fluctuations of subjects with type 1 diabetes mellitus (T1DM) and of healthy subjects and to test how low and high GV affect expression of genes that protects cells from hyperglycaemia-induced damage.

METHODS

Human umbilical vein endothelial cells (HUVEC) were cultured 24h in medium with different glucose profiles: high GV, low GV and GV of healthy subjects-profiles created according to CGM of T1DM patients and healthy subjects. These profiles were compared to commonly used 5.5 and 25mmol/l glucose concentrations. Gene expression was determined using quantitative PCR.

RESULTS

Our results showed general down-regulation of enzymes that are involved in the protection against hyperglycaemia-induced intracellular changes in both low and high GV compared to normal glycaemia similarly to the decrease induced by continuous hyperglycaemia. Gene expressions did not differ between high and low GV.

CONCLUSION

Our data indicate that GV may have similar or even greater effect than continuous hyperglycaemia on the expression of several genes relevant to pathogenesis of diabetes microvascular complications.

Association of the average rate of change in HbA1c with severe adverse events: a longitudinal evaluation of audit data from the Bavarian Disease Management Program for patients with type 2 diabetes mellitus

AIMS/HYPOTHESIS

In patients with type 2 diabetes mellitus, the effects of HbA1c variability on macrovascular events remain uncertain. The present investigation evaluates the association of HbA1c variability with non-fatal cardiovascular events, emergency admissions and episodes of severe hypoglycaemia in a cohort of patients newly started on insulin therapy.

METHODS

HbA1c variability was defined as the rate of change in values between observations. The medical records of 406,356 patients enrolled in a disease management programme for type 2 diabetes mellitus were analysed to identify a cohort of 13,777 patients with observed transition to insulin therapy. The cohort was observed for a period of at least 5 years. Cox regression models were applied to quantify the association of HbA1c variability with the events of interest.

RESULTS

The models reveal a significant non-linear association between HbA1c variability and the risk of experiencing myocardial infarction, stroke and hypoglycaemia. The lowest risk is seen with a variability of approximately 0.5% (5.5 mmol/mol) per quarter. Using Cox models to predict survival curves for the cohort with hypothetical HbA1c variability of 0.5% (5.5 mmol/mol) and 1.5% (16.4 mmol/mol) per quarter, the proportion experiencing myocardial infarction within 2 years increases significantly from 1% to 10%. The proportion experiencing stroke increases from 1% to 29%, hypoglycaemia from 2% to 24% and the risk of emergency admission from 2% to 21%.

CONCLUSIONS/INTERPRETATION

In patients newly started on insulin therapy, rapid and higher HbA1c variability is associated with an increased risk of myocardial infarction, stroke, severe hypoglycaemia and emergency admission.

Long-term Glycemic Variability and Risk of Adverse Outcomes: A Systematic Review and Meta-analysis

OBJECTIVE

Glycemic variability is emerging as a measure of glycemic control, which may be a reliable predictor of complications. This systematic review and meta-analysis evaluates the association between HbA1c variability and micro- and macrovascular complications and mortality in type 1 and type 2 diabetes.

RESEARCH DESIGN AND METHODS

Medline and Embase were searched (2004-2015) for studies describing associations between HbA1c variability and adverse outcomes in patients with type 1 and type 2 diabetes. Data extraction was performed independently by two reviewers. Random-effects meta-analysis was performed with stratification according to the measure of HbA1c variability, method of analysis, and diabetes type.

RESULTS

Seven studies evaluated HbA1c variability among patients with type 1 diabetes and showed an association of HbA1c variability with renal disease (risk ratio 1.56 [95% CI 1.08-2.25], two studies), cardiovascular events (1.98 [1.39-2.82]), and retinopathy (2.11 [1.54-2.89]). Thirteen studies evaluated HbA1c variability among patients with type 2 diabetes. Higher HbA1c variability was associated with higher risk of renal disease (1.34 [1.15-1.57], two studies), macrovascular events (1.21 [1.06-1.38]), ulceration/gangrene (1.50 [1.06-2.12]), cardiovascular disease (1.27 [1.15-1.40]), and mortality (1.34 [1.18-1.53]). Most studies were retrospective with lack of adjustment for potential confounders, and inconsistency existed in the definition of HbA1c variability.

CONCLUSIONS

HbA1c variability was positively associated with micro- and macrovascular complications and mortality independently of the HbA1c level and might play a future role in clinical risk assessment.

How well do glucose variability measures predict patient glycaemic outcomes during treatment intensification in type 2 diabetes?

AIM

Despite links to clinical outcomes in patients with type 2 diabetes mellitus (T2DM), the clinical utility of glycaemic variability (GV) measures is unknown. We evaluated the correlation between baseline GV, and glycated haemoglobin (HbA1c) attainment and hypoglycaemic events during treatment intensification in a large group of patients.

METHODS

Patient-level data from six 24-week clinical trials of T2DM patients undergoing treatment intensification with basal insulin or comparators (N = 1699) were pooled. Baseline GV measures included standard deviation (SD), mean amplitude of glycaemic excursions (MAGE), mean absolute glucose (MAG), coefficient of variation (CV), high blood glucose index (HBGI), and low blood glucose index (LBGI) and were correlated with HbA1c change and hypoglycaemic events.

RESULTS

All mean GV measures, excluding CV which worsened, improved significantly from baseline to Week 24, with the largest proportional reduction obtained for HBGI (-65.5%). When assessed as mean individual percentage changes, only HBGI improved significantly. Baseline GV correlated positively with Week 24 HbA1c for SD, MAGE, and HBGI. Baseline HBGI and CV correlated negatively and positively, respectively, with Week 24 HbA1c change. Correlations also existed between most baseline GV measures and age, body mass index, Week 24 fasting plasma glucose, Week 24 postprandial plasma glucose, and hypoglycaemic events; statistical significance depended on the specific measure.

CONCLUSIONS

Pre-treatment GV is associated with glycaemic outcomes in T2DM patients undergoing treatment intensification over 24 weeks. HBGI might be the most robust predictor, warranting validation in dedicated prospective studies or randomized trials to assess the predictive value of measuring GV.

Association between hemoglobin A1c variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes

AIMS

We examined the association between hemoglobin A1c (HbA1c) variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes.

METHODS

We used the multidetector coronary computed tomography data collected from subjects with type 2 diabetes who did not have a history of cardiovascular disease or angina symptoms. HbA1c measurements preceding the date of cardiac imaging were retrospectively collected, and intraindividual SD (HbA1c-SD), CV and adjusted SD of HbA1c measurements were calculated. Subclinical coronary atherosclerosis was defined as calcium score >400 without any cardiac symptoms.

RESULTS

A total of 595 subjects were categorized according to the median value of each HbA1c variability indicators. The prevalence of subclinical coronary atherosclerosis was higher in higher HbA1c variability group compared with lower HbA1c variability group. Multivariable logistic regression analysis showed that higher HbA1c-SD and -CV were associated with the presence of subclinical coronary atherosclerosis, independent of mean HbA1c level in subjects with diabetes duration ≤10 years (OR [95% CI]; HbA1c-SD, 2.894 [1.105-7.584]; HbA1c-CV, 2.540 [1.022-6.316]).

CONCLUSIONS

Long-term stabilization of blood glucose level might be important in preventing subclinical coronary atherosclerosis in subjects with earlier period of type 2 diabetes.

Data-Driven Personalized Feedback to Patients with Type 1 Diabetes: A Randomized Trial

BACKGROUND

A mobile phone-based application can be useful for patients with type 1 diabetes in managing their disease. This results in large datasets accumulated on the patient's devices, which can be used for individualized feedback. The effect of such feedback is investigated in this article.

MATERIALS AND METHODS

We developed an application that included a data-driven feedback module known as Diastat for patients on self-measured blood glucose regimens. Using a stepped-wedge design, both groups initially received an application without Diastat. Group 1 activated Diastat after 4 weeks, whereas Group 2 activated Diastat 12 weeks after startup (T1). End points were glycated hemoglobin (HbA1c) level and number of out-of-range (OOR) measurements (i.e., outside the range 72-270 mg/dL).

RESULTS

Thirty patients were recruited to the study, and 15 were assigned to each group after the initial meeting. There were no significant differences between groups at T1 in HbA1c or OOR events. Overall, all patients had a decrease of 0.6 percentage points in mean HbA1c (P < 0.001) and 14.5 in median OOR events over 2 weeks (P < 0.001).

CONCLUSIONS

The study does not provide evidence that data-driven feedback improves glycemic control. The decrease in HbA1c was sizeable and significant, even though the study was not powered to detect this. The overall improvement in glycemic control suggests that, in general, mobile phone-based interventions can be useful in diabetes self-management.

Saxagliptin is similar in glycaemic variability more effective in metabolic control than acarbose in aged type 2 diabetes inadequately controlled with metformin

This study compared the effects on glycaemic variability and glucose control between saxagliptin and acarbose as add-on therapies for aged T2DM inadequately controlled with metformin alone. The results showed that compared with acarbose-metformin, saxagliptin-metformin was more effective in glucose control with similar glycaemic variability.

Epigenetic mechanisms of endothelial dysfunction in type 2 diabetes

The development of type-2 diabetes mellitus (T2DM) and its complications is largely due to the complex interaction between genetic factors and environmental influences, mainly dietary habits and lifestyle, which can either accelerate or slow down disease progression. Recent findings suggest the potential involvement of epigenetic mechanisms as a crucial interface between the effects of genetic predisposition and environmental factors. The common denominator of environmental factors promoting T2DM development and progression is that they trigger an inflammatory response, promoting inflammation-mediated insulin resistance and endothelial dysfunction. Proinflammatory stimuli, including hyperglycemia, oxidative stress, and other inflammatory mediators, can affect epigenetic mechanisms, altering the expression of specific genes in target cells without changes in underlying DNA sequences. DNA methylation and post-translational histone modifications (PTHMs) are the most extensively investigated epigenetic mechanisms. Over the past few years, non-coding RNA, including microRNAs (miRNAs), have also emerged as key players in gene expression modulation. MiRNAs can be actively released or shed by cells in the bloodstream and taken up in active form by receiving cells, acting as efficient systemic communication tools. The miRNAs involved in modulation of inflammatory pathways (inflammamiRs), such as miR-146a, and those highly expressed in endothelial lineages and hematopoietic progenitor cells (angiomiRs), such as miR-126, are the most extensively studied circulating miRNAs in T2DM. However, data on circulating miRNA signatures associated with specific diabetic complications are still lacking. Since immune cells and endothelial cells are primarily involved in the vascular complications of T2DM, their relative contribution to circulating miRNA signatures needs to be elucidated. An integrated approach encompassing different epigenetic mechanisms would have the potential to provide new mechanistic insights into the genesis of diabetes and its severe vascular complications and identify a panel of epigenetic markers with diagnostic/prognostic and therapeutic relevance.

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

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

How well do glucose variability measures predict patient glycaemic outcomes during treatment intensification in type 2 diabetes?

AIM

Despite links to clinical outcomes in patients with type 2 diabetes mellitus (T2DM), the clinical utility of glycaemic variability (GV) measures is unknown. We evaluated the correlation between baseline GV, and glycated haemoglobin (HbA1c) attainment and hypoglycaemic events during treatment intensification in a large group of patients.

METHODS

Patient-level data from six 24-week clinical trials of T2DM patients undergoing treatment intensification with basal insulin or comparators (N=1699) were pooled. Baseline GV measures included standard deviation (SD), mean amplitude of glycaemic excursions (MAGE), mean absolute glucose (MAG), coefficient of variation (CV), high blood glucose index (HBGI), and low blood glucose index (LBGI) were correlated with HbA1c change and hypoglycaemic events.

RESULTS

All mean GV measures, excluding CV which worsened, improved significantly from baseline to Week 24, with the largest proportional reduction obtained for HBGI (-65.5%). When assessed as mean individual percentage changes only HBGI improved significantly. Baseline GV correlated positively with Week 24 HbA1c for SD, MAGE, and HBGI. Baseline HBGI and CV correlated negatively and positively, respectively, with Week 24 HbA1c change. Correlations also existed between most baseline GV measures and age, body mass index, Week 24 fasting plasma glucose, Week 24 postprandial plasma glucose, and hypoglycaemic events; statistical significance depended on the specific measure.

CONCLUSIONS

Pre-treatment GV is associated with glycaemic outcomes in T2DM patients undergoing treatment intensification over 24 weeks. HBGI might be the most robust predictor, warranting validation in dedicated prospective studies or randomized trials to assess the predictive value of measuring GV.

DPP-4 inhibitors: pharmacological differences and their clinical implications

INTRODUCTION

Recently, incretin-based therapy was introduced for the treatment of type 2 diabetes (T2D). In particular, dipeptidyl peptidase-4 inhibitors (DPP-4i) (sitagliptin, vildagliptin, saxagliptin, linagliptin and alogliptin) play an increasing role in the management of T2D.

AREAS COVERED

An extensive literature search was performed to analyze the pharmacological characteristics of DPP-4i and their clinical implications.

EXPERT OPINION

DPP-4i present significant pharmacokinetic differences. They also differ in chemical structure, in the interaction with distinct subsites of the enzyme and in different levels of selectivity and potency of enzyme inhibition. Moreover, disparities in the effects on glycated hemoglobin, glucagon-like peptide-1 and glucagon levels and on glucose variability have been observed. However, indirect comparisons indicate that all DPP-4i have a similar safety and efficacy profiles. DPP-4i are preferred in overweight/obese and elderly patients because of the advantages of minimal or no influence on weight gain and low risk of hypoglycemia. For the same reasons, DPP-4i can be safely combined with insulin. However, currently cardiovascular outcomes related to DPP-4i are widely debated and the available evidence is controversial. Today, long-term studies are still in progress and upcoming results will allow us to better define the strengths and limits of this therapeutic class.

The combined effect of visit-to-visit variability in HbA1c and systolic blood pressure on the incidence of cardiovascular events in patients with type 2 diabetes

OBJECTIVE

To investigate the association between long-term visit-to-visit variability in glycated hemoglobin (HbA1c) and systolic blood pressure (SBP) and the incidence of cardiovascular disease (CVD) in patients with type 2 diabetes.

METHODS

We retrospectively enrolled 632 patients with type 2 diabetes and no history of CVD who first visited our hospital between 1995 and 1996, were followed-up for ≥1 year, attended at least 4 clinic visits and had at least 1 visit per year. Patients were followed until June 2012 at the latest, and mailed questionnaires.

RESULTS

During the median follow-up period (15.4 years), 81 patients developed CVD. Multivariate analysis revealed that the coefficient of variation (CV) and the variation independent of mean (VIM) for HbA1c and SBP were significant predictors of CVD incidence independent of mean HbA1c and SBP. Patients were classified into 4 groups by median HbA1cCV and SBPCV values and by median HbA1cVIM and SBPVIM values. Among these groups, the HRs were highest in the high-HbA1cCV/high-SBPCV and high-HbA1cVIM/high-SBPVIM groups and were significantly higher compared with those in the low-HbA1cCV/low-SBPCV and low-HbA1cVIM/low-SBPVIM groups, respectively. Among patients with mean SBP≥130 mm Hg, the HRs associated with HbA1cCV and HbA1cVIM were drastically elevated compared with those with mean SBP<130 mm Hg (interaction p<0.05).

CONCLUSIONS

Long-term visit-to-visit variability in HbA1c and SBP represented a combined and additive risk for CVD incidence in patients with type 2 diabetes. It is suggested that a synergistic effect exists between HbA1c variability and mean SBP levels for CVD incidence.

Diet and glycaemia: the markers and their meaning. A report of the Unilever Nutrition Workshop

Consumption of carbohydrate-containing foods leads to transient postprandial rises in blood glucose concentrations that vary between food types. Higher postprandial glycaemic exposures have particularly been implicated in the development of chronic cardiometabolic diseases. Reducing such diet-related exposures may be beneficial not only for diabetic patients but also for the general population. A variety of markers have been used to track different aspects of glycaemic exposures, with most of the relevant knowledge derived from diabetic patients. The assessment of glycaemic exposures among the non-diabetic population may require other, more sensitive markers. The present report summarises key messages of presentations and related discussions from a workshop organised by Unilever intended to consider currently applied markers of glycaemic exposure. The particular focus of the meeting was to identify the potential applicability of glycaemic exposure markers for studying dietary effects in the non-diabetic population. Workshop participants concluded that markers of glycaemic exposures are sparsely used in intervention studies among non-diabetic populations. Continuous glucose monitoring remains the optimal approach to directly assess glycaemic exposure. Markers of glycaemic exposure such as glycated Hb, fructosamine, glycated albumin, 1,5-anhydroglucitol and advanced glycation end products can be preferred dependent on the aspect of interest (period of exposure and glucose variability). For all the markers of glycaemia, the responsiveness to interventions will probably be smaller among the non-diabetic than among the diabetic population. Further validation and acceptance of existing glycaemic exposure markers applied among the non-diabetic population would aid food innovation and better design of dietary interventions targeting glycaemic exposure.

A very low-carbohydrate, low-saturated fat diet for type 2 diabetes management: a randomized trial

OBJECTIVE

To comprehensively compare the effects of a very low-carbohydrate, high-unsaturated/low-saturated fat diet (LC) with those of a high-unrefined carbohydrate, low-fat diet (HC) on glycemic control and cardiovascular disease (CVD) risk factors in type 2 diabetes (T2DM).

RESEARCH DESIGN AND METHODS

Obese adults (n = 115, BMI 34.4 ± 4.2 kg/m(2), age 58 ± 7 years) with T2DM were randomized to a hypocaloric LC diet (14% carbohydrate [<50 g/day], 28% protein, and 58% fat [<10% saturated fat]) or an energy-matched HC diet (53% carbohydrate, 17% protein, and 30% fat [<10% saturated fat]) combined with structured exercise for 24 weeks. The outcomes measured were as follows: glycosylated hemoglobin (HbA1c), glycemic variability (GV; assessed by 48-h continuous glucose monitoring), antiglycemic medication changes (antiglycemic medication effects score [MES]), and blood lipids and pressure.

RESULTS

A total of 93 participants completed 24 weeks. Both groups achieved similar completion rates (LC 79%, HC 82%) and weight loss (LC -12.0 ± 6.3 kg, HC -11.5 ± 5.5 kg); P ≥ 0.50. Blood pressure (-9.8/-7.3 ± 11.6/6.8 mmHg), fasting blood glucose (-1.4 ± 2.3 mmol/L), and LDL cholesterol (-0.3 ± 0.6 mmol/L) decreased, with no diet effect (P ≥ 0.10). LC achieved greater reductions in triglycerides (-0.5 ± 0.5 vs. -0.1 ± 0.5 mmol/L), MES (-0.5 ± 0.5 vs. -0.2 ± 0.5), and GV indices; P ≤ 0.03. LC induced greater HbA1c reductions (-2.6 ± 1.0% [-28.4 ± 10.9 mmol/mol] vs. -1.9 ± 1.2% [-20.8 ± 13.1 mmol/mol]; P = 0.002) and HDL cholesterol (HDL-C) increases (0.2 ± 0.3 vs. 0.05 ± 0.2 mmol/L; P = 0.007) in participants with the respective baseline values HbA1c >7.8% (62 mmol/mol) and HDL-C <1.29 mmol/L.

CONCLUSIONS

Both diets achieved substantial improvements for several clinical glycemic control and CVD risk markers. These improvements and reductions in GV and antiglycemic medication requirements were greatest with the LC compared with HC. This suggests an LC diet with low saturated fat may be an effective dietary approach for T2DM management if effects are sustained beyond 24 weeks.

Visit-to-visit variability of fasting plasma glucose as predictor of ischemic stroke: competing risk analysis in a national cohort of Taiwan Diabetes Study

BACKGROUND

Glycemic variation as an independent predictor of ischemic stroke in type 2 diabetic patients remains unclear. This study examined visit-to-visit variations in fasting plasma glucose (FPG), as represented by the coefficient of variation (CV), for predicting ischemic stroke independently, regardless of glycated hemoglobin (HbA1c) and other conventional risk factors in such patients.

METHODS

Type 2 diabetic patients enrolled in the National Diabetes Care Management Program, ≥30 years old and free of ischemic stroke (n = 28,354) in 2002 to 2004 were included, and related factors were analyzed with extended Cox proportional hazards regression models of competing risk data on stroke incidence.

RESULTS

After an average 7.5 years of follow-up, there were 2,250 incident cases of ischemic stroke, giving a crude incidence rate of 10.56/1,000 person-years (11.64 for men, 9.63 for women). After multivariate adjustment, hazard ratios for the second, third and fourth versus first FPG-CV quartile were 1.11 (0.98, 1.25), 1.22 (1.08, 1.38) and 1.27 (1.12, 1.43), respectively, without considering HbA1c, and 1.09 (0.96, 1.23), 1.16 (1.03, 1.31) and 1.17 (1.03, 1.32), respectively, after considering HbA1c.

CONCLUSIONS

Besides HbA1c, FPG-CV was a potent predictor of ischemic stroke in type 2 diabetic patients, suggesting that different therapeutic strategies now in use be rated for their potential to (1) minimize glucose fluctuations and (2) reduce HbA1c level in type 2 diabetic patients to prevent ischemic stroke.

Impact of visit-to-visit glycemic variability on the risks of macrovascular and microvascular events and all-cause mortality in type 2 diabetes: the ADVANCE trial

OBJECTIVE

There is no consensus on the importance of visit-to-visit glycemic variability in diabetes. Therefore, we assessed the effects of visit-to-visit variability (VVV) in HbA1c and fasting glucose on major outcomes in the ADVANCE (Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation) trial.

RESEARCH DESIGN AND METHODS

ADVANCE was a factorial randomized controlled trial of intensive glucose control and blood pressure lowering in patients with type 2 diabetes. VVV in the intensive glucose treatment group was defined using the SD of five measurements of HbA1c and glucose taken 3-24 months after randomization. Outcomes were combined macro- and microvascular events and all-cause mortality occurring post 24 months. Sensitivity analyses were performed using other indices of variability and in the standard glucose treatment group.

RESULTS

Among 4,399 patients in the intensive group, an increase in VVV of HbA1c was associated with an increased risk of vascular events (P = 0.01) and with mortality (P < 0.001): highest versus lowest tenth hazard ratio (95% CI) 1.64 (1.05-2.55) and 3.31 (1.57-6.98), respectively, after multivariable adjustment. A clear association was also observed between VVV of fasting glucose and increased risk of vascular events (P < 0.001; 2.70 [1.65-4.42]). HbA1c variability was positively associated with the risk of macrovascular events (P = 0.02 for trend), whereas glucose variability was associated with both macro- and microvascular events (P = 0.005 and P < 0.001 for trend, respectively). Sensitivity analyses using other indices, and patients in the standard glucose treatment group, were broadly consistent with these results.

CONCLUSIONS

Consistency of glycemic control is important to reduce the risks of vascular events and death in type 2 diabetes.

Comparison of continuous subcutaneous insulin infusion and insulin glargine-based multiple daily insulin aspart injections with preferential adjustment of basal insulin in patients with type 2 diabetes

The purpose of this study was to evaluate and compare multiple daily injection (MDI) therapy of bolus insulin aspart and basal insulin glargine with continuous subcutaneous insulin infusion (CSII) with aspart in patients with type 2 diabetes mellitus (T2DM). It was assessed whether MDI was capable of controlling glycemic index with a higher efficacy than CSII by preferential adjustment of basal insulin with a lower total daily insulin dosage in T2DM. Two hundred patients with T2DM were enrolled in the study and randomly assigned to CSII (n=100) and MDI (n=100; aspart immediately prior to each meal and glargine at bedtime) groups for 12 weeks of therapy. During the last week of each treatment period, the subjects wore a continuous glucose monitoring system for 2–3 days. The dosage of basal insulin was preferentially adjusted to control prior-meal blood glucose levels, and the characteristics of insulin dosage were analyzed. No statistically significant differences were observed between the two groups in hemoglobin A1c (HbA1c), which dropped from 10–11% prior to therapy to 7–7.5% after 12 weeks. After 12 weeks, good glycemic level control was achieved in all patients in the MDI and CSII groups. A statistically significant difference in the dose of insulin between the CSII and MDI groups was observed (P<0.001). In conclusion, no significant differences were found between the two therapies in the incidence of hypoglycemia and HbA1c for the 12 weeks. The basal insulin dosage was significantly decreased in the MDI group compared with that in the CSII group, but the CSII group was superior to MDI group in decreasing fasting blood glucose and shortening the time required for hypoglycemia to meet the targeted level.

Oscillating high glucose enhances oxidative stress and apoptosis in human coronary artery endothelial cells

PURPOSE

To investigate the toxic effect of oscillating high glucose (OHG) versus persistent high glucose (PHG) in inducing oxidative stress and cellular apoptosis in human coronary artery endothelial cells (HCAECs) in vitro.

METHODS

HCAECs were incubated for 72 h continuously in normal glucose (5.5 mmol/L glucose), PHG (25 mmol/L glucose), OHG (5.5 mmol and 25 glucose mmol/L alternating every 6 h) and mannitol, respectively. Cellular viability, concentration of oxidative stress biomarkers (MDA and GSH) in the supernatants of cell culture, and intracellular ROS level were quantitated after exposure to different concentrations of glucose for a total 72 h. Apoptosis of HCAECs cultured with various glucose levels was evaluated by annexin V-FITC and PI staining followed by analysis with flow cytometry. The expressions of HO-1 and Nrf2 were measured by RT-qPCR and Western blotting at the end of the experiment.

RESULTS

HCAECs cultured with PHG showed decreased cellular viability compared to those with normal level of glucose (p < 0.05). The decrease was more pronounced under OHG condition (p < 0.05). Cellular oxidative stress was provoked in HCAECs exposed to PHG with marked increased MDA level, reduced GSH concentration and elevated ROS production (p < 0.05). The stress was further amplified in the setting of OHG (p < 0.05). The cellular apoptosis was enhanced by culturing with PHG, and to a greater extent when incubated with OHG. Both expressions of HO-1 and Nrf2 were suppressed in HCAECs in persistent hyperglycemia condition, while the inhibition was more intense in the fluctuating hyperglycemia condition (p < 0.05).

CONCLUSIONS

These findings indicate that OHG could be more detrimental to HCAECs than PHG. This is probably due to the enhancement of oxidative stress and cellular apoptosis induced by frequent glucose swings through the inhibition of Nrf2/HO-1 pathway.

Effects of sitagliptin or mitiglinide as an add-on to acarbose on daily blood glucose fluctuations measured by 72 h subcutaneous continuous glucose monitoring in Japanese patients with type 2 diabetes: a prospective randomized study

OBJECTIVE

Postprandial hyperglycemia and blood glucose fluctuations increase the risk of macroangiopathy in patients with type 2 diabetes mellitus (T2DM). However, few studies have examined the effects of oral hypoglycemic drugs on blood glucose fluctuations in daily life.

METHODS

Twenty-nine T2DM patients treated with acarbose were randomized to receive either sitagliptin (14 patients) or mitiglinide (15 patients) together with acarbose for 4 weeks. Patients were then switched to a combination of 10 mg mitiglinide and 0.2 mg voglibose for 4 weeks. All patients wore a continuous glucose monitoring (CGM) device for 5 - 7 days in week 3 of each treatment period.

RESULTS

The percentage of blood glucose levels in the hyperglycemic range, blood glucose indices derived from 24-h CGM profiles and the glycemic parameters (HbA1c, glycated albumin and fasting plasma glucose) were significantly improved by adding sitagliptin or mitiglinide to ongoing acarbose therapy. These parameters also tended to improve in the mitiglinide/voglibose combination period.

CONCLUSION

Daily blood glucose fluctuations were significantly improved by adding sitagliptin or mitiglinide to acarbose, and improved after switching to the mitiglinide/voglibose combination. Larger controlled studies are needed to verify the effects of adding sitagliptin or mitiglinide to acarbose on glucose fluctuations.

Glycemic variability in patients with early type 2 diabetes: the impact of improvement in β-cell function

OBJECTIVE Increased glycemic variability has been reported to be associated with the risk of hypoglycemia and possibly diabetes complications and is believed to be due to β-cell dysfunction. However, it is not known whether improvement in β-cell function can reduce glycemic variability. Because short-term intensive insulin therapy (IIT) can improve β-cell function in early type 2 diabetes (T2DM), our objective was to determine whether the β-cell functional recovery induced by this therapy is associated with decreased glycemic variability. RESEARCH DESIGN AND METHODS Sixty-one patients with T2DM of 3.0 years mean duration underwent 4 weeks of IIT, which consisted of basal insulin detemir and premeal insulin aspart. Glucose variability was assessed in both the first and the last week by the coefficient of variation of capillary glucose on daily 6-point self-monitoring profiles. β-Cell function before and after IIT was assessed with the Insulin Secretion-Sensitivity Index-2 (ISSI-2). RESULTS Between the first and the last week on IIT, 55.7% of patients had a reduction in glucose variability. Change in glucose variability was negatively correlated with the change in β-cell function (ISSI-2) (r = -0.34, P = 0.008). On multiple linear regression analyses, percentage change in ISSI-2 emerged as the only factor independently associated with the change in glucose variability (standardized β = -0.42, P = 0.03). Moreover, patients with an increase in ISSI-2 ≥25% experienced a reduction in glucose variability compared with their peers who had almost no change (-0.041 ± 0.06 vs. -0.0002 ± 0.04, respectively; P = 0.006). CONCLUSIONS In early T2DM, glycemic variability is a modifiable parameter that can be reduced by improving β-cell function with short-term IIT.

Hyperglycemia following recovery from hypoglycemia worsens endothelial damage and thrombosis activation in type 1 diabetes and in healthy controls

BACKGROUND AND AIMS

Hypoglycemia produces thrombosis activation, but little attention has been paid to the effects of hyperglycemia following recovery from hypoglycemia on thrombosis activation.

METHODS AND RESULTS

In both twenty-two healthy subjects and twenty-one matched persons with type 1 diabetes, recovery from a 2-h induced hypoglycemia was obtained by reaching normo-glycemia or hyperglycemia for another 2 h. After this, normal glycemia was maintained for the following 6 h. Hyperglycemia after hypoglycemia was also repeated with the concomitant infusion of vitamin C. In both controls and people with diabetes, the recovery with normo-glycemia was accompanied by a significant improvement of Von Willebrand factor (vWF), prothrombin fragment 1 + 2 (F1 + 2), thrombin-antithrombin III-complexes (TAT), P-selectin, plasminogen activator inhibitor-1 (PAI-1), nitrotyrosine and 8-iso-prostaglandin F2α (8-iso-PGF2α) (p < 0.01 vs hypoglycemia for all the parameters), all directly affected by hypoglycemia itself (p < 0.01 vs baseline for all the parameters). On the contrary, the recovery with hyperglycemia after hypoglycemia worsens all these parameters (p < 0.01 vs normoglycemia for all the parameters), an effect persisting even after the additional 6 h of normo-glycemia. The effect of hyperglycemia following hypoglycemia was partially counterbalanced when vitamin C was infused (p < 0.01 vs hyperglycemia alone for all the parameters), suggesting that hyperglycemia following hypoglycemia may activate thrombosis through the oxidative stress production.

CONCLUSION

This study shows that, in type 1 diabetes as well as in controls, the way in which recovery from hypoglycemia takes place could play an important role in favoring the activation of thrombosis and oxidative stress, widely recognized cardiovascular risk factors.

Feasibility of closed-loop insulin delivery in type 2 diabetes: a randomized controlled study

OBJECTIVE

Closed-loop insulin delivery offers a promising treatment option, but to date, it has only been evaluated in type 1 diabetes. Our aim was to evaluate the feasibility of fully closed-loop subcutaneous insulin delivery in insulin-naïve patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

Twelve subjects (seven males, age 57.2 years, BMI 30.5 kg/m2) with noninsulin-treated type 2 diabetes (HbA1c 8.4% [68 mmol/mol], diabetes duration 7.6 years) underwent two 24-h visits (closed-loop and control) in a randomized crossover design. During closed-loop visits, the subjects' routine diabetes therapy was replaced with model predictive control algorithm-driven subcutaneous insulin pump delivery based on real-time continuous glucose monitoring. Meals were unannounced, and no additional insulin was administered for carbohydrates consumed. During control visits, the usual diabetes regimen was continued (metformin 92%, sulfonylureas 58%, dipeptidyl peptidase-4 inhibitors 33%). On both visits, subjects consumed matched 50- to 80-g carbohydrate meals and optional 15-g carbohydrate snacks and remained largely sedentary. Plasma glucose measurements evaluated closed-loop performance.

RESULTS

Compared with conventional therapy, 24 h of closed-loop insulin delivery increased overall the median time in target plasma glucose (3.9-8.0 mmol/L) from 24 to 40% (P = 0.016), despite sensor under-reading by a median of 1.2 mmol/L. The benefit of the closed-loop system was more prominent overnight, with greater time in target glucose (median 78 vs. 35%; P = 0.041) and less time in hyperglycemia (22 vs. 65%; P = 0.041). There was no hypoglycemia during either intervention.

CONCLUSIONS

A closed-loop system without meal announcement and using subcutaneous insulin delivery in insulin-naïve patients with type 2 diabetes appears feasible and safe. Improvement in postprandial glucose control may require further optimization of system performance.

The cytotoxic role of intermittent high glucose on apoptosis and cell viability in pancreatic beta cells

OBJECTIVES

Glucose fluctuations are both strong predictor of diabetic complications and crucial factor for beta cell damages. Here we investigated the effect of intermittent high glucose (IHG) on both cell apoptosis and proliferation activity in INS-1 cells and the potential mechanisms.

METHODS

Cells were treated with normal glucose (5.5 mmol/L), constant high glucose (CHG) (25 mmol/L), and IHG (rotation per 24 h in 11.1 or 25 mmol/L) for 7 days. Reactive oxygen species (ROS), xanthine oxidase (XOD) level, apoptosis, cell viability, cell cycle, and expression of cyclinD1, p21, p27, and Skp2 were determined.

RESULTS

We found that IHG induced more significant apoptosis than CHG and normal glucose; intracellular ROS and XOD levels were more markedly increased in cells exposed to IHG. Cells treated with IHG showed significant decreased cell viability and increased cell proportion in G0/G1 phase. Cell cycle related proteins such as cyclinD1 and Skp2 were decreased significantly, but expressions of p27 and p21 were increased markedly.

CONCLUSIONS

This study suggested that IHG plays a more toxic effect including both apoptosis-inducing and antiproliferative effects on INS-1 cells. Excessive activation of cellular stress and regulation of cyclins might be potential mechanism of impairment in INS-1 cells induced by IHG.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Glycemic variability is an independent predictive factor for development of hepatic fibrosis in nonalcoholic fatty liver disease

Patients with nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) often have metabolic disorders including insulin resistance and type 2 diabetes mellitus (T2DM). We clarified the predictive factors in glucose metabolism for progression of hepatic fibrosis in patients with NAFLD by the 75-g oral glucose tolerance test (75gOGTT) and a continuous glucose monitoring system (CGMS). One hundred sixty-nine patients (68 female and 101 male patients) with biopsy-proven NAFLD with performance with 75gOGTT were enrolled and divided into four groups according to the stage of hepatic fibrosis (F0–3). The proportion of patients with T2DM significantly gradually increased, HbA1c and the homeostasis model assessment of insulin resistance were significantly elevated, and 1,5-anhydroglucitol (1,5-AG) was remarkably decreased with the progression of fibrosis. In the 75gOGTT, both plasma glucose and insulin secretion were remarkably increased with the progression of fibrosis. The only factor significantly associated with advanced fibrosis was 1,5-AG (P = 0.008) as determined by multivariate logistic regression analysis. We next evaluated the changes in blood glucose during 24 hours by monitoring with the CGMS to confirm the relationship between glycemic variability and progression of fibrosis. Variability of median glucose, standard deviation of median glucose (P = 0.0022), maximum blood glucose (P = 0.0019), and ΔMin–max blood glucose (P = 0.0029) were remarkably higher in severe fibrosis than in mild fibrosis.

Conclusion

Hyperinsulinemia and hyperglycemia, especially glycemic variability, are important predictive factors in glucose impairment for the progression of hepatic fibrosis in NAFLD.

Risks of diabetic nephropathy with variation in hemoglobin A1c and fasting plasma glucose

BACKGROUND

This study examined whether annual variation in glycosylated hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG), as represented by the coefficient of variation (CV), can predict diabetic nephropathy independently of mean FPG, mean HbA1c, and other risk factors in patients with type 2 diabetes.

METHODS

A computerized database of patients with type 2 diabetes aged ≥30 years and free of diabetic nephropathy (n = 3220) who were enrolled in the Diabetes Care Management Program of China Medical University Hospital before 2007 was used in a time-dependent Cox proportional hazards regression model.

RESULTS

The incidence rates of diabetic nephropathy were 16.11, 22.95, and 28.86 per 1000 person-years in the first, second, and third tertiles of baseline HbA1c-CV, respectively; the corresponding incidence rates for FPG-CV were 9.46, 21.23, and 37.51 per 1000 person-years, respectively. After multivariate adjustment, the corresponding hazard ratios for the second and third tertiles versus the first tertile of annual HbA1c-CV were 1.18 (95% confidence interval [CI], 0.88-1.58) and 1.58 (95% CI, 1.19-2.11), respectively, and 1.55 (95% CI, 0.99-2.41) and 4.75 (95% CI, 3.22-7.01) for FPG-CV, respectively. The risks of diabetic nephropathy for HbA1c-CV and FPG-CV stratified according to age, gender, renal function, and hypertension status were provided.

CONCLUSIONS

Annual FPG and HbA1c variations have a strong association with diabetic nephropathy in patients with type 2 diabetes. Whether intervention for reducing glucose variation should be administered needs to be examined in a future study.

Biological variation of cardiovascular risk factors in patients with diabetes

Biological variation refers to the natural fluctuations found when repeated measurements are made in a biological system. Generally, biological variation remains within narrow boundaries in health, but may differ in pathological states, with implications for the diagnosis and monitoring of disease processes. In disease, biological variation may alter such that any subsequent measurement may need to have a greater difference compared with a healthy control to be biologically relevant. Treatments such as insulin or anti-hypertensive therapy have been shown to reduce biological variability closer to normal levels and theoretically this may help prevent complication development or progression in conditions such as diabetes. This article reviews how biological variation can influence our identification and assessment of vascular risk factors in a person with diabetes. The role of biological variation in the diagnosis of diabetes (glucose and HbA1c) is then examined. Finally, the influence that common treatments in diabetes have in modifying biological variation is described.

Do data in the literature indicate that glycaemic variability is a clinical problem? Glycaemic variability and vascular complications of diabetes

In recent years glycaemic variability (GV) has emerged as a determinant of vascular complications of both type 1 and type 2 diabetes mellitus. In type 1 diabetes analysis of data of GV show conflicting results on both micro- and macro-vascular complications. In non-diabetic subjects blood glucose after loading is a stronger predictor of cardiovascular complications than fasting glucose. In type 2 diabetes both coefficient of variation of fasting blood glucose and postprandial blood glucose predict cardiovascular events. Also, long term variability of HbA1c has been associated predominantly with diabetic nephropathy, less frequently with retinopathy. Intervention trials to evaluate the effect of postprandial glucose have been conducted only in prediabetes or in type 2 diabetes and the data are not conclusive. In vitro and in vivo data have shown the mechanisms that are at the basis of the adverse cardiovascular effects of GV, mainly associated with oxidative stress; the atherogenic action of postprandial glucose also involves insulin sensitivity, postprandial increase in serum lipids and glycaemic index of food. Thus, correction of GV emerges as a target to be pursued in clinical practice in order to safely reduce mean blood glucose (and thus glycated haemoglobin) and for its direct effects on vascular complications of diabetes.

Effects of nateglinide and acarbose on glycemic excursions in standardized carbohydrate and mixed-meal tests in drug-naïve type 2 diabetic patients

The aim of this study was to compare the effects of nateglinide and acarbose on glycemic excursions and postprandial glucose profiles with different types of meals (standardized carbohydrate and mixed meals) in drug-naïve type 2 diabetic patients. A randomized, parallel-group prospective design clinical trial was conducted and a total of 39 drug-naïve patients (16 males and 23 females, aged 56.7±10.2 years) were enrolled. The patients were randomly divided into group A [nateglinide 120 mg three times daily (t.i.d.), n=19] and group B (acarbose 50 mg t.i.d., n=20). The standardized carbohydrate and mixed-meal tests were performed at baseline and at the end of study. Continuous glucose monitoring system (CGMS) data were recorded. Various parameters that measure glucose variability were derived from the CGMS data. In the standardized carbohydrate meal tests, the postprandial glucose excursions (PPGEs) were significantly decreased in the two groups after 12 weeks of treatment (P<0.05), whereas the decrease was more prominent in the acarbose compared to the nateglinide group (P=0.138). In the mixed-meal tests, the mean sensor glucose values [24-h mean blood glucose (MBG)] were significantly decreased in the two groups after 12 weeks of treatment (P<0.05) and the parameters of glucose excursions, including standardized deviation (SD), largest amplitude of glycemic excursion (LAGE), mean of daily differences (MODD) and mean amplitude of glycemic excursion (MAGE), were reduced in the two groups. However, the decreases in SD and LAGE in the nateglinide group were statistically significant, whereas in the acarbose group only the decreases in LAGE were statistically significant. The efficiency of nateglinide or acarbose in lowering postprandial 120-min hyperglycemia were similar in the standardized carbohydrate meal test. However, acarbose was more efficient in lowering postprandial 30- and 60-min hyperglycemia (P<0.05) compared to nateglinide. The fasting and postprandial total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) had a tendency to decrease from the baseline after 12 weeks of treatment with nateglinide, whereas fasting and postprandial high-density lipoprotein cholesterol (HDL-C) had a tendency to increase. Acarbose did not affect the fasting or postprandial lipid profiles after 12 weeks of treatment (P>0.05). In conclusion, nateglinide and acarbose effectively improved postprandial glycemic control, although acarbose was shown to be more efficient in controlling early (30 and 60 min) postprandial glucose excursions in the carbohydrate meal test, whereas nateglinide was shown to be superior to acarbose in controlling postprandial glucose excursions in the mixed-meal test.

Variability of glucose-lowering effect as a limiting factor in optimizing basal insulin therapy: a review

Lowering blood glucose with insulin therapy towards beneficial target levels while also avoiding hypoglycaemia is a challenging task. An important confounding factor, which might be under-appreciated in this scenario, is that of variable glucose readings causing difficulties with dose adjustment. Furthermore, this glucose variability is, to some extent, a reflection of variability in the glucose-lowering action of the insulin therapy itself. Not only is glucose variability a major confounding factor in disease management but it is possibly also of direct prognostic consequence and is increasingly recognized as an informative measurement in diabetes management. The scope for insulin-induced glucose variability is particularly great with basal insulins because of their prolonged absorption from high-dose depots. Pharmacodynamic (PD) variability manifests as both fluctuations in the level of glucose-lowering effect over time, and as inconsistencies in the response from one injection to another. Well-controlled pharmacokinetic (PK)/PD studies using repeated isoglycaemic clamp methodology clearly how that many injected basal insulin products have high variable absorption with correspondingly variable action. Incomplete resuspension and precipitation appear to be important issues with regard to unpredictability in this action, while an inadequate duration of action relative to the dosing interval results in a fluctuating action profile. There are some ultra-long-acting basal insulins with novel protraction mechanisms currently in clinical development for which clamp studies show markedly improved PK/PD profiles.

Glycemic variability: Clinical implications

Glycemic control and its benefits in preventing microvascular diabetic complications are convincingly proved by various prospective trials. Diabetes control and complications trial (DCCT) had reported variable glycated hemoglobin (HbA1C) as a cause of increased microvascular complications in conventional glycemic control group versus intensive one. However, in spite of several indirect evidences, its link with cardiovascular events or macrovascular complications is still not proved. Glycemic variability (GV) is one more tool to explain relation between hyperglycemia and increased cardiovascular risk in diabetic patients. In fact GV along with fasting blood sugar, postprandial blood sugar, HbA1C, and quality of life has been proposed to form glycemic pentad, which needs to be considered in diabetes management. Postprandial spikes in blood glucose as well as hypoglycemic events, both are blamed for increased cardiovascular events in Type 2 diabetics. GV includes both these events and hence minimizing GV can prevent future cardiovascular events. Modern diabetes management modalities including improved sulfonylureas, glucagon like peptide-1 (GLP-1)-based therapy, newer basal insulins, and modern insulin pumps address the issue of GV effectively. This article highlights mechanism, clinical implications, and measures to control GV in clinical practice.

Effect of vildagliptin on glucose and insulin concentrations during a 24-hour period in type 2 diabetes patients with different ranges of baseline hemoglobin A1c levels

BACKGROUND

Currently, it is still unknown whether differences in glycemic control have any effect on glucose and insulin kinetics after vildagliptin administration. The aim of this study was to evaluate the effect of vildagliptin on glucose and insulin concentrations during a 24-h period in type 2 diabetes patients with different ranges of baseline hemoglobin A1c (A1C) levels.

PATIENTS AND METHODS

A randomized, double-blind, crossover, placebo-controlled clinical trial was carried out in 12 drug-naive adult volunteers with type 2 diabetes and overweight or obesity. Subjects had fasting glucose values between 7.2 and 13.3 mmol/L. Six patients had A1C between 7.0% and 8.4% (Group A), and the remaining subjects had A1C between 8.5% and 10.0% (Group B). Patients received oral administration of vildagliptin (50 mg twice daily) or placebo in a crossover manner for two consecutive days. Until the second day of the interventions, glucose and insulin concentrations were measured every hour during a 24-h period, and areas under the curve (AUCs) were calculated. Statistical analyses were evaluated with Wilcoxon and Mann-Whitney U tests.

RESULTS

There were significant decreases in glucose concentrations after vildagliptin administration in both groups when comparing placebo in all measurements throughout the 24-h period and in the AUC. There were no significant changes in insulin concentration in both groups after vildagliptin administration when comparing placebo in all measurements throughout the 24-h period and in the AUC.

CONCLUSIONS

Vildagliptin administration improved glucose control during a 24-h period in type 2 diabetes patients, independent of the basal A1C level, without changes in insulin levels.

Association between glucose variability as assessed by continuous glucose monitoring (CGM) and diabetic retinopathy in type 1 and type 2 diabetes

There is a growing debate in the literature on whether glucose variability contributes, as well as high HbA1c levels and longstanding diabetes, to the onset and progression of diabetic retinopathy (DR) in patients with diabetes types 1 (DM1) and 2 (DM2). Few data, obtained only by self-monitoring of blood glucose, support this hypothesis. We used continuous glucose monitoring (CGM) to investigate the association between DR and glucose variability parameters (SD, CONGA 2, MAGE), acute hyperglycemia (HBGI) and chronic exposure to glucose (AG and AUC tot). We studied 68 patients from 19 to 69 years old, 35 with DM1 and 33 with DM2. The prevalence of retinopathy was 43 % in DM 1 patients and 39 % in DM 2 patients. The values of all indicators were obtained by CGM for 72 h. DR was diagnosed on direct or indirect ophthalmoscopic examination, after inducing mydriasis with tropicamide. HbA1c was measured at the baseline and 6 weeks after CGM to test the stability of the patients' glycemic control. Univariate analysis showed a close association between DR and duration of diabetes (OR 1.11; 1.04-1.19), intensive insulin therapy (OR 5.6, CI 1.14-27.30), SD (OR 1.03; CI 1.01-1.06) and CONGA 2 (OR 1.02; CI 1.00-1.04)-both indicators of variability and HBGI (OR 1.1, CI 1.01-1.18)-a parameter reflecting acute hyperglycemia. There was no significant correlation with HbA1c (p = 0.070). Multivariate regression analysis showed that disease duration is the parameter most significantly correlating with DR (OR 1.05; 1.01-1.15). These results reinforce the evidence that longstanding disease is the factor most closely associated with DR. Our data also suggest, however, that glucose variability-regardless of HbA1c-may also have a role as a risk factor for DR, particularly in the case of acute fluctuations (as represented by CONGA 2 and SD) and acute hyperglycemia (as represented by HBGI).

Model-driven diabetes care: study protocol for a randomized controlled trial

Background

People with type 1 diabetes who use electronic self-help tools register a large amount of information about their disease on their participating devices; however, this information is rarely utilized beyond the immediate investigation. We have developed a diabetes diary for mobile phones and a statistics-based feedback module, which we have named Diastat, to give data-driven feedback to the patient based on their own data.

Method

In this study, up to 40 participants will be given a smartphone on which is loaded a diabetes self-help application (app), the Few Touch Application (FTA). Participants will be randomized into two groups to be given access to Diastat 4 or 12 weeks, respectively after receiving the smartphone, and will use the FTA with Diastat for 8 weeks after this point. The primary endpoint is the frequency of high and low blood-glucose measurements.

Discussion

The study will investigate the effect of data-driven feedback to patients. Our hypothesis is that this will improve glycemic control and reduce variability. The endpoints are robust indicators that can be assembled with minimal effort by the patient beyond normal routine.

Trial registration

Clinicaltrials.gov: NCT01774149

Glycemic variability in hospitalized patients: choosing metrics while awaiting the evidence

Hyperglycemia, hypoglycemia, preexisting diabetes, and glycemic variability each may affect hospital outcomes. Observational findings derived from randomized trials or retrospective studies suggest that independent of hypoglycemia and hyperglycemia, a relationship exists between variability and hospital outcomes. A review of studies conducted in diverse hospital populations is reported here, showing a relationship between measures of variability and nonglycemic outcomes, including ICU and hospital mortality and length of stay. "Glycemic variability" has an intuitive meaning, understood as a propensity of a single patient to develop repeated episodes of excursions of BG over a relatively short period of time that exceed the amplitude expected in normal physiology. It is proposed that each of 3 dimensions of variability should be separately studied: (1) magnitude of glycemic excursions during intervals of relative stability of the moving average of BG, (2) frequency with which a critical magnitude of excursion is exceeded, and (3) presence or absence of fine tuning. Multiple hospital studies have found that the standard deviation (SD) of the data set of blood glucose values (BG) of individual patients predicts outcomes. An appropriate refinement would be to report the "Reverse-transformed group mean of the SD of the logarithmically transformed BG data set of each patient," with confidence intervals. In logarithmic space, group means of the SD of BGs of each patient may be compared, using an appropriate parametric test. Upon reverse transformation, the upper and lower bounds of the confidence intervals become asymmetric about the reverse-transformed group mean of the SD. There is a need to understand what patterns of dispersion of BG over time are captured by SD as a predictor of outcomes. Among the causes of high SD, a subgroup may consist of patients having frequent oscillations of BG. Another subgroup may consist of patients experiencing a major change of overall glycemia during the timeframe of data collection. Appropriate metrics should be developed to recognize both variability in the sense of recurrent large oscillations of BG, and separately to recognize any time-dependent change of overall glycemia during hospitalization. Especially in relation to uncontrolled diabetes, there is a need to know whether rapid correction of chronic hyperglycemia adversely affects hospital outcomes. We have some understanding of how to control or prevent change of overall glycemia, and less understanding of how to control variability. Each may be associated with outcomes, and each may be detected by a high SD, but it remains uncertain whether intervention to prevent either pattern of changing glycemia would affect outcomes.

Comparison of a multiple daily insulin injection regimen (glargine or detemir once daily plus prandial insulin aspart) and continuous subcutaneous insulin infusion (aspart) in short-term intensive insulin therapy for poorly controlled type 2 diabetes patients

Aims. To examine the potential differences between multiple daily injection (MDI) regimens based on new long-acting insulin analogues (glargine or detemir) plus prandial insulin aspart and continuous subcutaneous insulin aspart infusion (CSII) in patients with poorly controlled type 2 diabetes. Methods. Patients (n = 119) with poorly controlled type 2 diabetes of a duration exceeding five years were randomly assigned into three groups: Group A treated with CSII using insulin aspart; Group B treated with glargine-based MDI and Group C treated with detemir-based MDI. Results. Good glycemic control was achieved by patients in Group A in a significantly shorter duration than patients in Groups B and C. Total daily insulin, basal insulin dose and dose per kg body weight in Group A were significantly less than those in Groups B and C. Daily blood glucose fluctuation in Group A was significantly less than that in Groups B and C. There were no differences between Groups B and C. Conclusions. Aspart-based CSII may achieve good blood glucose control with less insulin doses over a shorter period compared with glargine or detemir-based MDI. No differences between glargine- and detemir-based MDI were detected in poorly controlled subjects with type 2 diabetes.

Mobile phone-based pattern recognition and data analysis for patients with type 1 diabetes

BACKGROUND

Persons with type 1 diabetes who use electronic self-help tools, most commonly blood glucose meters, record a large amount of data about their personal condition. Mobile phones are powerful and ubiquitous computers that have a potential for data analysis, and the purpose of this study is to explore how self-gathered data can help users improve their blood glucose management.

SUBJECTS AND METHODS

Thirty patients with insulin-regulated type 1 diabetes were equipped with a mobile phone application for 3-6 months, recording blood glucose, insulin, dietary information, physical activity, and disease symptoms. The data were analyzed in terms of usage of the different modules and which data processing and visualization tools could be constructed to support the use of these data.

RESULTS

Eighteen patients (denoted "adopters") recorded complete data for over 80 consecutive days, up to 247 days. Among those who withdrew or did not use the application extensively, the most common reasons given were outdated or difficult-to-use phone. Data analysis using period finding and scale-space trends was found to yield significant patterns for most adopters. Pattern recognition methods to predict low or high blood glucose were found to be performing poorly.

CONCLUSIONS

Minimally intrusive mobile applications enable users with type 1 diabetes to record data that can provide data-driven feedback to the user, potentially providing relevant insight into their disease.

Quality of life and technology: impact on children and families with diabetes

Ensuring quality of life (QOL) while maintaining glycemic control within targets is an important challenge in type 1 and type 2 diabetes treatment. For children with diabetes, QOL includes enjoying meals, feeling safe in school, and perceiving positive, supportive relationships with parents, siblings, and friends. Yet many treatment-related and psychosocial barriers can interfere with a child's QOL and their ability to manage diabetes effectively. Diabetes management also imposes considerable lifestyle demands that are difficult and often frustrating for children to negotiate at a young age. Recent advances in diabetes medications and technologies have improved glycemic control in children with diabetes. Two widely used technologies are the insulin pump and continuous glucose monitoring (CGM) system. These technologies provide patients with more flexibility in their daily life and information about glucose fluctuations. Several studies report improvements in glycemic control in children with type 1 diabetes using the insulin pump or sensor-augmented pump therapy. Importantly, these technologies may impact QOL for children and families with diabetes, although they are rarely used or studied in the treatment of children with type 2 diabetes. Further, emerging closed loop and web- and phone-based technologies have great potential for supporting diabetes self-management and perhaps QOL. A deeper understanding and appreciation of the impact of diabetes technology on children's and parents' QOL is critical for both the medical and psychological care of diabetes. Thus, the purpose of this review is to discuss the impact of new diabetes technologies on QOL in children, adolescents and families with type 1 diabetes.

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

Glucose variability has recently been investigated in diabetic patients in several studies, but most of them considered only a few variability indicators and did not systematically correlate them with patients' HbA1c levels and other important characteristics. In thus study, the correlations between HbA1c levels and metabolic control (average glucose, AG), glucose variability (SD, CONGA, MAGE, MODD, BG ROC), hyperglycemia (HBGI), hypoglycemia (LBGI) and postprandial (AUC PP) indices were investigated in patients with type 1 and type 2 diabetes. The study involved 68 patients divided into 3 groups as follows: 35 patients had type 1 diabetes (group 1); 17 had type 2 diabetes and were taking multiple daily injections (MDI) of insulin (group 2); and 16 patients had type 2 diabetes treated with OHA and/or basal insulin (group 3). The indicators were obtained over at least 48 h using a continuous glucose monitoring (CGM) system. HbA1c levels were measured at the baseline and after CGM. HbA1c correlated significantly with AG (r = 0.74), AUC PP (r = 0.69) and HBGI (r = 0.74), but only in type 1 diabetic patients. Patients with longstanding disease and type 1 diabetes had a greater glucose variability, irrespective of their HbA1c levels. Insulin therapy with MDI correlated strongly with HbA1c, but not with glucose variability. HbA1c levels identify states of sustained hyperglycemia and seem to be unaffected by hypoglycemic episodes or short-lived glucose spikes, consequently revealing shortcomings as a "gold standard" indicator of metabolic control. Glucose variability indicators describe the glucose profile of type 1 diabetic patients and identify any worsening glycemic control (typical of longstanding diabetes) more accurately than HbA1c tests.