Glucose variability; does it matter?

Evaluation of an open access software for calculating glucose variability parameters of a continuous glucose monitoring system applied at pediatric intensive care unit

Background

Continuous Glucose Monitoring (CGM) has become an increasingly investigated tool, especially with regards to monitoring of diabetic and critical care patients. The continuous glucose data allows the calculation of several glucose variability parameters, however, without specific application the interpretation of the results is time-consuming, utilizing extreme efforts. Our aim was to create an open access software [Glycemic Variability Analyzer Program (GVAP)], readily available to calculate the most common parameters of the glucose variability and to test its usability.

Methods

The GVAP was developed in MATLAB® 2010b environment. The calculated parameters were the following: average area above/below the target range (Avg. AUC-H/L); Percentage Spent Above/Below the Target Range (PATR/PBTR); Continuous Overall Net Glycemic Action (CONGA); Mean of Daily Differences (MODD); Mean Amplitude of Glycemic Excursions (MAGE). For verification purposes we selected 14 CGM curves of pediatric critical care patients. Medtronic® Guardian® Real-Time with Enlite® sensor was used. The reference values were obtained from Medtronic®^’s own software for Avg. AUC-H/L and PATR/PBTR, from GlyCulator for MODD and CONGA, and using manual calculation for MAGE.

Results

The Pearson and Spearman correlation coefficients were above 0.99 for all parameters. The initial execution took 30 minutes, for further analysis with the Windows® Standalone Application approximately 1 minute was needed.

Conclusions

The GVAP is a reliable open access program for analyzing different glycemic variability parameters, hence it could be a useful tool for the study of glycemic control among critically ill patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s12938-015-0035-3) contains supplementary material, which is available to authorized users.

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.

"Mild dysglycemia" in type 2 diabetes: to be neglected or not?

"Mild dysglycemia" in type 2 diabetes can be defined by the range of HbA1c levels≥6.5% (48 mmol/mol) and<7% (53 mmol/mol), which corresponds to when the risk for vascular complications begins to increase. This "mild dysglycemia" is characterized by both a dawn phenomenon (a spontaneous blood glucose rise in the early morning) and an excess of post-prandial glucose excursions in the absence of abnormal elevation in basal glucose, especially during nocturnal periods. This represents an intermediary stage between pre-diabetes (HbA1c≥5.7%, 39 mmol/mol, and<6.5%, 48 mmol/mol) and those who begin to show a steadily progressive worsening in basal glucose (HbA1c≥7%, 53 mmol/mol). Should this relatively minor intermediate dysglycemic phase deserve more attention, that is the question. The now available incretin-based therapies, and more specifically the DPP-4 inhibitors provide the clinician with the possibility to reduce or eradicate both the dawn phenomenon and post-meal glucose excursions with minimal side effects. The availability of 24-h glycemic profiles in those with "mild dysglycemia" will help to describe their individual glycemic phenotype, based on which the early and appropriate life style changes and/or pharmacological interventions can be introduced.

Optimal candidates for the switch from glimepiride to sitagliptin to reduce hypoglycemia in patients with type 2 diabetes mellitus

BACKGROUND

Sitagliptin is a novel antidiabetic agent with a low risk for hypoglycemia. We investigated the efficacy and safety of sitagliptin when patients switched from a sulfonylurea to sitagliptin and identified good candidates for the switch.

METHODS

Sixty-one patients with type 2 diabetes switched from glimepiride with metformin to sitagliptin with metformin due to clinical hypoglycemia. Serum glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), and 2-hour postprandial plasma glucose (2h-PPG) before and 12 and 24 weeks after the drug switch were checked.

RESULTS

HbA1c and FPG levels did not change 12 or 24 weeks after the switch; however, the 2h-PPG level decreased from 218.0±67.5 mg/dL at baseline to 197.1±69.9 mg/dL at 12 weeks and 192.3±67.4 mg/dL at 24 weeks after switching drugs (P=0.045, P=0.018, respectively). All but one patient no longer experienced hypoglycemia after discontinuing glimepiride. In a multivariate logistic regression analysis, a high homeostasis model assessment of insulin resistance and low baseline HbA1c level were independent predictors of an HbA1c ≤7% after switching to sitagliptin.

CONCLUSION

Glycemic control was not aggravated in patients 24 weeks after the drug switch, and symptomatic hypoglycemia decreased significantly. Patients with dominant insulin resistance may be good candidates for switching from a sulfonylurea to sitagliptin to reduce hypoglycemia.

Continuous glucose monitoring and its relationship to hemoglobin A1c and oral glucose tolerance testing in obese and prediabetic youth

CONTEXT

The optimal screening test for diabetes and prediabetes in obese youth is controversial.

OBJECTIVE

We examined whether glycosylated hemoglobin (HbA1c) or the oral glucose tolerance test (OGTT) is a better predictor of free-living glycemia as measured by continuous glucose monitoring (CGM).

DESIGN

This was a cross-sectional study of youth 10-18 years old, body mass index (BMI) 85th percentile or greater, with diabetes risk factors.

SETTING AND PARTICIPANTS

Participants (n = 118) with BMI 85th percentile or greater, not on medications for glucose management, were recruited from primary care and pediatric endocrinology clinics around Denver, Colorado.

INTERVENTION

HbA1c, fasting plasma glucose, and 2-hour glucose were collected and all participants wore a blinded CGM for 72 hours.

MAIN OUTCOME MEASURES

CGM outcomes were determined and descriptive statistics calculated. Performance characteristics at current American Diabetes Association cutpoints were compared with CGM outcomes.

RESULTS

CGM data were successfully collected on 98 obese youth. Those with prediabetes had significantly higher average glucose, area under the curve (AUC), peak glucose, and time greater than 120 and greater than 140 mg/dL (P < .01) on CGM than youth with normal HbA1c or OGTT. HbA1c had a greater magnitude of correlation to CGM average glucose, AUC, and minimum glucose; 2-hour glucose had a greater magnitude of correlation to CGM SD, peak glucose, and time greater than 140 and greater than 200 mg/dL. However, there were no overall differences in the strength comparisons between 2-hour glucose and HbA1c correlations to CGM outcomes.

CONCLUSIONS

In obese youth, HbA1c and 2-hour glucose performed equally well at predicting free-living glycemia on CGM, suggesting that both are valid tests for dysglycemia screening.

Glucose and triglyceride excursions following a standardized meal in individuals with diabetes: ELSA-Brasil study

Objective

To assess glucose and triglyceride excursions 2 hours after the ingestion of a standardized meal and their associations with clinical characteristics and cardiovascular complications in individuals with diabetes.

Research design and methods

Blood samples of 898 subjects with diabetes were collected at fasting and 2 hours after a meal containing 455 kcal, 14 g of saturated fat and 47 g of carbohydrates. Self-reported morbidity, socio-demographic characteristics and clinical measures were obtained by interview and exams performed at the baseline visit of the ELSA-Brasil cohort study.

Results

Median (interquartile range, IQR) for fasting glucose was 150.5 (123–198) mg/dL and for fasting triglycerides 140 (103–199) mg/dL. The median excursion for glucose was 45 (15–76) mg/dL and for triglycerides 26 (11–45) mg/dL. In multiple linear regression, a greater glucose excursion was associated with higher glycated hemoglobin (10.7, 95% CI 9.1–12.3 mg/dL), duration of diabetes (4.5; 2.6–6.4 mg/dL, per 5 year increase), insulin use (44.4; 31.7–57.1 mg/dL), and age (6.1; 2.5–9.6 mg/dL, per 10 year increase); and with lower body mass index (−5.6; −8.4– -2.8 mg/dL, per 5 kg/m² increase). In adjusted logistic regression models, a greater glucose excursion was marginally associated with the presence of cardiovascular comorbidities (coronary heart disease, myocardial infarction and angina) in those with obesity.

Conclusions

A greater postprandial glycemic response to a small meal was positively associated with indicators of a decreased capacity for insulin secretion and negatively associated with obesity. No pattern of response was observed with a greater postprandial triglyceride excursion.

Blood glucose self-monitoring patterns in Mexican Americans: further lessons from the Starr County Border Health Initiative

BACKGROUND

The purpose was to describe patterns of home self-monitoring of blood glucose (SMBG) in Mexican Americans with type 2 diabetes mellitus enrolled in a diabetes self-management education protocol. Research questions were as follows: (1) What were the patterns and rates of home glucose self-monitoring over the 6-month course of the study? (2) What were the differences in monitoring rates between experimental and control groups? (3) What were the relationships between rates of monitoring and glycosylated hemoglobin (A1C), gender, and years with diabetes?

SUBJECTS AND METHODS

We used a randomized (by group) repeated-measures pretest/posttest control group design. Glucometer data from an experimental group (diabetes self-management education plus nurse case management) and a comparison group (diabetes self-management education only) were analyzed. Data were collected at baseline and at 3 and 6 months.

RESULTS

Overall average SMBG rates were low. Experimental and control group monitoring levels were not significantly different. More females than males never monitored glucose values, but more females than males checked at least one time per week. Those participants who checked their glucose levels more than once per week had diabetes for a longer period of time. Rates of monitoring were not strongly associated with A1C levels at 3 and 6 months, but at 6 months A1C levels were statistically significantly different based on whether or not individuals monitored their glucose levels (P=0.03, n=71).

CONCLUSIONS

SMBG rates were low in this study despite SMBG education and access to free glucometers and test strips. The lower rates of SMBG may reflect the effects of unexpected environmental challenges, but exact causes remain unclear. Reasons for low rates of SMBG need to be explored further, especially in underserved communities.

Professional continuous glucose monitoring for the identification of type 1 diabetes mellitus among subjects with insulin therapy

The identification of type 1 diabetes in diabetic subjects receiving insulin therapy is sometimes difficult. The purpose of this study is to evaluate whether results of professional continuous glucose monitoring can improve the identification of type 1 diabetes.From 2007 to 2012, 119 adults receiving at least twice-daily insulin therapy and professional continuous glucose monitoring were recruited. Type 1 diabetes was diagnosed by endocrinologists according to American Diabetes Association standards, including a very low C-peptide level (<0.35  pg/mL) or the presence of diabetic ketoacidosis. Continuous glucose monitoring was applied for 3 days.Among 119 subjects, 86 were diagnosed with type 1 diabetes. Subjects with type 1 diabetes were younger (33.8 vs 52.3 years old, P < 0.001), had lower body mass index (BMI, 21.95 vs 24.42, P = 0.003), lower serum creatinine (61.77  vs 84.65 μmol/L, P = 0.001), and higher estimated glomerular filtration rate (108.71 vs 76.48 mg/mL/min/1.73m2, P < 0.001) than subjects with type 2 diabetes. Predictive scores for identification of type 1 diabetes were constructed, including age, BMI, average mean amplitude of glucose excursion in days 2 and 3, and the area under the curve of nocturnal hyperglycemic and hypoglycemic states. The area under the receiver operating characteristic curve was 0.90. With the cutoff of 0.58, the sensitivity was 86.7% and the specificity was 80.8%. The good performance was validated by the leave-one-out method (sensitivity 83.3%, specificity 73.1%).Professional continuous glucose monitoring is a useful tool that improves identification of type 1 diabetes among diabetic patients receiving insulin therapy.

Evaluating quality of glycemic control: graphical displays of hypo- and hyperglycemia, time in target range, and mean glucose

There is need for readily understandable graphical displays of glucose data to facilitate interpretation by clinicians and researchers. (1) Display of the percentage of glucose values above a specified threshold for hyperglycemia (%High) versus percentage of glucose values below a specified threshold for hypoglycemia (%Low). If all glucose values fell within the target range, then all data points would fall at the origin. (2) After an intervention, one can plot the change in percentage of glucose values above a specified threshold for hyperglycemia versus the change in percentage of glucose values below a specified threshold defining hypoglycemia: The quadrants of this graph correspond to (a) increased risk of both hyper- and hypoglycemia, (b) decreased hyperglycemia but increased risk of hypoglycemia, (c) decreases in both hypo- and hyperglycemia, and (d) decreased hypoglycemia but increased hyperglycemia. (3) A 2-dimensional triangular graph can be used for simultaneous display of %High, %Low, and percentage in target range. (4) Display of risk of hyper- versus risk of hypoglycemia based on both frequency and severity of departures from the target range can be used. (5) Graphs (1) and (4) can also be presented using percentile scores relative to a reference population. (6) It is also useful to analyze %Hypoglycemia or risk of hypoglycemia versus mean glucose. These methods are illustrated with examples from representative cases and shown to be feasible, practical, and informative. These new types of graphical displays can facilitate rapid analysis of risks of hypo- and hypoglycemia simultaneously and responses to therapeutic interventions for individuals or in clinical trials.

Four-Point Preprandial Self-Monitoring of Blood Glucose for the Assessment of Glycemic Control and Variability in Patients with Type 2 Diabetes Treated with Insulin and Vildagliptin

The study explored the utility of four-point preprandial glucose self-monitoring to calculate several indices of glycemic control and variability in a study adding the DPP-4 inhibitor vildagliptin to ongoing insulin therapy. This analysis utilized data from a double-blind, randomized, placebo-controlled crossover study in 29 patients with type 2 diabetes treated with vildagliptin or placebo on top of stable insulin dose. During two 4-week treatment periods, self-monitoring of plasma glucose was undertaken at 4 occasions every day. Glucose values were used to assess several indices of glycemic control quality, such as glucose mean, GRADE, M-VALUE, hypoglycemia and hyperglycemia index, and indices of glycemic variability, such as standard deviation, CONGA, J-INDEX, and MAGE. We found that vildagliptin improved the glycemic condition compared to placebo: mean glycemic levels, and both GRADE and M-VALUE, were reduced by vildagliptin (P < 0.01). Indices also showed that vildagliptin reduced glycemia without increasing the risk for hypoglycemia. Almost all indices of glycemic variability showed an improvement of the glycemic condition with vildagliptin (P < 0.02), though more marked differences were shown by the more complex indices. In conclusion, the study shows that four-sample preprandial glucose self-monitoring is sufficient to yield information on the vildagliptin effects on glycemic control and variability.

A comparison of continuous intravenous insulin and subcutaneous insulin among patients with type 2 diabetes and congestive heart failure exacerbation

BACKGROUND

The study aims to determine whether the route of insulin administration influences glycaemic variability and inflammatory or neurohormonal markers in patients with type 2 diabetes and congestive heart failure (CHF) exacerbation.

METHODS

Patients (n = 65) were randomized to intravenous (IV) insulin (duration 48 h) or subcutaneous (SQ) insulin. Inflammatory cytokines and markers of lipid oxidation, high-frequency heart rate variability (n = 27) and cardiac impedance (pre-ejection period, n = 28) were used to estimate parasympathetic and sympathetic tone in patients with valid cardiac data. Glycaemic variability was measured using a continuous glucose monitor.

RESULTS

Mean glucose was lower (7.7 ± 1.2 vs 9.4 ± 2.7 mmol/L, p = 0.004), coefficient of variation was higher (p = 0.03) and glycaemic lability index was similar on day 1 in the IV group compared with the SQ group, but groups were similar by day 2. The IV group had more confirmed hypoglycaemia (p = 0.005). There were no differences in hospital readmission or hospital length of stay between groups. There were no differences in CHF biomarkers, heart rate variability or pre-ejection period between groups. Increasing log glycaemic lability index was associated with lower on-treatment pre-ejection period (p = 0.03) while increasing coefficient of variation was associated with increasing brain natriuretic peptide (p = 0.004) and paroxonase-1 (p = 0.02). Other univariable analyses were not significant.

CONCLUSIONS

There were modest, transient differences in glucose control between IV and SQ insulin in hospitalized CHF patients. However, the analyses do not support a link between insulin route and inflammatory markers or autonomic tone. Further study is needed to assess outcomes in hospitalized CHF patients.

Glucose control positively influences patient outcome: A retrospective study

OBJECTIVE

The goal of this research is to demonstrate that well-regulated glycemia is beneficial to patient outcome, regardless of how it is achieved.

METHODS

This analysis used data from 1701 patients from 2, independent studies. Glycemic outcome was measured using cumulative time in band (cTIB), calculated for 3 glycemic bands and for threshold values of t = 0.5, 0.6, 0.7, and 0.8. For each day of intensive care unit stay, patients were classified by cTIB, threshold, and hospital mortality, and odds of living (OL) and odds ratio were calculated.

RESULTS

The OL given cTIB ≥ t is higher than the OL given cTIB <t for all values of t, every day, for all 3 glycemic bands studied. The difference between the odds clearly increased over intensive care unit stay for t>0.6. Higher cTIB thresholds resulted in larger increases to odds ratio over time and were particularly significant for the 4.0 to 7.0 mmol/L glycemic band.

CONCLUSION

Increased cTIB was associated with higher OL. These results suggest that effective glycemic control positively influences patient outcome, regardless of how the glycemic regulation is achieved. Blood glucose < 7.0 mmol/L is associated with a measurable increase in the odds of survival, if hypoglycemia is avoided.

GDF15 Is a Novel Biomarker for Impaired Fasting Glucose

BACKGROUND

Growth differentiation factor-15 (GDF15) is a protein that belongs to the transforming growth factor β superfamily. An elevated serum level of GDF15 was found to be associated with type 2 diabetes mellitus (T2DM). T2DM is an inflammatory disease that progresses from normal glucose tolerance (NGT) to impaired fasting glucose (IFG). Hence, we aimed to validate the relationship between GDF15 and IFG.

METHODS

The participants were divided into the following three groups: NGT (n=137), IFG (n=29), and T2DM (n=75). The controls and T2DM outpatients visited the hospital for routine health check-ups. We used fasting blood glucose to detect IFG in nondiabetic patients. We checked the body mass index (BMI), C-reactive protein level, metabolic parameters, and fasting serum GDF15 level.

RESULTS

Age, BMI, triglyceride, insulin, glucose, homeostatic model assessment-insulin resistance (HOMA-IR), and GDF15 levels were elevated in the IFG and T2DM groups compared to the NGT group. In the correlation analysis between metabolic parameters and GDF15, age and HOMA-IR had a significant positive correlation with GDF15 levels. GDF15 significantly discriminated between IFG and NGT, independent of age, BMI, and HOMA-IR. The serum levels of GDF15 were more elevated in men than in women. As a biomarker for IFG based on the receiver operating characteristic curve analysis, the cutoff value of GDF15 was 510 pg/mL in males and 400 pg/mL in females.

CONCLUSION

GDF15 had a positive correlation with IR independent of age and BMI, and the serum level of GDF15 was increased in the IFG and T2DM groups. GDF15 may be a novel biomarker for detecting IFG in nondiabetic patients.

Clinical impact of sample interference on intensive insulin therapy in severely burned patients: a pilot study

Severely burned patients benefit from intensive insulin therapy (IIT) for tight glycemic control (TGC). The authors evaluated the clinical impact of automatic correction of hematocrit and ascorbic acid interference for bedside glucose monitoring performance in critically ill burn patients. The performance of two point-of-care glucose monitoring systems (GMSs): 1) GMS1, an autocorrecting device, and 2) GMS2, a noncorrecting device were compared. Sixty remnant arterial blood samples were collected in a prospective observational study to evaluate hematocrit and ascorbic acid effects on GMS1 vs GMS2 accuracy paired against a plasma glucose reference. Next, we enrolled 12 patients in a pilot randomized controlled trial. Patients were randomized 1:1 to receive IIT targeting a TGC interval of 111 to 151 mg/dl and guided by either GMS1 or GMS2. GMS bias, mean insulin rate, and glycemic variability were calculated. In the prospective study, GMS1 results were similar to plasma glucose results (mean bias, -0.75 [4.0] mg/dl; n = 60; P = .214). GMS2 results significantly differed from paired plasma glucose results (mean bias, -5.66 [18.7] mg/dl; n = 60; P = .048). Ascorbic acid therapy elicited significant GMS2 performance bias (29.2 [27.2]; P < .001). Randomized controlled trial results reported lower mean bias (P < .001), glycemic variability (P < .05), mean insulin rate (P < .001), and frequency of hypoglycemia (P < .001) in the GMS1 group than in the GMS2 group. Anemia and high-dose ascorbic acid therapy negatively impact GMS accuracy and TGC in burn patients. Automatic correction of confounding factors improves glycemic control. Further studies are warranted to determine outcomes associated with accurate glucose monitoring during IIT.

Lower blood glucose and variability are associated with earlier recovery from renal injury caused by episodic urinary tract infection in advanced type 2 diabetic chronic kidney disease

PURPOSE

In our previous study, type 2 diabetic chronic kidney disease (CKD) patients with glomerular filtration rates of <30 mL/min upon hospitalization for urinary tract infection (UTI) were at a risk for acute kidney injury. This study aimed to clarify the effect of glucose and its variability on renal outcomes during admission for the treatment of UTI.

MATERIALS AND METHODS

Based on the date of renal recovery (RIFLE criteria: acute kidney injury occurred within 1-7 days and was sustained over 1 day), we divided these patients into early- (≤9 days, Group A) and late-recovery (>9 days, Group B) groups. The differences in the continuous and categorical variables of the two groups were assessed separately. The mean glucose levels and their variability (using the standard deviation and the coefficient of standard deviation) were compared at the fasting, midday pre-meal, evening pre-meal, and evening post-meal time points during hospitalization. We have organized the manuscript in a manner compliant with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement.

RESULTS

Acute kidney injury occurred within the two groups (p = 0.007 and p = 0.001, respectively). The early-morning blood glucose levels (149.7±44.0 mg/dL) and average blood glucose levels (185.6±52.0 mg/dL) were better in Group A (p = 0.01, p = 0.02). Group A patients also had lower glucose variability than Group B at the different time points (p<0.05). Group A also had earlier renal recovery. More relevant pathogens were identified from blood in Group B (p = 0.038).

CONCLUSIONS

Early-morning fasting and mean blood glucose levels and their variability can be good indicators of severe infection and predictors of renal outcome in type 2 diabetic patients with CKD and UTI.

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.

Assessment of the association between glycemic variability and diabetes-related complications in type 1 and type 2 diabetes

Chronic hyperglycemia is the main risk factor for the development of diabetes-related complications in both type 1 and type 2 diabetes, but it is thought that frequent or large glucose fluctuations may contribute independently to diabetes-related complications. A systematic literature review was performed using the PubMed, EMBASE and Cochrane Library databases with searches limited to studies published from June 2002 to March 2014, in English and including ≥50 patients. Twenty eight articles were included in the final review. Eighteen studies reported the association between glucose variability and diabetes-related complications exclusively in type 2 diabetes. A positive association between increased variability and microvascular complications and coronary artery disease was consistently reported. Associations between glucose variability and other macrovascular complications were inconsistent in type 2 diabetes. Seven studies examined the association between glucose variability and complications exclusively in type 1 diabetes. Increased glucose variability appears to play a minimal role in the development of micro- and macrovascular complications in type 1 diabetes. Consistent findings suggest that in type 2 diabetes glucose variability is associated with development of microvascular complications. The role of increased glucose variability in terms of microvascular and macrovascular complications in type 1 diabetes is less clear; more data in are needed.

Continuous glucose monitoring in insulin-treated patients in non-ICU settings

Inpatient hyperglycemia, in patients with and without a history of diabetes, is associated with increased risk of complications, mortality, and longer hospital stay in medicine and surgical patients. Bedside capillary point of care testing is widely recommended as the preferred method for glucose monitoring and for guiding glycemic management of individual patients; however, the accuracy of most handheld glucose meters is far from optimal. Recent studies in the hospital setting have reported that the use of continuous glucose monitoring (CGM) can provide real-time information about glucose concentration, direction, and rate of change over a period of several days. Because it provides glucose values every 5-10 minutes 24 hours a day, CGM may have an advantage over point of care testing with respect to reducing the incidence of severe hypoglycemia in acute care. Real-time CGM technology may facilitate glycemic control and to reduce hypoglycemia in insulin-treated patients. Recent guidelines, however, have recommended deferring the use of CGM in the adult hospital setting until further data on accuracy and safety become available. In this study, we review the advantages and disadvantages of the use of real-time CGM in the management of dysglycemia in the hospital setting.

Glycemic variability in nondiabetic morbidly obese persons: results of an observational study and review of the literature

Glycemic variability (GV) is correlated with oxidative stress which may lead to increased cardiovascular risk and poor clinical outcomes in people with prediabetes and diabetes. We sought to understand whether morbidly obese persons without diabetes by standard criteria have dysglycemia as measured by GV. We performed an observational study of GV metrics and carotid intima media thickness (CIMT) in 21 morbidly obese normoglycemic and 15 morbidly obese prediabetic applicants to The Biggest Loser television show. The results were compared to previously published studies in normoglycemic nonobese and obese individuals. Glucose was measured with a masked continuous glucose monitor (CGM) over 3 to 8 days and carotid intima media thickness (CIMT) was determined by ultrasound. CGM-derived GV metrics for GV were coefficient of variation (CV), standard deviation (SD), mean amplitude of glycemic excursions (MAGE), continuous overall net glycemic action-1 hour (CONGA1), and mean of daily differences (MODD). We found that morbidly obese subjects (n = 21) who were normoglycemic by standard criteria had higher GV (CV = 22%, SD = 24.2 mg/dl and MAGE = 48.6 mg/dl) than previous reports of normoglycemic, nonobese individuals (CV = 12-18%, SD = 11.5-15.0 mg/dl, and MAGE = 26.3-28.3 mg/dl). Morbidly obese prediabetic subjects (n = 15) had GV metrics indistinguishable from those morbidly obese subjects who were normoglycemic. CIMT was higher in both morbidly obese groups compared with historical age- and sex-matched controls. Normoglycemic and prediabetic morbidly obese individuals have higher GV compared with normal weight, nondiabetic individuals. We speculate that this may increase the risk for macrovascular disease through excessive oxidative stress.

Test-retest reliability of a continuous glucose monitoring system in individuals with type 2 diabetes

AIMS

This study determined the test-retest reliability of a continuous glucose monitoring system (CGMS) (iPro™2; Medtronic, Northridge, CA) under standardized conditions in individuals with type 2 diabetes (T2D).

SUBJECTS AND METHODS

Fourteen individuals with T2D spent two nonconsecutive days in a calorimetry unit. On both days, meals, medication, and exercise were standardized. Glucose concentrations were measured continuously by CGMS, from which daily mean glucose concentration (GLU(mean)), time spent in hyperglycemia (t(>10.0 mmol/L)), and meal, exercise, and nocturnal mean glucose concentrations, as well as glycemic variability (SD(w), percentage coefficient of variation [%cv(w)], mean amplitude of glycemic excursions [MAGEc, MAGE(ave), and MAGE(abs.gos)], and continuous overlapping net glycemic action [CONGA(n)]) were estimated. Absolute and relative reliabilities were investigated using coefficient of variation (CV) and intraclass correlation, respectively.

RESULTS

Relative reliability ranged from 0.77 to 0.95 (P<0.05) for GLU(mean) and meal, exercise, and nocturnal glycemia with CV ranging from 3.9% to 11.7%. Despite significant relative reliability (R=0.93; P<0.01), t(>10.0 mmol/L) showed larger CV (54.7%). Among the different glycemic variability measures, a significant between-day difference was observed in MAGEc, MAGE(ave), CONGA6, and CONGA12. The remaining measures (i.e., SD(w), %cv(w), MAGE(abs.gos), and CONGA1-4) indicated no between-day differences and significant relative reliability.

CONCLUSIONS

In individuals with T2D, CGMS-estimated glycemic profiles were characterized by high relative and absolute reliability for both daily and shorter-term measurements as represented by GLUmean and meal, exercise, and nocturnal glycemia. Among the different methods to calculate glycemic variability, our results showed SD(w), %cv(w), MAGE(abs.gos), and CONGAn with n ≤ 4 were reliable measures. These results suggest the usefulness of CGMS in clinical trials utilizing repeated measured.

The causal role of breakfast in energy balance and health: a randomized controlled trial in lean adults

BACKGROUND

Popular beliefs that breakfast is the most important meal of the day are grounded in cross-sectional observations that link breakfast to health, the causal nature of which remains to be explored under real-life conditions.

OBJECTIVE

The aim was to conduct a randomized controlled trial examining causal links between breakfast habits and all components of energy balance in free-living humans.

DESIGN

The Bath Breakfast Project is a randomized controlled trial with repeated-measures at baseline and follow-up in a cohort in southwest England aged 21-60 y with dual-energy X-ray absorptiometry-derived fat mass indexes ≤11 kg/m² in women (n = 21) and ≤7.5 kg/m² in men (n = 12). Components of energy balance (resting metabolic rate, physical activity thermogenesis, energy intake) and 24-h glycemic responses were measured under free-living conditions with random allocation to daily breakfast (≥700 kcal before 1100) or extended fasting (0 kcal until 1200) for 6 wk, with baseline and follow-up measures of health markers (eg, hematology/biopsies).

RESULTS

Contrary to popular belief, there was no metabolic adaptation to breakfast (eg, resting metabolic rate stable within 11 kcal/d), with limited subsequent suppression of appetite (energy intake remained 539 kcal/d greater than after fasting; 95% CI: 157, 920 kcal/d). Rather, physical activity thermogenesis was markedly higher with breakfast than with fasting (442 kcal/d; 95% CI: 34, 851 kcal/d). Body mass and adiposity did not differ between treatments at baseline or follow-up and neither did adipose tissue glucose uptake or systemic indexes of cardiovascular health. Continuously measured glycemia was more variable during the afternoon and evening with fasting than with breakfast by the final week of the intervention (CV: 3.9%; 95% CI: 0.1%, 7.8%).

CONCLUSIONS

Daily breakfast is causally linked to higher physical activity thermogenesis in lean adults, with greater overall dietary energy intake but no change in resting metabolism. Cardiovascular health indexes were unaffected by either of the treatments, but breakfast maintained more stable afternoon and evening glycemia than did fasting.

Influence of pulse pressure and spontaneous variations of macular thickness in patients with diabetic macular oedema

PURPOSE

To study spontaneous variations of central macular thickness (CMT) and its relation to blood pressure (BP) in patients with diabetic macular oedema (DME).

METHODS

23 diabetic patients presenting with DME with a CMT ≥ 260 μm on optical coherence tomography (OCT-3, Carl Zeiss Meditec, CA) were followed every 2 weeks for 3 months. At baseline, ambulatory 24H-BP monitoring (ABPM) was performed, as well as five CMT measurements (9 am, 12 am, 3 pm, 6 pm and 9 am the day after). During follow-up, BP and CMT were simultaneously measured at 9 am.

RESULTS

Significant spontaneous variations in CMT (at least one change in CMT greater than 11% compared to the median CMT value) were observed over 3 months in 48% of patients. Mean CMT decreased over the day and increased during the night, but not significantly (p = 0.1). During the 6 visits, the CMT at 9 am positively correlated with the pulse pressure (PP) measured at the same time (r = 0.29, p = 0.0008). In addition, the mean 24H-CMT was positively correlated with the mean 24H- PP (r = 0.48, p = 0.02).

CONCLUSION

Significant spontaneous changes in CMT of patients with DME were observed in nearly half of cases over 3 months. Retinal thickness was correlated to PP levels (patients with higher CMT had higher PP levels). This high variability of macular oedema, and the influence of BP on retinal thickness, should be taken into consideration by practitioners when evaluating the benefit of a therapy in DME.

Fluctuation between fasting and 2-H postload glucose state is associated with chronic kidney disease in previously diagnosed type 2 diabetes patients with HbA1c ≥ 7%

Objective

To investigate how the glucose variability between fasting and a 2-h postload glucose state (2-h postload plasma glucose [2hPG]-fasting plasma glucose [FPG]) is associated with chronic kidney disease (CKD) in middle-aged and elderly Chinese patients previously diagnosed with type 2 diabetes.

Design and Methods

This cross-sectional study included 1054 previously diagnosed type 2 diabetes patients who were 40 years of age and older. First, the subjects were divided into two groups based on a glycated hemoglobin (HbA1c) value of 7%. Each group was divided into two subgroups, with or without CKD. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was used to estimate the glomerular filtration rate (GFR). CKD was defined as eGFR<60 mL/min/1.73 m². Multiple linear regression analysis was used to estimate the association between the 2hPG-FPG and eGFR. The 2hPG-FPG value was divided into four groups increasing in increments of 36 mg/dl (2.0 mmol/L): 0–72, 72–108, 108–144 and ≥144 mg/dl, based on the quartiles of patients with HbA1c levels ≥7%; then, binary logistic regression analysis was used to investigate the association between 2hPG-FPG and the risk of CKD.

Results

In the patients with HbA1c levels ≥7%, the 2hPG-FPG was significantly associated with decreased eGFR and an increased risk of CKD independent of age, gender, body mass index (BMI), systolic blood pressure (BP), diastolic BP, smoking, and drinking, as well as fasting insulin, cholesterol, triglyceride, and HbA1c levels. The patients with 2hPG-FPG values ≥144 mg/dl showed an increased odds ratio (OR) of 2.640 (P = 0.033). Additionally, HbA1c was associated with an increased risk of CKD in patients with HbA1c values ≥7%.

Conclusions

The short-term glucose variability expressed by 2hPG-FPG is closely associated with decreased eGFR and an increased risk of CKD in patients with poor glycemic control (HbA1c≥7%).

Hypomethylation of the promoter of the catalytic subunit of protein phosphatase 2A in response to hyperglycemia

In order to identify epigenetic mechanisms through which hyperglycemia can affect gene expression durably in β cells, we screened DNA methylation changes induced by high glucose concentrations (25 mmol/L) in the BTC3 murine cell line, using an epigenome‐wide approach. Exposure of BTC3 cells to high glucose modified the expression of 1612 transcripts while inducing significant methylation changes in 173 regions. Among these 173 glucose‐sensitive differentially methylated regions (DMRs), 14 were associated with changes in gene expression, suggesting an epigenetic effect of high glucose on gene transcription at these loci. Among these 14 DMRs, we selected for further study Pp2ac, a gene previously suspected to play a role in β‐cell physiology and type 2 diabetes. Using RT‐qPCR and bisulfite pyrosequencing, we confirmed our previous observations in BTC3 cells and found that this gene was significantly demethylated in the whole blood cells (WBCs) of type 2 diabetic patients compared to controls.

In order to identify epigenetic mechanisms through which hyperglycemia can affect gene expression durably in β cells, we screened DNA methylation changes induced by high glucose concentration in the BTC3 murine cell line. We identified one interesting gene, PP2AC, and confirmed it in type 2 diabetic patients.

Different antihyperglycaemic drug effects on glycaemic variability in Type 2 diabetic patients

Optimizing treatments for type 2 diabetes mellitus (T2DM) remains an urgent issue. In addition to T2DM treatment strategies, such as glycaemic goals (glucose and glycated haemoglobin ? HbА1c) among different patient populations, the influence of glycaemic variability (GV) on the prognosis of patients with T2DM is also important. According to recent data, GV is associated with cardiovascular complications arising from T2DM. However, although the influence of GV on the development of vascular complications arising from diabetes and underlying mechanisms has been extensively investigated, few studies have investigated the effects of different glucose-lowering medications on GV, and there are even fewer reviews of this topic. This type of analysis is highly relevant, particularly because new classes of antidiabetic medications with potent glucose-dependent insulinotropic effects have been developed. These include groups of drugs that mimic or enhance incretin activity, such as glucagon-like peptide (GLP)-1 analogues/mimetics and dipeptidyl peptidase (DPP)-4 inhibitors. A glucose-dependent mechanism suggests that these groups of antidiabetic medications have beneficial effects on GV. Thus, the current study focusses on the comparative analysis of drugs based on their incretin effects (GLP-1 analogues/mimetics and DPP-4 inhibitors) and оther antidiabetic medications with regard to GV in the patients with T2DM.

Insulin analogs--is there a compelling case to use them? No!

The availability of insulin analogs has offered insulin replacement strategies that are proposed to more closely mimic normal human physiology. Specifically, there are a considerable number of reports demonstrating that prandial insulin analogs (lispro, aspart, glulisine) have pharmacokinetic and pharmacodynamic profiles closer to normal, with resulting faster onset and offset of insulin effect when compared with regular human insulin. In addition, basal insulin analogs (glargine, detemir) have been reported to offer longer duration of action, less variability, more predictability, less hypoglycemia (especially nocturnal), and a favorable effect on weight. However, an argument against use of analog insulins as compared with use of regular or NPH insulin is one that states that the effectiveness and risk of hypoglycemia are the only two valid clinical outcomes that should be used to compare the analog and human insulins. Thus, there remains a debate in some circles that analog insulins are no more effective than human insulins, yet at a much higher financial cost. To provide an in-depth understanding of both sides of the argument, we provide a discussion of this topic as part of this two-part point-counterpoint narrative. In the counterpoint narrative presented here, Dr. Davidson provides his argument and defends his opinion that outside of a few exceptions, analog insulins provide no clinical benefit compared with human insulins but cost much more. In the preceding point narrative, Dr. Grunberger provides a defense of analog insulins and their value in clinical management and suggests that when evaluating the “cost” of therapy, a much more global assessment is needed.

At the centennial of Michaelis and Menten, competing Michaelis-Menten steps explain effect of GLP-1 on blood-brain transfer and metabolism of glucose

Glucagon-like peptide-1 (GLP-1) is a potent insulinotropic incretin hormone with both pancreatic and extrapancreatic effects. Studies of GLP-1 reveal significant effects in regions of brain tissue that regulate appetite and satiety. GLP-1 mimetics are used for the treatment of type 2 diabetes mellitus. GLP-1 interacts with peripheral functions in which the autonomic nervous system plays an important role, and emerging pre-clinical findings indicate a potential neuroprotective role of the peptide, for example in models of stroke and in neurodegenerative disorders. A century ago, Leonor Michaelis and Maud Menten described the steady-state enzyme kinetics that still apply to the multiple receptors, transporters and enzymes that define the biochemical reactions of the brain, including the glucose-dependent impact of GLP-1 on blood-brain glucose transfer and metabolism. This MiniReview examines the potential of GLP-1 as a molecule of interest for the understanding of brain energy metabolism and with reference to the impact on brain metabolism related to appetite and satiety regulation, stroke and neurodegenerative disorders. These effects can be understood only by reference to the original formulation of the Michaelis-Menten equation as applied to a chain of kinetically controlled steps. Indeed, the effects of GLP-1 receptor activation on blood-brain glucose transfer and brain metabolism of glucose depend on the glucose concentration and relative affinities of the steps both in vitro and in vivo, as in the pancreas.

Qualitative analysis of subcutaneous Lispro and regular insulin injections for stress hyperglycemia: a pilot numerical study

Increased glucose variability (GV) is an independent risk factor for mortality in the critically ill; unfortunately, the optimal insulin therapy that minimizes GV is not known. We simulate the glucose-insulin feedback system to study how stress hyperglycemia (SH) states, taken to be a non-uniform group of physiologic disorders with varying insulin resistance (IR) and similar levels of hyperglycemia, respond to the type and dose of subcutaneous (SQ) insulin. Two groups of 100 virtual patients are studied: those receiving and those not receiving continuous enteral feeds. Stress hyperglycemia was facilitated by doubling the gluconeogenesis rate and IR was stepwise varied from a borderline to a high value. Lispro and regular insulin were simulated with dosages that ranged from 0 to 6 units; the resulting GV was analyzed after each insulin injection. The numerical model used consists of a set of non-linear differential equations with two time delays and five adjustable parameters. The results show that regular insulin decreased GV in both patient groups and rarely caused hypoglycemia. With continuous enteral feeds and borderline to mild IR, Lispro showed minimal effect on GV; however, rebound hyperglycemia that increased GV occurred when the IR was moderate to high. Without a nutritional source, Lispro worsened GV through frequent hypoglycemia episodes as the injection dose increased. The inferior performance of Lispro is a result of its rapid absorption profile; half of its duration of action is similar to the glucose ultradian period. Clinical trials are needed to examine whether these numerical results represent the glucose-insulin dynamics that occur in intensive care units, and if such dynamics are present, their clinical effects should be evaluated.

Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications

The routine approach to evaluating the effectiveness of diabetes treatment based on the level of glycated haemoglobin (HbA. 1c) accounts for the average glucose level but does not consider the scope and frequency of its fluctuations. The development of computational methods to analyse glycaemic oscillations has made it possible to propose the concept of glycaemic variability (GV). The interest in research focused on GV increased dramatically after continuous glucose monitoring (CGM) technology was introduced, which provided the opportunity to study in detail the temporal structure of blood glucose curves. Numerous methods for assessing GV proposed over the past five decades characterize glycaemic fluctuations as functions of concentration and time and estimate the risks of hypoglycaemia and hyperglycaemia. Accumulating evidence indicates that GV may serve as a significant predictor of diabetic complications. Prospective studies demonstrate that certain GV parameters have independent significance for predicting diabetic retinopathy, nephropathy and cardiovascular diseases. There is evidence that GV correlates with the severity of atherosclerotic vascular lesions and cardiovascular outcomes in diabetic patients. The mechanisms underlying the relationship between GV and vascular complications are being intensively studied, and recent data show that the effect of GV on vascular walls may be mediated by oxidative stress, chronic inflammation and endothelial dysfunction. Average blood glucose levels and GV are considered independent predictors of hypoglycaemia. Increased GV is associated with impaired hormonal response to hypoglycaemia and is a long-term predictor of hypoglycaemia unawareness. These data allow us to conclude that computational methods for analysing GV in patients with diabetes may serve as a promising tool for personalized assessment of glycaemic control and the risk of vascular complications and hypoglycaemia. Thus, the reduction of GV can be regarded as one of the therapeutic targets to treat diabetes.

Glycemic variability is higher in type 1 diabetes patients with microvascular complications irrespective of glycemic control

BACKGROUND

Increased glycemic variability (GV) may be associated with diabetes complications. Our study assessed the relationship between microvascular complications (MVCs) and GV calculated from continuous glucose monitoring (CGM) data in type 1 diabetes patients.

SUBJECTS AND METHODS

Thirty-two patients with type 1 diabetes (16 with and 16 without MVC) participated in this cross-sectional study. Vibration perception threshold (VPT), microalbuminuria, and fundoscopy were used to detect MVC. CGM data were recorded for 2 weeks and analyzed using proprietary software. Total SD (SDT), coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE) were compared.

RESULTS

Patients with any MVC had significantly higher GV, calculated from CGM, than patients without MVC (SDT, 4.1 ± 0.6 vs. 3.4 ± 0.8 mmol/L [P = 0.010]; CV, 0.43 ± 0.06 vs. 0.38 ± 0.08 [P = 0.032]; MAGE, 6.9 ± 1.2 vs. 5.9 ± 1.2 mmol/L [P = 0.014]) but comparable glycated hemoglobin (HbA1c) (70 ± 9 vs. 69 ± 10 mmol/mol [8.6 ± 0.8% vs. 8.5 ± 0.9%], difference not significant). No significant difference in GV was found between the two groups when using only self-monitored blood glucose (SMBG) data. A positive association was found between VPT and SDT in all patients (r = 0.51, P = 0.0026).

CONCLUSIONS

Patients with type 1 diabetes and any MVC had significantly higher GV calculated from CGM, but not from SMBG, than patients with comparable glycemic control but without complications. This supports the hypothesis that increased GV might be associated with MVC in type 1 diabetes and that HbA1c may not describe diabetes control completely.

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.

Impact of glycemic variability and hypoglycemia on adverse hospital outcomes in non-critically ill patients

AIMS

To determine if glycemic variability is associated with hospitalization outcomes in non-critically ill patients, and if this association remains after controlling for hypoglycemia.

METHODS

A retrospective review was performed on 1276 medical admissions (801 patients) in which insulin was given, ≥6 point of care glucose (POCG) measurements and length of stay (LOS) 2-30 days. Coefficient of variation (%CV) was used to measure glycemic variability. Outcomes included LOS and a composite outcome based on ICU transfer, hospital acquired infections, and acute renal failure (ARF).

RESULTS

There were a median of 18.5 POCG measurements per admission with a mean %CV 34.2 ± 11.1. Hypoglycemia (POCG ≤70 mg/dl [3.9 mmol/l]) occurred in 35.0% of admissions. ICU transfer occurred in 3.3%, hospital acquired infections 4.8%, ARF 8.3%, and composite outcome 13.5%. Adjusting for age, sex, race and Charlson score, every 10 unit increase in %CV was associated with an increase in LOS of 0.27 days (p=0.004), while there was no association between %CV and the composite outcome. For LOS, there was a significant interaction between %CV and hypoglycemia (p=0.07). While there was a non-significant correlation in patients without hypoglycemia, LOS correlated negatively with %CV in patients with hypoglycemia. When considered simultaneously with %CV, hypoglycemia was associated with increased odds of the composite outcome [OR 2.03 (95% CI 1.36-3.01), p=<0.001] and an increase of 2 days in LOS for those with average %CV.

CONCLUSIONS

Hypoglycemia, compared to glycemic variability, is more strongly associated with adverse outcomes in hospitalized, non-critically ill patients.

The Association of Glucose Variability and Home Discharge Among Survivors of Critical Illness Managed With a Computerized Decision-Support Tool for Glycemic Control

In-intensive care unit (ICU) glucose variability (GV) is associated with increased mortality. However, the impact of GV on hospital survivors' morbidity and associated changes in destination at time of hospital discharge are unknown. We studied a retrospective patient cohort in a medical/surgical ICU, requiring insulin infusion, using computer-guided insulin dosing software. Standard deviation (Glu_SD) and coefficient of variation (Glu_CV) were used as GV measures. We examined rates of home discharge (H) in the whole cohort and selected subgroups across GV quartiles, between patients with and without H, determinants of H, and determinants of GV and its association with patients' ICU length of stay (LOS). A total of 351 patients met study criteria. The association of GV and H varied among examined subgroups. H increased with GV quartile (Glu_SD; P = .004). GV was higher in patients with H than non-H (Glu_SD 36.1 vs 30.0 mg/dl, respectively; P = .002). Increased GV was not a predictor of reduced H on multivariate analysis. GV was inversely associated with patients' ICU LOS in all examined subgroups. Increased number of hypoglycemic events and time to attain target glycemia were independent predictors of reduced H. GV was not associated with adverse impact on H in the present cohort, and its prognostic impact should be considered in the context of ICU LOS of examined patient populations. Further studies are needed to examine the morbidity effects of GV and other glycemia-related measures among hospital survivors of critical illness across varying ICU populations, glycemic control approaches, and glycemic targets.

Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

The relationship between both interstitial and blood glucose remains a debated topic, on which there is still no consensus. The experimental evidence suggests that blood and interstitial fluid glucose levels are correlated by a kinetic equilibrium, which as a consequence has a time and magnitude gradient in glucose concentration between blood and interstitium. Furthermore, this equilibrium can be perturbed by several physiological effects (such as foreign body response, wound-healing effect, etc.), with a consequent reduction of interstitial fluid glucose versus blood glucose correlation. In the present study, the impact of operating in the interstitium on continuous glucose monitoring systems (CGMs) will be discussed in depth, both for the application of CGMs in the management of diabetes and in other critical areas, such as tight glycaemic control in critically ill patients.

Poor agreement of computerized calculators for mean amplitude of glycemic excursions

BACKGROUND

Glucose variability has been identified as a predictor of hypoglycemia and has been associated with mortality in critically ill patients without diabetes. A popular metric to quantify glucose variability is the mean amplitude of glycemic excursions (MAGE). The "ruler and pencil" approach to calculate MAGE is operator-dependent and time-consuming for analysis of continuous glucose monitoring data. Therefore, several computer software programs have been developed for the automated calculation of MAGE. The aim of our study was to evaluate the agreement of currently available MAGE calculators when applied to the same set of continuous glucose monitoring (CGM) traces.

MATERIALS AND METHODS

Four software programs for calculation of MAGE were identified and used to calculate MAGE of 21 CGM traces from seven patients with type 1 diabetes. Subsequently, the median MAGE per calculator was calculated. The correlation between the MAGE calculators was evaluated by Spearman's correlation analysis. Between-group comparison was performed using analysis of variance.

RESULTS

The median MAGE (interquartile range) per calculator was 8.7 (7.1-10.7), 6.7 (5.5-8.6), 6.7 (5.2-8.6), and 5.8 (4.3-7.1), which was statistically different overall (P<0.001). The correlation coefficients between the calculators ranged from 0.787 to 0.999.

CONCLUSIONS

Available computer programs developed to calculate MAGE show varying agreement. Although software programs for the calculation of MAGE would seem attractive to assess glucose variability, their use has limitations by different outcomes, in the absence of a gold standard.

Relationship between autonomic nervous system function and continuous interstitial glucose measurement in patients with type 2 diabetes

AIMS

The Aim of the present study was to examine whether there is a relationship between autonomic nervous system function and glycemic variability (GV) in patients with type 2 diabetes (T2D).

METHODS

A total of 50 (29 males) patients with T2D (mean age 58.4 ± 9.9 years, median diabetes duration 5.5 [IQR 2.0-9.25] years), on oral antidiabetic agents, underwent ECG recording and subcutaneous glucose monitoring, simultaneously and continuously, for 24 hours.

RESULTS

After adjustment for HbA1c and diabetes duration, total power of heart rate variability (HRV) was inversely associated with the standard deviation of the mean interstitial tissue glucose (MITG) and with the M-value during the entire recording (r: -0.29, P = 0.052; r: -0.30, P = 0.047, resp.) and during the night (r: -0.29, P = 0.047; r: -0.31, P = 0.03, resp.). Most of the HRV time-domain indices were significantly correlated with standard deviation of the MITG and the M-value. These correlations were stronger for the HRV recordings during the night. No significant association was found between HRV parameters and MAGE.

CONCLUSIONS

HRV is inversely associated with GV in patients with T2D, which might be a sign of causation between GV and autonomic dysfunction. Prospective studies are needed to further investigate the importance of GV in the pathogenesis of long-term complications of diabetes.

Systematic review: continuous intraperitoneal insulin infusion with implantable insulin pumps for diabetes mellitus

Continuous intraperitoneal insulin infusion (CIPII) with implantable insulin pumps (IIPs) is a treatment option for diabetes, which is not widely utilized nor freely accessible in clinical practice. The aim of this study was to summarize available evidence on use of IIPs for CIPII for diabetes treatment, since its introduction to clinical use on the following outcomes: HbA1c, hypoglycaemic events, and complications of treatment.

SECONDARY OUTCOMES

complications of diabetes and treatment satisfaction. Following the procedure for a systematic review this paper may contribute to a balanced evaluation of the need and effectiveness of IIPs. A pre-specified, registered protocol (CRD42012002150) was followed. Studies investigating all diabetes populations and types of IIPs were considered eligible. The sensitive search strategy was developed in collaboration with a clinical librarian and contents experts. PUBMED, MEDLINE, CENTRAL EMBASE, trial registries, and other databases were searched. References were screened independently by two authors, and decisions on study selection were recorded. Of the 1,703 references screened, 362 were assessed as potentially eligible. Ninety-four were identified as studies using IIPs. Fifteen papers, together reporting on four-randomized trials, and eight cohorts were included. Narrative analysis is provided, and data tables are available. CIPII by way of IIPs is effective in lowering HbA1c levels and reducing hypoglycaemic events. Superiority of IIP treatment is likely related to patient characteristics, one subgroup being patients unable to acquire satisfactory glycaemic control with subcutaneous insulin treatment. Higher treatment satisfaction was also reported for this subgroup. For these patients, risk of morbidity may be considered acceptable. Patients' perspectives, influence on quality of life, and possible other outcomes should also be considered important factors in weighing individual benefits and risks. A more uniform method of reporting would help strengthen the evidence base.

Chronic fatigue in type 1 diabetes: highly prevalent but not explained by hyperglycemia or glucose variability

OBJECTIVE Fatigue is a classical symptom of hyperglycemia, but the relationship between chronic fatigue and diabetes has not been systematically studied. We investigated prevalence, impact, and potential determinants of chronic fatigue in patients with type 1 diabetes mellitus (T1DM). RESEARCH DESIGN AND METHODS Out of 324 randomly selected T1DM outpatients, 214 participated in this cross-sectional observational study. Participants were compared with age- and sex-matched population-based controls. Chronic fatigue, functional impairments, current health status, comorbidity, diabetes-related factors, and fatigue-related cognitions and behaviors were assessed with questionnaires, and HbA1c values and comorbidity were assessed with medical records. Sixty-six patients underwent continuous glucose monitoring combined with an electronic fatigue diary for 5 days. Acute fatigue and four glucose parameters were determined: mean, variability, and relative time spent in hypoglycemia and hyperglycemia. RESULTS T1DM patients were significantly more often chronically fatigued (40%; 95% CI 34-47%) compared with matched controls (7%; 95% CI 3-10%; P < 0.001). Chronically fatigued patients had significantly more functional impairments. Fatigue was the most troublesome symptom. Age, depression, pain, sleeping problems, low self-efficacy concerning fatigue, and physical inactivity were significantly associated with chronic fatigue. Chronically fatigued patients spent slightly less time in hypoglycemia (proportion 0.07 ± 0.06 vs. 0.12 ± 0.10; P = 0.025). Glucose parameters were not related to acute fatigue. CONCLUSIONS Chronic fatigue is highly prevalent and clinically relevant in T1DM. Its significant relationship with cognitive behavioral variables and weak association with blood glucose levels suggests that behavioral interventions could be helpful in managing chronic fatigue in T1DM.

Hypoglycemia and blood glucose fluctuations in the application of a sensor-augmented insulin pump

BACKGROUND

The purpose of this study was to understand the effect of sensor-augmented insulin pump (SAP) use on hypoglycemia and blood glucose (BG) fluctuations.

SUBJECTS AND METHODS

Sixty patients with type 2 diabetes mellitus were randomly assigned to three groups of treatment with SAP, continuous subcutaneous insulin infusion (CSII), or multiple daily injection (MDI) therapy for 6 days. Parameters of glycemic control that were determined included mean BG concentration (MBG), SD of BG (SDBG), mean amplitude of glycemic excursions (MAGE), absolute means of daily differences (MODD), 24-h area under the curve at 10 h (AUC10), 24-h area under the curve at 3.9 h (AUC3.9), and Low Blood Glucose Index (LBGI).

RESULTS

No significant differences were observed among the three groups in terms of MBG, SDBG, MAGE, or MODD at the beginning of treatment. The MBG, SDBG, MAGE, MODD, and total AUC10 of the SAP group improved over the 4 days of the intervention compared with the CSII and MDI groups; however, no significant differences were observed among the three groups in terms of total AUC3.9 and LBGI.

CONCLUSIONS

Compared with CSII and MDI therapy, SAP therapy was able to rapidly lower mean BG and reduce BG level fluctuations with no increased risks of hypoglycemia.

Increased glycemic variability is independently associated with length of stay and mortality in noncritically ill hospitalized patients

OBJECTIVE

To investigate the association between glycemic variability (GV) and both length of stay (LOS) and 90-day mortality in noncritically ill hospitalized patients.

RESEARCH DESIGN AND METHODS

This study retrospectively analyzed 4,262 admissions to the general medicine or surgery services during a 2 year period. Patients with point-of-care glucose monitoring and a minimum of two glucose values per day on average were selected. GV was assessed by SD and coefficient of variation (CV). Data were analyzed with linear and logistic multivariate regression analysis in separate models for SD and CV. Analysis was performed with generalized estimating equations to adjust for correlation between multiple admissions in some individual cases.

RESULTS

After exclusions, 935 admissions comprised the sample. Results of adjusted analysis indicate that for every 10 mg/dL increase in SD and 10-percentage point increase in CV, LOS increased by 4.4 and 9.7%, respectively. Relative risk of death in 90 days also increased by 8% for every 10-mg/dL increase in SD. These associations were independent of age, race, service of care (medicine or surgery), previous diagnosis of diabetes, HbA1c, BMI, the use of regular insulin as a sole regimen, mean glucose, and hypoglycemia occurrence during the hospitalization.

CONCLUSIONS

Our results indicate that increased GV during hospitalization is independently associated with longer LOS and increased mortality in noncritically ill patients. Prospective studies with continuous glucose monitoring are necessary to investigate this association thoroughly and to generate therapeutic strategies targeted at decreasing GV.

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.

Minimal functional β-cell mass in intraportal implants that reduces glycemic variability in type 1 diabetic recipients

OBJECTIVE

Previous work has shown a correlation between β-cell number in cultured islet cell grafts and their ability to induce C-peptide secretion after intraportal implantation in C-peptide-negative type1 diabetic patients. In this cross-sectional study, we examined the minimal functional β-cell mass (FBM) in the implant that induces metabolic improvement.

RESEARCH DESIGN AND METHODS

Glucose clamps assessed FBM in 42 recipients with established implants. C-peptide release during each phase was expressed as percentage of healthy control values. Its relative magnitude during a second hyperglycemic phase was most discriminative and therefore selected as a parameter to be correlated with metabolic effects.

RESULTS

Recipients with functioning β-cell implants exhibited average FBM corresponding to 18% of that in normal control subjects (interquartile range 10-33%). Its relative magnitude negatively correlated with HbA1c levels (r = -0.47), daily insulin dose (r = -0.75), and coefficient of variation of fasting glycemia (CVfg) (r = -0.78, retained in multivariate analysis). A correlation between FBM and CVfg <25% appeared from the receiver operating characteristic curve (0.97 [95% CI 0.93-1.00]). All patients with FBM >37% exhibited CVfg <25% and a >50% reduction of their pretransplant CVfg; this occurred in none with FBM <5%. Implants with FBM >18% reduced CVfg from a median pretransplant value of 46 to <25%.

CONCLUSIONS

Glucose clamping assesses the degree of restoration in FBM achieved by islet cell implants. Values >37% of normal control subjects appear needed to reduce glycemic variability in type 1 diabetic recipients. Further studies should examine whether the test can help guide decisions on additional islet cell transplants and on adjusting or stopping immunotherapy.

Glycaemic instability correlates with a hyperglucagonaemic response in patients with type 1 diabetes without residual beta-cell function

We investigated the association between arginine-stimulated glucagon secretion (AUCIRG) and several parameters of glycaemic variability in 12 patients with type 1 diabetes without residual beta-cell function. AUCIRG positively correlated with the SD and mean amplitude of glycaemic excursions, thus glucagon might contribute to glycaemic instability, independent of endogenous insulin.