Key indices of glycaemic variability for application in diabetes clinical practice.

Near normal glycaemic control in diabetes consists to target daily glucose fluctuations and quarterly HbA1c oscillations in addition to overall glucose exposure. Consequently, the prerequisite is to define simple, and mathematically undisputable key metrics for the short- and long-term variability in glucose homeostasis. As the standard deviations (SD) of either glucose or HbA1c are dependent on their means, the coefficient of variation (CV = SD/mean) should be applied instead as it that avoids the correlation between the SD and mean values. A CV glucose of 36% is the most appropriate threshold between those with stable versus labile glucose homeostasis. However, when near normal mean glucose concentrations are achieved a lower CV threshold of <27 % is necessary for reducing the risk for hypoglycaemia to a minimal rate. For the long-term variability in glucose homeostasis, a CVHbA1c < 5 % seems to be a relevant recommendation for preventing adverse clinical outcomes.

Glycaemic variabilities: Key questions in pursuit of clarity.

After years of intensive investigation, the definition of glycaemic variability remains unclear and the term variability in glucose homoeostasis might be more appropriate covering both short and long-term glycaemic variability. For the latter, we remain in the search of an accurate definition and related targets. Recent work leads us to consider that the within-subject variability of HbA1c calculated from consecutive determinations of HbA1c at regular time-intervals could be the most relevant index for assessing the long-term variability with a threshold value of 5% (%CV = SD of HbA1c/mean HbA1c) to separate stability from lability of HbA1c. Presently, no one can deny that short- and long-term glucose variability should be maintained within their lower ranges to limit the incidence of hypoglycaemia. Usually, therapeutic strategies aimed at reducing post-meal glucose excursions, i.e. the major contributor to daily glucose fluctuations, exert a beneficial effect on the short-term glucose variability. This explains the effectiveness of adjunct therapies with either GLP- receptor agonists or SGLT inhibitors in type 2 diabetes. In type 1 diabetes, the application of a CGM device alone reduces the short-term glycaemic variability. In contrast, sophisticated insulin delivery does not necessarily lead to such reductions despite marked downward shifts of 24-hour glycaemic profiles. Such contrasting observations raise the question as to whether the prolonged wear of CGM devices is or not the major causative factor for improvement in glucose variability among intensively insulin-treated persons with type 1 diabetes.

Glucose variability and diabetes complications: Risk factor or biomarker? Can we disentangle the "Gordian Knot"?

« Variability in glucose homoeostasis ¼ is a better description than « glycaemic variability ¼ as it encompasses two categories of dysglycaemic disorders: i) the short-term daily glucose fluctuations and ii) long-term weekly, monthly or quarterly changes in either HbA1c, fasting or postprandial plasma glucose. Presently, the relationship between the "variability in glucose homoeostasis" and diabetes complications has never been fully clarified because studies are either observational or limited to retrospective analysis of trials not primarily designed to address this issue. Despite the absence of definitive evidence from randomized controlled trials (RCTs), it is most likely that acute and long-term glucose homoeostasis "cycling", akin to weight and blood pressure "cycling" in obese and hypertensive individuals, are additional risk factors for diabetes complications in the presence of sustained ambient hyperglycaemia. As hypoglycaemic events are strongly associated with short- and long-term glucose variability, two relevant messages can be formulated. Firstly, due consideration should be given to avoid within-day glucose fluctuations in excess of 36% (coefficient of variation) at least for minimizing the inconvenience and dangers associated with hypoglycaemia. Secondly, it seems appropriate to consider that variability in glucose homoeostasis is not only associated with cardiovascular events but is also a causative risk factor via hypoglycaemic episodes as intermediary step. Untangling the" Gordian Knot", to provide confirmation about the impact of variability in glucose homoeostasis and diabetes complications remains a daunting prospect.

The obesity treatment dilemma: Why dieting is both the answer and the problem? A mechanistic overview.

Restricted-calorie diets are the most worldwide used treatments for obesity. Although such strategies are based on the first law of thermodynamics, the real life clinical practice demonstrates that the observed weight losses are divergent from those theoretically predicted. Loosely adherence to recommendations is one of the main causes for the limited efficacy of dieting, but many additional factors can be involved in the hurdles to weight loss. According to the second law of thermodynamics any restriction in dietary energy intake results in energy sparing with a diminution in the basal metabolic rate and a concomitant loss in the lean body mass. This "thrifty" energetic adaptation is associated with a progressive reduction in the difference between levels of energy intake and expenditure, thus resulting in a drastic fall in weight loss rates on the medium and long-term regardless of the dietary carbohydrate/fat ratio. This loss of efficacy is aggravated by the misadaptation of the production and action of anti-obesity hormones such as leptin. During the latest past decades the discovery of changes in the gut microbiota of obese people referred to as "obese dysbiosis" has raised the question as to whether these alterations can participate to diet-resistance. Combined with the behavioral and psychological barriers to low-calorie diets, there is a broad physiologic spectrum of evidence indicating that weight loss is a hard challenge. Consequently, the answer would be primarily to prevent the development of obesity and at worst to avoid its ominous progression from metabolically healthy to unhealthy stages.

Review of methods for detecting glycemic disorders.

Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity.

Respective Contributions of Glycemic Variability and Mean Daily Glucose as Predictors of Hypoglycemia in Type 1 Diabetes: Are They Equivalent?

OBJECTIVE: To evaluate the respective contributions of short-term glycemic variability and mean daily glucose (MDG) concentration to the risk of hypoglycemia in type 1 diabetes. RESEARCH DESIGN AND METHODS: People with type 1 diabetes (n = 100) investigated at the University Hospital of Montpellier (France) underwent continuous glucose monitoring (CGM) on two consecutive days, providing a total of 200 24-h glycemic profiles. The following parameters were computed: MDG concentration, within-day glycemic variability (coefficient of variation for glucose [%CV]), and risk of hypoglycemia (presented as the percentage of time spent below three glycemic thresholds: 3.9, 3.45, and 3.0 mmol/L). RESULTS: MDG was significantly higher, and %CV significantly lower (both P < 0.001), when comparing the 24-h glycemic profiles according to whether no time or a certain duration of time was spent below the thresholds. Univariate regression analyses showed that MDG and %CV were the two explanatory variables that entered the model with the outcome variable (time spent below the thresholds). The classification and regression tree procedure indicated that the predominant predictor for hypoglycemia was %CV when the threshold was 3.0 mmol/L. In people with mean glucose ≤7.8 mmol/L, the time spent below 3.0 mmol/L was shortest (P < 0.001) when %CV was below 34%. CONCLUSIONS: In type 1 diabetes, short-term glycemic variability relative to mean glucose (i.e., %CV) explains more hypoglycemia than does mean glucose alone when the glucose threshold is 3.0 mmol/L. Minimizing the risk of hypoglycemia requires a %CV below 34%.

Toward Defining the Threshold Between Low and High Glucose Variability in Diabetes.

OBJECTIVE: To define the threshold for excess glucose variability (GV), one of the main features of dysglycemia in diabetes. RESEARCH DESIGN AND METHODS: A total of 376 persons with diabetes investigated at the University Hospital of Montpellier (Montpellier, France) underwent continuous glucose monitoring. Participants with type 2 diabetes were divided into several groups-groups 1, 2a, 2b, and 3 (n = 82, 28, 65, and 79, respectively)-according to treatment: 1) diet and/or insulin sensitizers alone; 2) oral therapy including an insulinotropic agent, dipeptidyl peptidase 4 inhibitors (group 2a) or sulfonylureas (group 2b); or 3) insulin. Group 4 included 122 persons with type 1 diabetes. Percentage coefficient of variation for glucose (%CV = [(SD of glucose)/(mean glucose)] × 100) and frequencies of hypoglycemia (interstitial glucose <56 mg/dL [3.1 mmol/L]) were computed. RESULTS: Percentages of CV (median [interquartile range]; %) increased significantly (P < 0.0001) from group 1 (18.1 [15.2-23.9]) to group 4 (37.2 [31.0-42.3]). In group 1, the upper limit of %CV, which served as reference for defining excess GV, was 36%. Percentages of patients with %CVs above this threshold in groups 2a, 2b, 3, and 4 were 0, 12.3, 19.0, and 55.7%, respectively. Hypoglycemia was more frequent in group 2b (P < 0.01) and groups 3 and 4 (P < 0.0001) when subjects with a %CV >36% were compared with those with %CV ≤36%. CONCLUSIONS: A %CV of 36% appears to be a suitable threshold to distinguish between stable and unstable glycemia in diabetes because beyond this limit, the frequency of hypoglycemia is significantly increased, especially in insulin-treated subjects.

"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.

Magnitude of the dawn phenomenon and its impact on the overall glucose exposure in type 2 diabetes: is this of concern?

OBJECTIVE: To assess the magnitude of the dawn phenomenon and its impact on the total glucose exposure in type 2 diabetes. RESEARCH DESIGN AND METHODS: A total of 248 noninsulin-treated persons with type 2 diabetes who underwent continuous glucose monitoring were divided into three groups selected by treatments: diet alone (n = 53); insulin sensitizers alone (n = 82); and insulin secretagogues alone or in combination with insulin sensitizers (n = 113). The dawn phenomenon (∂ glucose, mg/dL) was quantified by its absolute increment from nocturnal nadir to prebreakfast value. The participants were secondarily divided into two paired subsets after they had been separated by the presence/absence of a dawn phenomenon based on a threshold of 20 mg/dL and matched for glucose nadir. The impact of the dawn phenomenon was assessed on HbA1c and 24-h mean glucose. RESULTS: The median of ∂ glucose (interquartile range) was 16.0 (0-31.5 mg/dL) in the 248 subjects, and no differences were observed across groups selected by HbA1c or treatments. In the overall population, the mean impacts on HbA1c and 24-h mean glucose were 4.3 ± 1.3 mmol/mol (0.39 ± 0.12%) and 12.4 ± 2.4 mg/dL, respectively. The mean impact on 24-h mean glucose was not statistically different between those on diet alone (16.7 ± 5.9 mg/dL) compared with the two subsets treated with oral hypoglycemic agents (11.2 ± 5.3 and 8.5 ± 7.5 mg/dL). CONCLUSIONS: The impact of the dawn phenomenon on overall glycemic control in type 2 diabetes, as depicted by the HbA1c level, was ∼0.4% and not eliminated by any of the currently available armamentarium of oral antidiabetes agents.

Frequency and severity of the dawn phenomenon in type 2 diabetes: relationship to age.

OBJECTIVE: To know whether age has an independent effect on the dawn phenomenon in noninsulin-using type 2 diabetes. RESEARCH DESIGN AND METHODS: Eighty-one individuals with type 2 diabetes were matched for HbA(1c) and divided by age into three subgroups of 27 individuals (1: ≥70 years; 2: 60-69 years; and 3: ≤59 years). All underwent ambulatory continuous glucose monitoring for quantifying the dawn phenomenon (i.e., the absolute [∂G, mg/dL] or relative [∂G%] increments from nocturnal nadirs to prebreakfast time points). RESULTS: HbA(1c) levels and 24-h glycemic profiles were similar across the three groups. Glucose increments (mean ± SEM) were identical in the three groups: ∂G (mg/dL), 22.0 ± 4.7 (1), 21.3 ± 3.6 (2), and 18.0 ± 3.6 (3) and δG (%), 19.9 ± 4.9 (1), 21.6 ± 4.4 (2), and 17.6 ± 4.2 (3). Using the most common definition (∂G >10 mg/dL), the prevalence of the dawn phenomenon was 52, 70, and 59% in groups 1, 2, and 3, respectively. CONCLUSIONS: The dawn phenomenon is present in the elderly.

Add-on therapies to metformin in type 2 diabetes: what modulates the respective decrements in postprandial and basal glucose?

BACKGROUND: Oral hypoglycemic agents (OHAs) are usually divided into postprandial and basal drugs. As their actions are probably more complex, it is important to ascertain which factors can modulate their effects. SUBJECTS AND METHODS: Thirty-one type 2 diabetes patients treated with metformin (glycosylated hemoglobin [HbA1c] 6.5-9%; median, 7.3%) and enrolled in two randomized controlled studies were allocated to either rosiglitazone (Group 1, n = 8) or glimepiride (Group 2, n = 7) and to either vildagliptin or sitagliptin (Group 3 considered as a whole, n = 16). All patients were investigated using continuous glucose monitoring at baseline and after 8-12 weeks of add-on therapy. Areas under the 24-h glycemic profile curves (AUCs) were determined for assessing postprandial (AUCpp), basal (AUCb), and total (AUCtotal) hyperglycemia. After calculation of decrements in AUCs (∂AUCs) from baseline to end of treatment periods, the following contribution ratios of postprandial and basal decrements to the overall glucose decrement were determined: ∂AUCpp/∂AUCtotal and ∂AUCb/∂AUCtotal (%). RESULTS: ∂AUCpp/∂AUCtotal and ∂AUCb/∂AUCtotal were negatively and positively, respectively, associated (R(2) = 0.195, P = 0.013) with baseline HbA1c. ∂AUCpp/∂AUCtotal was significantly higher (50.8 ± 4.8%) in patients with HbA1c <7.3% than in those with HbA1c ≥ 7.3% (27.0 ± 4.4%) (P = 0.001). After adjustment on baseline HbA1c, ∂AUCpp/∂AUCtotal was greater in Group 3 (44.0 ± 1.6%) than in Group 1 (32.1 ± 4%) and 2 (37.0 ± 3.1%) (P = 0.007). CONCLUSIONS: Gliptins, glitazones and sulfonylureas concomitantly act on basal and postprandial glucose even though gliptins are more efficient on postprandial glucose. HbA1c appears as a reliable factor for predicting the respective decrements of these two parameters and thus for guiding the choice between the aforementioned drugs.

The glycemic triumvirate and diabetic complications: is the whole greater than the sum of its component parts?

The dysglycemia of diabetes mellitus can be depicted as the glycemic triumvirate with its 3 main components: the sustained chronic (ambient) hyperglycemia, glucose variability and hypoglycemic episodes. The respective contributions of these glycemic disorders to the overall risk for diabetic complications remain a subject of debate. At present, there is cogent evidence for the direct deleterious effect of ambient hyperglycemia while the roles exerted by glucose variability and hypoglycemia remain less documented and only based on observational and pathophysiological studies. In addition, these 3 glycemic disorders could be regarded as components of either an additive or an initiator/accelerator model according to whether each disorder exerts an independent or inter-dependent effect on the development and progression of diabetes-related complications, respectively. In the present review, pros and cons arguments for each model are debated. However it is highly likely that these 3 glycemic disorders have both direct (spoke in a wheel) and indirect (link in a chain) causal effects on clinical cardiovascular outcomes. As a consequence, the relationship between the so-called glycemic triumvirate and diabetic complications might be summarized by the famous Aristotle's aphorism: "the whole is greater than the sum of its parts".

Postprandial and basal glucose in type 2 diabetes: assessment and respective impacts.

The independent contribution of postprandial glucose (PPG) excursions to the overall glucose exposure and its role in the development of both micro- and macrovascular complications of diabetes remain subject to continuing debate in type 2 diabetes. Discussion continues on whether postprandial hyperglycemia is the main contributor to the overall hyperglycemia in fairly well-controlled individuals, whereas basal hyperglycemia becomes the preponderant contributor in poorly controlled patients. The concern about the role of PPG as a risk factor for diabetes complications is related to the controversial data obtained in individuals with impaired glucose tolerance. It remains, however, that the total glucose exposure as reflected by hemoglobin A1c (HbA1c) levels is an undoubted major vascular risk factor. Excluding the contribution of PPG is nonsensical. In support of this position is the fact that the absolute impact of PPG on HbA1c, expressed as percentage levels of HbA1c, remains constant at 1% across the HbA1c continuum in non-insulin-treated type 2 diabetes patients. This key feature clearly depicts the absolute contribution of PPG in contrast to its relative contribution and better explains why PPG contributes to the excess of glycation with the basal hyperglycemia.