Glucose variability: Do we have to revisit the profusion of definitions to avoid confusion?

Research progress in the application of time in range: more than a percentage

ABSTRACT

Glucose monitoring is an important part of medical care in diabetes mellitus, which not only helps assess glycemic control and treatment safety, but also assists with treatment adjustment. With the development of continuous glucose monitoring (CGM), the use of CGM has increased rapidly. With the wealth of glucose data produced by CGM, new metrics are greatly needed to optimally evaluate glucose status and guide the treatment. One of the parameters that CGM provides, time in range (TIR), has been recognized as a key metric by the international consensus. Before the adoption of TIR in clinical practice, several issues including the minimum length of CGM use, the setting of the target range, and individualized TIR goals are summarized. Additionally, we discussed the mounting evidence supporting the association between TIR and diabetes-related outcomes. As a novel glucose metric, it is of interest to compare TIR with other conventional glucose markers such as glycated hemoglobin A1c. It is anticipated that the use of TIR may provide further information on the quality of glucose control and lead to improved diabetes management.

Are There Different Viewpoints About the Management of Type 2 Diabetes Mellitus and Comorbidities? A Multidisciplinary Spanish Qualitative Research

INTRODUCTION

The aim of this study was to explore the vision of a large multidisciplinary group of physicians treating type 2 diabetes mellitus (T2DM) in Spain, with a special focus on controversial management aspects. The perceptions of primary care (PC) physicians and hospital care (HC) specialists were compared.

METHODS

This was a mixed survey that included Delphi-like statements and opinion, attitude and behaviour (OAB) questions. The Delphi-like statements were assessed on the basis of the degree of agreement among respondents, and a descriptive analysis was performed on the answers to the OAB questions.

RESULTS

A total of 296 participants responded to the first wave of the survey, of whom 293 responded to the second wave (211 from PC and 80 from HC, with two respondents for whom there were no data on specialty). A high degree of consensus (CNS ≥ 0.8) was obtained in all the statements. A proactive approach to detect prediabetes or T2DM in asymptomatic people was highly supported (80.4% of agreement). Introducing early treatment intensification was considered to favour the durability of glycaemic control and to delay the progression of the disease (80.4%). There was agreement on the statement that glycaemic variability constitutes a risk factor for chronic complications, although differences in the perceptions of HC physicians and PC specialists were identified (86.3 vs. 80.1%, respectively). More HC physicans than PC specialists considered comorbidities to affect the ability to self-care (95 vs. 82.9%, respectively).

CONCLUSIONS

The survey revealed that there was a high, albeit not universal, degree of agreement amongst PC physicians and HC specialists in relation to prevention, screening and diagnosis of T2DM; early treatment intensification; dysglycaemias; and the management of patients with comorbidities. The statement on the management of patients with comorbidities elicited the highest difference between PC physicans and HC specialists. The results of this survey indicate that there is room for improvement in terms of implementing strategies in these areas.

Enlarged glycemic variability in sulfonylurea-treated well-controlled type 2 diabetics identified using continuous glucose monitoring

Time in range (TIR) is an index of glycemic control obtained from continuous glucose monitoring (CGM). The aim was to compare the glycemic variability of treatment with sulfonylureas (SUs) in type 2 diabetes mellitus (T2DM) with well-controlled glucose level (TIR > 70%). The study subjects were 123 patients selected T2DM who underwent CGM more than 24 h on admission without changing treatment. The primary endpoint was the difference in glycemic variability, while the secondary endpoint was the difference in time below range < 54 mg/dL; TBR < 54, between the SU (n = 63) and non-SU (n = 60) groups. The standard deviation, percentage coefficient of variation (%CV), and maximum glucose level were higher in the SU group than in the non-SU group, and TBR < 54 was longer in the high-dose SU patients. SU treatment was identified as a significant factor that affected %CV (β: 2.678, p = 0.034). High-dose SU use contributed to prolonged TBR < 54 (β: 0.487, p = 0.028). Our study identified enlarged glycemic variability in sulfonylurea-treated well-controlled T2DM patients and high-dose SU use was associated with TBR < 54. The results highlight the need for careful adjustment of the SU dose, irrespective of glycated hemoglobin level or TIR value.

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

« Variability in glucose homoeostasis » is a better description than « glycaemic variability » 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.

Resistance to data loss from the Freestyle Libre: impact on glucose variability indices and recommendations for data analysis

Like many wearables, flash glucose monitoring relies on user compliance and is subject to missing data. As recent research is beginning to utilise glucose technologies as behaviour change tools, it is important to understand whether missing data are tolerable. Complete Freestyle Libre data files were amputed to remove 1-6 h of data both at random and over mealtimes (breakfast, lunch, and dinner). Absolute percent errors (MAPE) and intraclass correlation coefficients (ICC) were calculated to evaluate agreement and reliability. Thirty-two (91%) participants provided at least 1 complete day (24 h) of data (age: 44.8 ± 8.6 years, female: 18 (56%); mean fasting glucose: 5.0 ± 0.6 mmol/L). Mean and continuous overall net glycaemic action (CONGA) (60 min) were robust to data loss (MAPE ≤3%). Larger errors were calculated for standard deviation, coefficient of variation (CV) and mean amplitude of glycaemic excursions (MAGE) at increasing missingness (MAPE: 2%-10%, 2%-9%, and 4%-18%, respectively). ICC decreased as missing data increased, with most indicating excellent reliability (>0.9) apart from certain MAGE ICCs, which indicated good reliability (0.84-0.9). Researchers and clinicians should be aware of the potential for larger errors when reporting standard deviation, CV, and MAGE at higher rates of data loss in nondiabetic populations. But where mean and CONGA are of interest, data loss is less of a concern. Novelty: As research now utilises flash glucose monitoring as behavioural change tools in nondiabetic populations, it is important to consider the influence of missing data. Glycaemic variability indices of mean and CONGA are robust to data loss, but standard deviation, CV, and MAGE are influenced at higher rates of missingness.

Reconfirmation of newly discovered risk factors of diabetic peripheral neuropathy in patients with type 2 diabetes: A case-control study

AIMS

The aim of the present study was to investigate the major determinants of diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes (T2D), considering the traditional and newly discovered risk factors, including hypoglycaemia and glycemic variability.

METHODS

This retrospective case-control study was conducted in a tertiary care hospital in Taiwan. A total of 2,837 patients with T2D were recruited, medical history and biochemical data were obtained, and patients were screened for DPN using the Michigan Neuropathy Screening Instrument (MNSI). DPN was defined as an MNSI exam score > 2. A stepwise selection of variables was used based on the Akaike Information Criterion (AIC) and the Schwarz Criterion (SC). Multivariate analysis was performed using the identified variables obtained from the stepwise selection.

RESULTS

Among the recruited patients, 604 (21.3%) were found to have DPN. 275 patients with DPN were selected because of longer follow up period before enrollment and complete data of glycemic parameters, and paired with 351 patients with T2D without DPN and matched for age, gender, and diabetes duration. The results of the stepwise selection showed that the presence of moderately and severely increased albuminuria yielded the lowest values of AIC and SC, which indicate the best predictive performance. Multivariate analysis demonstrated that moderately and severely increased albuminuria and greater long-term glycemic variability significantly increased the risk of DPN, with a corresponding odds ratio of 1.85 and 1.61 (95%confidence intervals of 1.25-2.73and1.02-2.55, respectively), after adjusted for hypoglycaemia and types of diabetes treatment.

CONCLUSIONS

Albuminuria is a potent predictor of DPN, and greater long-term glycemic variabilityis clearly associated with DPN in adults with T2D. These findings indicate that, in addition to achieve average blood glucose control, screening for albuminuria and reducing blood glucose fluctuations might be useful for improving diabetic microvascular complications.

Improvements of ambient hyperglycemia and glycemic variability are associated with reduction in oxidative stress for patients with type 2 diabetes

AIMS

We aimed to evaluate which parameters of improvement in glucose metabolism reduce oxidative stress for patients with Type 2 diabetes mellitus (T2DM).

METHODS

Sixty-seven outpatients with T2DM underwent 72 h of continuous glucose monitoring (CGM) and were measured for oxidative stress before and after a 24-week intervention with the following targets: fasting plasma glucose (FPG), <130 mg/dl; postprandial plasma glucose (PPG), <180 mg/dl; and glycated hemoglobin (HbA1c), <7% (53 mmol/mol). The mean glucose level (MGL), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), percentage coefficient of variation for glucose (%CV) and area under the postprandial plasma glucose curve (AUC_PP) were calculated from the CGM data. Oxidative stress was estimated using the diacron-reactive oxygen metabolites (d-ROMs) test. Finally, the association between the improvements in glucose metabolism and oxidative stress was evaluated.

RESULTS

FPG, MGL, HbA1c, MAGE, MODD, %CV, AUC_PP, and d-ROMs significantly improved after 24 weeks of intervention. The change in d-ROMs was significantly correlated with that in FPG (r = 0.414), MGL (r = 0.402), HbA1c (r = 0.271), MAGE (r = 0.457), MODD (r = 0.371), and AUC_PP (r = 0.352). The correlation of the change in d-ROMs with that in FPG, MAGE, and MODD and the use of glucose-like peptide 1 receptor agonists and statins remained significant after adjustment for other markers of diabetes control (multiple R² = 0.406).

CONCLUSIONS

Improvements in glucose metabolism, including FPG and daily and day-to-day glucose variability, were all correlated with reduced oxidative stress for patients with T2DM.

The application of simple metrics in the assessment of glycaemic variability

The assessment of glycaemic variability (GV) remains a subject of debate with many indices proposed to represent either short- (acute glucose fluctuations) or long-term GV (variations of HbA_1c). For the assessment of short-term within-day GV, the coefficient of variation for glucose (%CV) defined as the standard deviation adjusted on the 24-h mean glucose concentration is easy to perform and with a threshold of 36%, recently adopted by the international consensus on use of continuous glucose monitoring, separating stable from labile glycaemic states. More complex metrics such as the Low Blood Glucose Index (LBGI) or High Blood Glucose Index (HBGI) allow the risk of hypo or hyperglycaemic episodes, respectively to be assessed although in clinical practice its application is limited due to the need for more complex computation. This also applies to other indices of short-term intraday GV including the mean amplitude of glycemic excursions (MAGE), Shlichtkrull's M-value and CONGA. GV is important clinically as exaggerated glucose fluctuations are associated with an enhanced risk of adverse cardiovascular outcomes due primarily to hypoglycaemia. In contrast, there is at present no compelling evidence that elevated short-term GV is an independent risk factor of microvascular complications of diabetes. Concerning long-term GV there are numerous studies supporting its association with an enhanced risk of cardiovascular events. However, this association raises the question as to whether the impact of long-term variability is not simply the consequence of repeated exposure to short-term GV or ambient chronic hyperglycaemia. The renewed emphasis on glucose monitoring with the introduction of continuous glucose monitoring technologies can benefit from the introduction and application of simple metrics for describing GV along with supporting recommendations.