The Fallacy of Average: How Using HbA1c Alone to Assess Glycemic Control Can Be Misleading

Post-Load Insulin Secretion Patterns are Associated with Glycemic Status and Diabetic Complications in Patients with Type 2 Diabetes Mellitus

BACKGROUND

To examine whether the different patterns of post-load insulin secretion can identify the heterogeneity of type 2 diabetes mellitus (T2DM).

METHODS

Six hundred twenty-five inpatients with T2DM at Jining No. 1 People's Hospital were recruited from January 2019 to October 2021. The 140 g steamed bread meal test (SBMT) was conducted on patients with T2DM, and glucose, insulin, and C-peptide levels were recorded at 0, 60, 120, and 180 min. To avoid the effect of exogenous insulin, patients were categorized into three different classes by latent class trajectory analysis based on the post-load secretion patterns of C-peptide. The difference in short- and long-term glycemic status and prevalence of complications distributed among the three classes were compared by multiple linear regression and multiple logistic regression, respectively.

RESULTS

There were significant differences in long-term glycemic status (e. g., HbA1c) and short-term glycemic status (e. g., mean blood glucose, time in range) among the three classes. The difference in short-term glycemic status was similar in terms of the whole day, daytime, and nighttime. The prevalence of severe diabetic retinopathy and atherosclerosis showed a decreasing trend among the three classes.

CONCLUSIONS

The post-load insulin secretion patterns could well identify the heterogeneity of patients with T2DM in short- and long-term glycemic status and prevalence of complications, providing recommendations for the timely adjustment in treatment regimes of patients with T2DM and promotion of personalized treatment.

Pancreas Transplantation: Current Challenges, Considerations, and Controversies

Pancreas transplantation (PTx) reestablishes an autoregulating source of endogenous insulin responsive to normal feedback controls. In addition to achieving complete β-cell replacement that frees the patient with diabetes from the need to monitor serum glucose and administer exogenous insulin, successful PTx provides counterregulatory hormone secretion and exocrine function. A functioning PTx mitigates glycemic variability, eliminates the daily stigma and burden of diabetes, restores normal glucose homeostasis in patients with complicated diabetes, and improves quality of life and life expectancy. The tradeoff is that it entails a major surgical procedure and requisite long-term immunosuppression. Despite the high likelihood of rendering patients euglycemic independent of exogenous insulin, PTx is considered a treatment rather than a cure. In spite of steadily improving outcomes in each successive era coupled with expansion of recipient selection criteria to include patients with a type 2 diabetes phenotype, a decline in PTx activity has occurred in the new millennium related to a number of factors including: (1) lack of a primary referral source and general acceptance by the diabetes care community; (2) absence of consensus criteria; and (3) access, education, and resource issues within the transplant community. In the author's experience, patients who present as potential candidates for PTx have felt as though they needed to circumvent the conventional diabetes care model to gain access to transplant options. PTx should be featured more prominently in the management algorithms for patients with insulin requiring diabetes who are failing exogenous insulin therapy or experiencing progressive diabetic complications regardless of diabetes type. Furthermore, all patients with diabetes and chronic kidney disease should undergo consideration for simultaneous pancreas-kidney transplantation independent of geography or location.

Low and high carbohydrate isocaloric diets on performance, fat oxidation, glucose and cardiometabolic health in middle age males

High carbohydrate, low fat (HCLF) diets have been the predominant nutrition strategy for athletic performance, but recent evidence following multi-week habituation has challenged the superiority of HCLF over low carbohydrate, high fat (LCHF) diets, along with growing interest in the potential health and disease implications of dietary choice. Highly trained competitive middle-aged athletes underwent two 31-day isocaloric diets (HCLF or LCHF) in a randomized, counterbalanced, and crossover design while controlling calories and training load. Performance, body composition, substrate oxidation, cardiometabolic, and 31-day minute-by-minute glucose (CGM) biomarkers were assessed. We demonstrated: (i) equivalent high-intensity performance (@∼85%VO2max), fasting insulin, hsCRP, and HbA1c without significant body composition changes across groups; (ii) record high peak fat oxidation rates (LCHF:1.58 ± 0.33g/min @ 86.40 ± 6.24%VO2max; 30% subjects > 1.85 g/min); (iii) higher total, LDL, and HDL cholesterol on LCHF; (iv) reduced glucose mean/median and variability on LCHF. We also found that the 31-day mean glucose on HCLF predicted 31-day glucose reductions on LCHF, and the 31-day glucose reduction on LCHF predicted LCHF peak fat oxidation rates. Interestingly, 30% of athletes had 31-day mean, median and fasting glucose > 100 mg/dL on HCLF (range: 111.68-115.19 mg/dL; consistent with pre-diabetes), also had the largest glycemic and fat oxidation response to carbohydrate restriction. These results: (i) challenge whether higher carbohydrate intake is superior for athletic performance, even during shorter-duration, higher-intensity exercise; (ii) demonstrate that lower carbohydrate intake may be a therapeutic strategy to independently improve glycemic control, particularly in those at risk for diabetes; (iii) demonstrate a unique relationship between continuous glycemic parameters and systemic metabolism.

Expert Consensus Recommendations on Time in Range for Monitoring Glucose Levels in People with Diabetes: An Indian Perspective

Keeping up with the global scenario, diabetes prevalence is on rise in India. Inadequate glycemic control is a major cause of diabetes-related morbidity and mortality. The conventional standards of care (SOC) in diabetes, including self-monitoring of blood glucose and measurement of glycated hemoglobin, have supported achievement of glycemic control, yet there are a few limitations. With the use of current technologies and metrics, such as continuous glucose monitoring (CGM) and standardized CGM data reporting, the continuous real-time glucose levels can be measured, and importantly, the percentage of time above, below, and within the target glucose range can be calculated, which facilitates patient-centric care, a current goal in diabetes management. International consensus recommendations endorse the incorporation of CGM and CGM data reporting in SOC for diabetes management. The guidelines provide time in range (TIR) thresholds for different patient populations and different types of diabetes. However, extrapolation of these global guidelines does not aptly cover the Indian population, which has diverse diet, culture, and religious practices. In this context, a consensus meeting was held in India in 2021 with experts in the field of diabetes care. The purpose of the meeting was to develop consensus recommendations for TIR thresholds for different patient profiles in India. Those expert recommendations, together with an evidence-based review, are reported here. The aim of this agreement is to aid clinicians across India to routinely use CGM and CGM data reports for optimizing individualized diabetes care, by implementing clinical targets for TIR.

Diabetic neuropathy: Past, present, and future

BACKGROUND

A sedentary lifestyle and an unhealthy diet have considerably increased the incidence of diabetes mellitus worldwide in recent decades, which has generated a high rate of associated chronic complications.

METHODS

A narrative review was performed in MEDLINE, EMBASES and SciELO databases, including 162 articles.

RESULTS

Diabetic neuropathy (DN) is the most common of these complications, mainly producing two types of involvement: sensorimotor neuropathy, whose most common form is symmetric distal polyneuropathy, and autonomic neuropathies, affecting the cardiovascular, gastrointestinal, and urogenital system. Although hyperglycemia is the main metabolic alteration involved in its genesis, the presents of obesity, dyslipidemia, arterial hypertension, and smoking, play an additional role in its appearance. In the pathophysiology, three main phenomena stand out: oxidative stress, the formation of advanced glycosylation end-products, and microvasculature damage. Diagnosis is clinical, and it is recommended to use a 10 g monofilament and a 128 Hz tuning fork as screening tools. Glycemic control and non-pharmacological interventions constitute the mainstay of DN treatment, although there are currently investigations in antioxidant therapies, in addition to pain management.

CONCLUSIONS

Diabetes mellitus causes damage to peripheral nerves, being the most common form of this, distal symmetric polyneuropathy. Control of glycemia and comorbidities contribute to prevent, postpone, and reduce its severity. Pharmacological interventions are intended to relieve pain.

Pathophysiology, Diagnostic Criteria, and Approaches to Type 2 Diabetes Remission

Diabetes mellitus is a prevalent, life-threatening, and costly medical illness. Type 2 diabetes is defined by insulin resistance caused by persistent hyperglycemia, and it is frequently diagnosed by tests such as fasting blood glucose levels of more than 7.0 mmol/L or HbA1c values of more than 6.5%. Pathogenesis and development of type 2 diabetes mellitus are clearly varied, with genetic and environmental factors both leading to it. The attainment of glycated hemoglobin (HbA1c) levels below the diagnostic level and maintaining it for a minimum of six months without pharmacotherapy, is described as diabetes remission. Diagnosis is a two-part procedure. To begin, the diagnosis of diabetes must be confirmed, and then the type of diabetes must be determined. Even in patients who succeeded to maintain remission, follow-up with the physician and regular tests should be done to prevent any expected diabetes complications.

TXNIP DNA methylation is associated with glycemic control over 28 years in type 1 diabetes: findings from the Pittsburgh Epidemiology of Diabetes Complications (EDC) study

INTRODUCTION

DNA methylation (DNAme) has been cross-sectionally associated with type 2 diabetes and hemoglobin A1c (HbA1c) in the general population. However, longitudinal data and data in type 1 diabetes are currently very limited. Thus, we performed an epigenome-wide association study (EWAS) in an observational type 1 diabetes cohort to identify loci with DNAme associated with concurrent and future HbA1cs, as well as other clinical risk factors, over 28 years.

RESEARCH DESIGN AND METHODS

Whole blood DNAme in 683 597 CpGs was analyzed in the Pittsburgh Epidemiology of Diabetes Complications study of childhood onset (<17 years) type 1 diabetes (n=411). An EWAS of DNAme beta values and concurrent HbA1c was performed using linear models adjusted for diabetes duration, sex, pack years of smoking, estimated cell type composition variables, and technical/batch covariates. A longitudinal EWAS of subsequent repeated HbA1c measures was performed using mixed models. We further identified methylation quantitative trait loci (meQTLs) for significant CpGs and conducted a Mendelian randomization.

RESULTS

DNAme at cg19693031 (Chr 1, Thioredoxin-Interacting Protein (TXNIP)) and cg21534330 (Chr 17, Casein Kinase 1 Isoform Delta) was significantly inversely associated with concurrent HbA1c. In longitudinal analyses, hypomethylation of cg19693031 was associated with consistently higher HbA1c over 28 years, and with higher triglycerides, pulse rate, and albumin:creatinine ratio (ACR) independently of HbA1c. We further identified 34 meQTLs in SLC2A1/SLC2A1-AS1 significantly associated with cg19693031 DNAme.

CONCLUSIONS

Our results extend prior findings that TXNIP hypomethylation relates to worse glycemic control in type 1 diabetes by demonstrating the association persists over the long term. Additionally, the associations with triglycerides, pulse rate, and ACR suggest TXNIP DNAme could play a role in vascular damage independent of HbA1c. These findings strengthen potential for interventions targeting TXNIP to improve glycemic control in type 1 diabetes through its role in SLC2A1/glucose transporter 1-mediated glucose regulation.

The influence of shorter red blood cell lifespan on the rate of HbA1c target achieved in type 2 diabetes patients with a HbA1c detection value lower than 7

BACKGROUND

Variations in the red blood cell (RBC) lifespan can affect glycosylated hemoglobin (HbA1c) test values, but there is still a lack of evidence regarding how and to what degree the RBC lifespan influences HbA1c in the type 2 diabetes mellitus (T2DM) population owing to the restriction of traditional RBC lifespan-detection means. This study aimed to investigate the influence of RBC lifespan variation on HbA1c values in T2DM patients with a HbA1c detection value lower than 7%.

METHODS

Patients with HbA1c <7% were divided into two groups: RBC lifespan <90 days and RBC lifespan ≥90 days. We collected blood glucose levels at seven time points for three consecutive months, assessed the HbA1c and glycosylated albumin levels, and calculated the hemoglobin glycation index (HGI) for each patient.

RESULTS

There were no statistical differences in the HbA1c value between two groups, but the estimated glycosylated hemoglobin (eHbA1c) was significantly higher in patients with an RBC lifespan <90 days. The proportion of the eHbA1c ≥7% in the group with an RBC lifespan <90 days was significantly higher than the other group (33.87% vs. 12.50%, p < .01). Pearson analysis showed a significant negative correlation between RBC lifespan and the HGI in patients with T2DM (r = -0.348, p < .01).

CONCLUSION

A reduced RBC lifespan in T2DM patients caused a noticeable underestimate of the blood glucose levels as presented by HbA1c detection value.

6. Glycemic Targets: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Making sense of glucose sensors in end-stage kidney disease: A review

Diabetes mellitus remains the leading cause of end-stage kidney disease worldwide. Inadequate glucose monitoring has been identified as one of the gaps in care for hemodialysis patients with diabetes, and lack of reliable methods to assess glycemia has contributed to uncertainty regarding the benefit of glycemic control in these individuals. Hemoglobin A1c, the standard metric to evaluate glycemic control, is inaccurate in patients with kidney failure, and does not capture the full range of glucose values for patients with diabetes. Recent advances in continuous glucose monitoring have established this technology as the new gold standard for glucose management in diabetes. Glucose fluctuations are uniquely challenging in patients dependent on intermittent hemodialysis, and lead to clinically significant glycemic variability. This review evaluates continuous glucose monitoring technology, its validity in the setting of kidney failure, and interpretation of glucose monitoring results for the nephrologist. Continuous glucose monitoring targets for patients on dialysis have yet to be established. While continuous glucose monitoring provides a more complete picture of the glycemic profile than hemoglobin A1c and can mitigate high-risk hypoglycemia and hyperglycemia in the context of the hemodialysis procedure itself, whether the technology can improve clinical outcomes merits further investigation.

Feasibility of Using a Factory-Calibrated Continuous Glucose Monitoring System to Diagnose Type 2 Diabetes

Context: Plasma glucose or A1C criteria can be used to establish the diagnosis of type 2 diabetes (T2D). Objective: We examined whether continuous glucose monitoring (CGM) data from a single 10-day wear period could form the basis of an alternative diagnostic test for T2D. Design: We developed a binary classification diagnostic CGM (dCGM) algorithm using a dataset of 716 individual CGM sensor sessions from 563 participants with associated A1C measurements from seven clinical trials. Data from 470 participants were used for training and 93 participants for testing (49 normoglycemic [A1C <5.7%], 27 prediabetes, and 17 T2D [A1C ≥6.5%] not using pharmacotherapy). dCGM performance was evaluated against the accompanying A1C measurement, which was assumed to provide the correct diagnosis. Results: The dCGM algorithm's overall sensitivity, specificity, positive predictive value, and negative predictive value were 71%, 93%, 71%, and 93%, respectively. At other clinically relevant A1C thresholds, dCGM specificity among normoglycemic participants was 98% (48/49 correctly classified), and for participants with suboptimally controlled diabetes (A1C ≥7%, above the American Diabetes Association recommended A1C goal) the sensitivity was 100% (8/8 participants correctly diagnosed with T2D). Conclusions: Classifications based on the dCGM algorithm were in good agreement with traditional methods based on A1C. The dCGM algorithm may provide an alternative method for screening and diagnosing T2D, and warrants further investigation.

Continuous Glucose Monitor, Insulin Pump, and Automated Insulin Delivery Therapies for Type 1 Diabetes: An Update on Potential for Cardiovascular Benefits

PURPOSE OF REVIEW

The incidence of type 1 diabetes (T1D) is rising in all age groups. T1D is associated with chronic microvascular and macrovascular complications but improving glycemic trends can delay the onset and slow the progression of these complications. Utilization of technological devices for diabetes management, such as continuous glucose monitors (CGM) and insulin pumps, is increasing, and these devices are associated with improvements in glycemic trends. Thus, device use may be associated with long-term prevention of T1D complications, yet few studies have investigated the direct impacts of devices on chronic complications in T1D. This review will describe common diabetes devices and combination systems, as well as review relationships between device use and cardiovascular outcomes in T1D.

RECENT FINDINGS

Findings from existing cohort and national registry studies suggest that pump use may aid in improving cardiovascular risk factors such as hypertension and dyslipidemia. Furthermore, pump users have been shown to have lower arterial stiffness and better measures of myocardial function. In registry and case-control longitudinal data, pump use has been associated with fewer cardiovascular events and reduction of cardiovascular disease (CVD) and all-cause mortality. CVD is the leading cause of morbidity and mortality in T1D. Consistent use of diabetes devices may protect against the development and progression of macrovascular complications such as CVD through improvement in glycemic trends. Existing literature is limited, but findings suggest that pump use may reduce acute cardiovascular risk factors as well as chronic cardiovascular complications and overall mortality in T1D.

Historical aspects of diagnosis and control of diabetes mellitus

Diabetes mellitus is a group of metabolic diseases affecting carbohydrate, lipid, and protein metabolism. This pathology has a long history, and it was considered a disease of the kidneys until the middle of the 19th century. Descriptions have been found in Egyptian papyri, in ancient Indian and Chinese medical literature, in the writings of ancient Greek and Arab doctors. Aretaeus of Cappadocia gave the first accurate description of the disease, coining the term diabetes. Thomas Willis first differentiated diabetes from other causes of polyuria by the sweet taste of urine. Matthew Dobson proved the presence of glucose in urine by evaporation. Claude Bernard demonstrated that hyperglycemia contributes to glucosuria. This is how the concept of the renal threshold appeared. In domestic practice, the term "renal threshold" was introduced by endocrinologist V.G. Baranov. The development of qualitative tests for determining glucose in the urine, the creation of test strips and glucometers has significantly improved the quality of life of patients with diabetes. The current stage of development of glucometry includes the determination of fasting plasma glucose, postprandial glycemia, glycated hemoglobin, as well as continuous glucose monitoring. Continuous glucose monitoring systems make it possible to estimate the time in target range, show the rate of rise or fall of glucose levels. It affects the rate and degree of carbohydrate metabolism compensation and allows for maximum control of the disease.

Association Between Time in Range and Postprandial Glucose Contribution Rate in Non-Insulin-Treated Type 2 Diabetes Patients: Inverse Correlation of Time in Range with Postprandial Glucose Contribution Rate

Background: Whether time in range (TIR), a parameter derived from continuous glucose monitoring (CGM), is a marker of postprandial hyperglycemia remains to be determined. In this study, we examined the association between TIR and postprandial glucose in non-insulin-treated type 2 diabetic patients. Methods: Our cross-sectional study included 729 non-insulin-treated patients with type 2 diabetes who underwent CGM without any changes in drug therapy on admission. The 24-h CGM record was analyzed for average glucose, standard deviation, percentage coefficient of variation, time above range, TIR, time below range, area under the curve (AUC) of basal glucose, AUC of postprandial glucose, and postprandial glucose contribution rate (%). The primary endpoint was the association between TIR and the postprandial glucose contribution rate. Results: We made TIR groups divided into 10% increments for a 7-group and compared with <40% to >90%. The basal and postprandial glucose AUCs correlated negatively with TIR. The postprandial glucose contribution rate correlated with TIR. The cutoff value for TIR, where postprandial glucose contribution rate was lower than the basal glucose contribution rate, was 66.3%. Conclusions: In non-insulin-treated type 2 diabetic patients, postprandial glucose AUC was higher in the high TIR group, whereas the basal glucose AUC was higher in the low TIR group. Good glycemic control can be achieved with therapeutic interventions that target postprandial glucose and basal glucose in patients with TIR ≥66.3% and <66.3%, respectively. University Medical Information Network [UMIN] ID: UMIN0000254333.

An Examination of the Glucose Management Indicator in Young Children with Type 1 Diabetes

BACKGROUND

Previous studies utilizing glucose data from continuous glucose monitors (CGM) to estimate the Glucose Management Indicator (GMI) have not included young children or determined appropriate GMI formulas for young children with type 1 diabetes (T1D).

METHODS

We extracted CGM data for 215 children with T1D (0-6 years) from a repository. We defined sampling periods ranging from the 3-27 days prior to an HbA1c measurement and compared a previously established GMI formula to a young child-specific GMI equation based on the sample's CGM data. We examined associations between HbA1c, GMI values, and other CGM metrics for each sampling period.

RESULTS

The young child-specific GMI formula and the published GMI formula did not evidence significant differences when using 21-27 days of CGM data. The young child-specific GMI formula demonstrated higher correlations to laboratory HbA1c when using 18 or fewer days of CGM data. Overall, the GMI estimate and HbA1c values demonstrate a strong relationship in young children with T1D.

CONCLUSIONS

Future research studies may consider utilizing the young child-specific GMI formula if the data collection period for CGM values is under 18 days. Further, researchers and clinicians may consider changing the default number of days of data used to calculate glycemic metrics in order to maximize validity of CGM-derived metrics.

Precision medicine in type 1 diabetes

First envisioned by early diabetes clinicians, a person-centred approach to care was an aspirational goal that aimed to match insulin therapy to each individual's unique requirements. In the 100 years since the discovery of insulin, this goal has evolved to include personalised approaches to type 1 diabetes diagnosis, treatment, prevention and prediction. These advances have been facilitated by the recognition of type 1 diabetes as an autoimmune disease and by advances in our understanding of diabetes pathophysiology, genetics and natural history, which have occurred in parallel with advancements in insulin delivery, glucose monitoring and tools for self-management. In this review, we discuss how these personalised approaches have improved diabetes care and how improved understanding of pathogenesis and human biology might inform precision medicine in the future.

Time in range, assessed with continuous glucose monitoring, is associated with brachial-ankle pulse wave velocity in type 2 diabetes: A retrospective single-center analysis

AIMS

The aim of this retrospective single-center is to research the relationship between time in range(TIR), an important novel metric of glycemic control, assessed with continuous glucose monitoring(CGM) and brachial-ankle pulse wave velocity(BaPWV), a unique index of systemic arterial stiffness in type 2 diabetes.

METHODS

Study participants included 469 hospitalized patients with type 2 diabetes and no history of serious cardiovascular disease who underwent CGM and BaPWV measurements. TIR of 3.9-10.0 mmol/L was evaluated with CGM. BaPWV was measured by non-invasive arteriosclerosis detector and high baPWV was defined as a mean baPWV≧1800m/s. The spearman correlation and the partial correlation analysis were applied to analyze the correlation between TIR and baPWV. The binary logistic regression was used to examine the independent association of TIR and high BaPWV.

RESULTS

The presence of high baPWV was 32.2%. Compared with patients of low baPWV, those with high baPWV had significantly reduced TIR(P<0.001). With the increase of TIR tertiles, the prevalence of high BaPWV progressively decreased. Correlation analysis showed that TIR is inversely correlated with BaPWV. In a fully adjusted model controlling for traditional risk factor of CVD, TIR is associated with the presence of high BaPWV independent of HbA1c.

CONCLUSION

TIR is correlated with BaPWV independent of HbA1c in patients with type 2 diabetes, confirming a link between TIR and arterial stiffness.

Long-term glycemic variability and risk of adverse health outcomes in patients with diabetes: A systematic review and meta-analysis of cohort studies

AIMS

To quantify associations of different metrics of long-term glycemic variability (GV) with multiple adverse diabetes-related outcomes.

METHODS

We searched PubMed and Embase from database inception to 23 August 2021. GV was based on measurements of HbA1c or fasting plasma glucose (FPG) and calculated by standard deviation (SD), coefficient of variance (CV) or other metrics. Outcomes included mortality, cardiovascular disease (CVD), renal disease, peripheral neuropathy, retinopathy, dementia and cancer. Random-effects meta-analyses were adopted to pool the relative risks (RRs).

RESULTS

Seventy-five articles with 2,051,701 participants were included. When comparing top with bottom quartiles, HbA1c variabilities were associated with all-cause mortality (RR_CV = 1.63, 95 % CI 1.37-1.92; RR_SD = 1.87, 1.55-2.26), CVD (RR_CV = 1.38, 1.07-1.78; RR_SD = 1.34, 1.12-1.59), renal disease (RR_CV = 1.43, 1.18-1.74; RR_SD = 1.44, 1.24-1.67), and peripheral neuropathy (RR_CV = 1.84, 1.40-2.43; RR_SD = 1.98, 1.51-2.61), but not retinopathy. FPG variabilities were associated with all-cause mortality (RR_CV = 1.59, 1.43-1.78; RR_SD = 1.67, 1.26-2.20), renal disease (RR_CV = 1.77, 1.32-2.38), and retinopathy (RR_CV = 1.92, 1.10-3.35), but not CVD and peripheral neuropathy. Associations of GV with Alzheimer's disease (RR_HbA1c-CV = 1.38, 1.13-1.70; RR_FPG-CV = 1.32, 1.07-1.63) and cancer (RR_HbA1c-SD = 2.19, 1.52-3.17; RR_FPG-CV = 3.64, 2.21-5.98) were each found significant in one study.

CONCLUSIONS

Long-term GV was associated with multiple adverse diabetes-related outcomes, while the strength of associations varied. The findings support the use of long-term GV for diabetes management in clinical practice.

The oxytocin signalling gene pathway contributes to the association between loneliness and cardiometabolic health

Increasing evidence has shown adverse effects of loneliness on cardiometabolic health. The neuromodulator and hormone oxytocin has traditionally been linked with social cognition and behaviour. However, recent implications of the oxytocin system in energy metabolism and the overrepresentation of metabolic issues in psychiatric illness suggests that oxytocin may represent a mechanism bridging mental and somatic traits. To clarify the role of the oxytocin signalling system in the link between cardiometabolic risk factors and loneliness, we calculated the contribution of single nucleotide polymorphisms (SNPs) in the oxytocin signalling pathway gene-set (154 genes) to the polygenic architecture of loneliness and body mass index (BMI). We investigated the associations of these oxytocin signalling pathway polygenic scores with body composition measured using body magnetic resonance imaging (MRI), bone mineral density (BMD), haematological markers, and blood pressure in a sample of just under half a million adults from the UK Biobank (BMD subsample n = 274,457; body MRI subsample n = 9796). Our analysis revealed significant associations of the oxytocin signalling pathway polygenic score for BMI with abdominal subcutaneous fat tissue, HDL cholesterol, lipoprotein(a), triglycerides, and BMD. We also found an association between the oxytocin signalling pathway polygenic score for loneliness and apolipoprotein A1, the major protein component of HDL. Altogether, these results provide additional evidence for the oxytocin signalling pathway's role in energy metabolism, lipid homoeostasis, and bone density, and support oxytocin's complex pleiotropic effects.

Variation of glucose time in range in type 1 diabetes

INTRODUCTION

The aim of the study was to assess the variation of glucose time in range (TIR) for persons with type 1 diabetes who perform intermittently scanned continuous glucose monitoring (isCGM).

METHODS

Glucose data for 8 weeks were analysed for 166 persons. TIR was calculated over four consecutive 2 weeks periods. Sixty-one of the persons had two downloads with an interval of >3 months.

RESULTS

A total of 140 individuals (84%) used multiple daily injection, and 26 (16%) used continuous insulin infusion. The within-individual standard deviation (SD) for TIR was 6.3% corresponding to 95% limits of agreement for the difference between two TIR values of ±17.6%. Mean TIR calculated from the first and last 2 weeks was 52.2 ± 17.1% and 53.7 ± 16.4%, respectively (difference 1.5%, SD of the difference 10.4%, p = .07). For persons with two downloads separated by months, the SD of the difference in TIR was 12.6%.

CONCLUSIONS

The 95% limit of agreement for TIR is vast for persons using isCGM. It is difficult to draw firm conclusions regarding systematic differences when individual TIR from 2 weeks are compared. This may not be valid for users of insulin pumps with closed-loop insulin delivery.

Improved CGM Glucometrics and More Visits for Pediatric Type 1 Diabetes Using Telemedicine During 1 Year of COVID-19

PURPOSE

The COVID-19 pandemic led to rapid adoption of telemedicine for the care of youth with type 1 diabetes (T1D). We assessed the utility of a primarily virtual care model by comparing glucometrics from a pediatric sample with T1D using continuous glucose monitoring (CGM) both before and during the pandemic.

METHODS

Pediatric patients aged 1 to 17 years with T1D duration ≥ 1 year if ≥ 6 years old or ≥ 6 months if < 6 years old, with ≥ 1 visit with recorded CGM data both prepandemic (April 1, 2019-March 15, 2020) and during the pandemic (April 1, 2020-March 15, 2021) were included. Data were extracted from the electronic health record.

RESULTS

Our sample comprised 555 young people (46% male, 87% White, 79% pump-treated), mean age 12.3 ± 3.4 years, T1D duration 5.9 ± 3.5 years, baseline glycated hemoglobin A1c 8.0 ± 1.0% (64 ± 10.9 mmol/mol). Diabetes visit frequency increased from 3.8 ± 1.7 visits/prepandemic period to 4.3 ± 2.2 visits/pandemic period (P < 0.001); during pandemic period, 92% of visits were virtual. Glucose management indicator (GMI) improved slightly from 7.9% (63 mmol/mol) prepandemic to 7.8% (62 mmol/mol) during the pandemic (P < 0.001). Those with equal or greater visit frequency (n = 437 [79% of sample]) had significant improvement in GMI (8.0% to 7.8% [64 to 62 mmol/mol], P < 0.001), whereas those with lower visit frequency did not (7.8 [62 mmol/mol], P = 0.86).

CONCLUSIONS

Children and adolescents with T1D using CGM before and during the pandemic showed an overall increase in visit frequency using primarily telemedicine-based care and improved CGM glucometrics. Further research is needed to understand factors associated with successful use of telemedicine for pediatric T1D.

Continuous Glucose Monitoring: An Opportunity for Population-Based Diabetes Management

The increasing prevalence of prediabetes and diabetes in the United States poses a serious threat to the health of the population. Closely associated with obesity, hypertension, dyslipidemia, and cardiovascular disease, a diagnosis of diabetes or prediabetes carries with it life-altering demands. Critically important among these is the requirement for frequent glucose level checks-typically performed with blood obtained from a fingerstick. Innovative real-time continuous glucose monitoring (rtCGM) technology makes it possible for patients and their clinicians to receive continuous glucose level measurements around the clock without finger sticks. Accruing evidence shows that rtCGM is an effective tool for patients and their clinicians in managing diabetes (ie, maintaining glucose levels within the recommended target range) and in understanding how lifestyle behaviors directly influence glucose levels. In recent years, a number of large payer organizations (eg, private health insurers, employers) have incorporated rtCGM in their diabetes management programs as a means of addressing the dual challenge of achieving/maintaining control of glucose levels and preventing or delaying the onset of complications. Programmatic integrated approaches have been used successfully and cost-effectively for managing other chronic conditions. Incorporating rtCGM in similar integrated approaches in diabetes management may be of value in improving quality outcomes and reducing costs on a population level. The evidence supports broader adoption and continued study to evaluate models that incorporate the use of rtCGM.

Metabolic syndrome associated with higher glycemic variability in type 1 diabetes: A multicenter cross-sectional study in china

AIMS

The comorbidity of metabolic syndrome (MetS) and type 1 diabetes mellitus (T1DM) is an obstacle to glucose control in patients with T1DM. We compared glycemic profiles using continuous glucose monitoring (CGM) systems in patients with T1DM with or without MetS.

METHODS

This was a multicenter cross-sectional study of patients with T1DM (N = 207) with or without MetS. CGM data were collected from study enrollment until discharge during a 1-week study session. We analyzed baseline HbA1c, average glucose, estimated HbA1c, time in range (TIR), time above range (TAR), time below range (TBR), coefficient of variation (CV), postprandial glucose excursions (PPGE) and other glycemic variability (GV) metrics. Logistic regression was developed to investigate the association between MetS and CGM metrics.

RESULTS

The results showed higher average baseline HbA1c levels, and a higher percentage of patients with baseline HbA1c levels ≥7.5%, in the T1DM with MetS group. Furthermore, MetS was associated with GV, which indicated a higher CV in patients with T1DM with MetS. However, our results showed that TAR, TIR, TBR and other GV metrics were comparable between the two groups. The T1DM with MetS group also had a higher proportion of patients with high CV (≥ 36%) than the group without MetS. In multivariable logistic regression analysis, the presence of MetS was a risk factor for high CV (≥ 36%) in our study participants.

CONCLUSIONS

T1DM patients with MetS in our study had better β-cell function. However, MetS was associated with worse glycemic control characterized by higher GV and HbA1c levels. Efforts should be expanded to improve treatment of MetS in patients with T1DM to achieve better glycemic control.

Comparing the effectiveness of continuous subcutaneous insulin infusion with multiple daily insulin injection for patients with type 1 diabetes mellitus evaluated by retrospective continuous glucose monitoring: A real-world data analysis

OBJECTIVE

Regarding the effects and practical application of insulin pumps on patients with type 1 diabetes mellitus (T1DM), the real-world evidence is limited especially concerning the incidence of hypoglycemia. This study aimed to compare the efficacy of continuous subcutaneous insulin infusion (CSII) therapy with multiple daily injection (MDI) therapy on glycemic metrics evaluated by retrospective continuous glucose monitoring (CGM) in Chinese patients with T1DM.

METHODS

In total, 362 T1DM Chinese patients from the outpatient department of the Second Xiangya Hospital, Central South University, who underwent intensive insulin therapy and used a retrospective CGM system were included in this retrospective cross-sectional study. Comprehensive analysis of clinical and biological features and retrospective CGM derived-metrics was performed on the 362 enrolled T1DM patients who underwent CSII (n = 61) or MDI (n = 301) therapy (defined as 4 or more insulin injections per day).

RESULTS

Our findings demonstrated that patients who underwent CSII therapy, compared with those who received MDI therapy, had lower levels of hemoglobin A1c (HbA1c) and fasting blood glucose; moreover, CSII therapy was associated with better glycemic outcomes in terms of increasing time in range (TIR), decreasing time above range (TAR), and achieving CGM-associated targets of TIR ≥70% and TAR <25%. However, patients who underwent CSII therapy did not experience decreasing time below range (TBR), achieving CGM-associated targets of TBR <4%, and reduction of the risk of hypoglycemia as evidenced by comparing TBR and low blood glucose index (LBGI) between the two treatment regimens. The parameters of glycemic variability, such as standard deviation of glucose (SD), mean amplitude glycemic excursion (MAGE), and large amplitude glycemic excursion (LAGE) in T1DM patients who underwent CSII therapy outperformed.

CONCLUSION

Our results provided further evidence that CSII therapy is safe and effective for management of Chinese T1DM patients, which was confirmed by a lower HbA1c level and better CGM-derived metrics but no demonstration of improvment in the risk of hypoglycemia. To achieve more satisfactory glycemic outcomes through the utilization of CSII therapy for Chinese T1DM patients, a strong physician-patient relationship is essential.

Impact of time in range during hospitalization on clinical outcomes in diabetic patients with toe amputation: a propensity score matching analysis

Purpose

In recent years, time in range (TIR), defined as a percentage within a target time range, has attracted much attention. This study was aimed to investigate the short-term effects of Time in Rang on diabetic patients undergoing toe amputation in a more specific and complete manner.

Methods

A retrospective analysis on patients with diabetic foot ulcer (DFU) treated by toe amputation or foot amputation at the First Affiliated Hospital of Wenzhou Medical University between January 2015 and December 2019 were evaluated. A 1:1 match was conducted between the TIR < 70% group and the TIR ≥ 70% group using the nearest neighbor matching algorithm. Data were analyzed using Chi-squared, Fisher’s exact, and Mann–Whitney U tests.

Results

Compared with patients in the TIR ≥ 70% group, patients in the TIR < 70% had a higher rate of re-amputation, and a higher rate of postoperative infection. Multivariate analysis revealed that smoking, lower extremity arterial disease and TIR < 70% were risk factors for surgery of re-amputation. The results of subgroup analysis found that the TIR < 70% was associated with a greater risk of re-amputation in patients with HbA1c < 7.5%, lower extremity arterial disease, and non-smokers.

Conclusions

TIR can be used as a short-term glycemic control indicator in patients with DFUs and should be widely accepted in clinical practice. However, a future multicenter prospective study is needed to determine the relationship between TIR and toe re-amputation in diabetic foot patients.

Cardiovascular Disease in Adults with Type 1 Diabetes: Looking Beyond Glycemic Control

PURPOSE OF REVIEW

Despite improvements in treatment, people with type 1 diabetes continue to have increased cardiovascular disease (CVD) risk. Glycemic control does not fully explain this excess CVD risk, so a greater understanding of other risk factors is needed.

RECENT FINDINGS

The authors review the relationship between glycemia and CVD risk in adults with type 1 diabetes and summarize evidence regarding other factors that may explain risk beyond glycemia. Insulin resistance, weight gain, sex differences, genetics, inflammation, emerging markers of risk, including lipid subclasses and epigenetic modifications, and future directions are discussed. As glycemic control improves, an increased focus on other CVD risk factors is warranted in type 1 diabetes. Novel markers and precision medicine approaches may improve CVD prediction, but a lack of type 1 diabetes-specific guidelines for lipids, blood pressure, and physical activity are likely impediments to optimal CVD prevention in this high-risk population.

Stepwise approach to continuous glucose monitoring interpretation for internists and family physicians

Continuous glucose monitoring (CGM) use has expanded rapidly in recent years among people with both type 1 and type 2 diabetes. In concert with the globally increasing prevalence of type 2 diabetes, the majority of whom receive diabetes care from internists or family physicians rather than specialists, it is becoming increasingly incumbent upon physicians within internal medicine and family practice to interpret and utilize CGM data in real-world clinical practice. It is therefore of paramount importance that internists and family physicians have access to the tools which will enable them to (1) interpret CGM data, and (2) utilize CGM data to guide therapeutic modifications for their patients with type 2 diabetes. Given the limited amount of time available to internists and family physicians to address multiple complex topics in a typical office visit, a pragmatic, simple, and systematic approach to CGM interpretation is crucial. This article aims to provide internists and family physicians with a simplified and systematic approach to CGM interpretation that can be easily and efficiently implemented in a brief office visit.

Monitoring of paediatric type 1 diabetes

PURPOSE OF REVIEW

This article reviews recent developments in methods used to monitor paediatric type 1 diabetes (T1D), including an examination of the role of glycated haemoglobin (haemoglobin A1c) and its limitations for long-term assessment of glycaemia in individual patients, self-monitoring of blood glucose, continuous glucose monitoring (CGM) systems and ketone monitoring.

RECENT FINDINGS

Monitoring of glycemia and ketones, when indicated, is a cornerstone of paediatric T1D management and is essential to optimize glycaemic control. Ongoing technological advancements have led to rapid changes and considerable improvement in the methods used to monitor glucose concentrations in people with T1D. As a result of recent innovations that have enhanced accuracy and usability, CGM is now considered the optimal method for monitoring glucose concentrations and should be introduced soon after diagnosis of T1D.

SUMMARY

Patients/families and healthcare providers must receive comprehensive education and proper training in the use of CGM and interpretation of the vast amounts of data. Future challenges include ensuring equal access to and optimizing clinical use of CGM to further improve T1D care and outcomes.

A Framework for Integrating Continuous Glucose Monitor-Derived Metrics into Economic Evaluations in Type 1 Diabetes

Economic models in type 1 diabetes have relied on a change in haemoglobin A1c as the link between the blood glucose trajectory and long-term clinical outcomes, including microvascular and macrovascular disease. The landscape has changed in the past decade with the availability of regulatory approved, accurate and convenient continuous glucose monitoring devices and their ability to track patients' glucose levels over time. The data emerging from continuous glucose monitoring have enriched the clinical understanding of the disease and indirectly of patients' behaviour. This has triggered the development of new measures proposed to better define the quality of glycaemic control, beyond haemoglobin A1c. The objective of this paper is to review recent developments in clinical knowledge brought into focus with the application of continuous glucose monitoring devices, and to discuss potential approaches to incorporate the concepts into economic models in type 1 diabetes. Based on a targeted review and a series of multidisciplinary workshops, an influence diagram was developed that captures newer concepts (e.g. continuous glucose monitoring metrics) that can be integrated into economic models and illustrates their association with more established concepts. How the additional continuous glucose monitoring-based indicators of glycaemic control may contribute to economic modelling beyond haemoglobin A1c, and more accurately reflect the economic value of novel type 1 diabetes treatments, is discussed.

Correlation between glucose measurement parameters of continuous flash monitoring and HbA1c. Real life experience in Asturias

INTRODUCTION

Despite continuous glucose monitoring having been proven useful in patients with type 1 diabetes mellitus, A1C remains the gold standard for assessing disease management.

MATERIAL AND METHODS

Descriptive, retrospective study which included 252 patients, 40.5% male, mean age 44.91±14.57 years, mean duration of diabetes 22.21±13.12 years, 88.1% on basal-bolus insulin therapy and 11.9% users of continuous subcutaneous insulin infusion. Glucose measurement, analytical and anthropometric data were obtained.

RESULTS

The mean time in range was 60.18±15.60% and was associated with A1C after adjusting for age, gender, duration of diabetes, BMI, insulin regimen, %CV and time below range (ß: -0.548; p<0.01). The glucose management indicator (GMI) was 7.19±0.69% and was also associated with A1C (ß: 0.957; p<0.01) regardless of age, gender, duration of diabetes, BMI, insulin treatment, %CV and time in range. The average difference between A1C and GMI was 0.17±0.65% (-2.70-3.40%), being higher as A1C increased, in a linear and significant manner, without being influenced by the duration of diabetes or CV.

CONCLUSIONS

Although we found a positive correlation between continuous glucose monitoring glucose measurement parameters and A1C, there is still not enough evidence to replace one parameter with another.

Blood Glucose Fluctuation in Older Adults with Diabetes Mellitus and End-Stage Renal Disease on Maintenance Hemodialysis: An Observational Study

INTRODUCTION

Patients with diabetes mellitus and end-stage renal disease are at a high risk of developing coronary, cerebrovascular, and peripheral vascular diseases. This study aimed to characterize hypoglycemia and blood glucose fluctuations associated with maintenance hemodialysis in older adult patients with diabetes mellitus and end-stage renal disease using a continuous glucose monitoring system.

METHODS

Seven patients were enrolled in this study, and 13 pairs of continuous glucose monitoring system data were collected. Each pair included data of 1 dialysis-on day and 1 dialysis-off day. Information on basic patient characteristics, including age, diabetes mellitus duration, hemodialysis duration, and proportions of hemoglobin A1c and glycated albumin, were collected. Differences in blood glucose fluctuation were compared between dialysis-on days and dialysis-off days.

RESULTS

The mean blood glucose on dialysis-on days (6.96 ± 2.57 mmol/L) was significantly lower than that on dialysis-off days (7.68 ± 2.31 mmol/L; P < 0.05). In contrast, the following parameters had significantly higher values (all P < 0.05) on dialysis-on days compared to dialysis-off days: large amplitude of glycemic excursion level (5.82 ± 2.86 mmol/L versus 4.21 ± 1.71 mmol/L), large amplitude of glycemic excursion level from 8 a.m. to 2 p.m. (3.6 ± 1.74 mmol/L versus 2.8 ± 1.33 mmol/L), mean amplitude of glycemic excursion level (4.78 ± 1.68 mmol/L versus 3.89 ± 1.67 mmol/L), mean amplitude of glycemic excursion level from 8 a.m. to 2 p.m. (4.01 ± 1.03 mmol/L versus 3.12. ± 0.97 mmol/L), standard deviation of blood glucose (1.55 ± 0.89 mmol/L versus 1.03 ± 0.4 mmol/L), and time below a target glucose range of less than 3.9 mmol/L (8.27% versus 4.25%).

CONCLUSION

Fluctuations in blood glucose levels were larger on dialysis-on days, particularly from the start of hemodialysis to 2 h post-hemodialysis, than on dialysis-off days. Hypoglycemia, as indicated by the time below a target glucose range of less than 3.9 mmol/L, occurred more frequently on dialysis-on days than on dialysis-off days.

Potential misclassification of diabetes and prediabetes in the U.S.: Mismatched HbA1c and glucose in NHANES 2005-2016

AIMS

To assess the prevalence and clinical implications of "mismatches" between HbA1c and glucose levels in the United States across the life course.

METHODS

Participants ages 12-79 years from U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2016 without known diagnosis of diabetes and who had a 75 g oral glucose tolerance test were included. Previously undiagnosed diabetes (DM), prediabetes, and normal glucose metabolism (NGM) were defined using American Diabetes Association cut-points. Mismatches were defined by the hemoglobin glycation index (HGI).

RESULTS

In 10,361 participants, 5% and 41% had diabetes and prediabetes, respectively, by fasting or 2-hour glucose criteria. By HbA1c criteria, the high HGI tertile consisted of mostly abnormal classification (3% DM, 52% prediabetes) and the low HGI tertile contained mostly normal classification (78% NGM). Across all ages, 15% (weighted: 30 million individuals) had clinically significant mismatches of HGI magnitude ≥+0.5% (i.e., high mismatch) or ≤-0.5% (low mismatch). Mismatch was most common in older adults and non-Hispanic Black participants.

CONCLUSIONS

Mismatches of clinically significant magnitude could lead to HbA1c-related misdiagnosis or inappropriate management in up to 30 million Americans. Older adults, non-Hispanic Black individuals, and others with high mismatches may benefit from complementing HbA1c with additional diagnostic and management strategies.

Insulin secretion and action affect glucose variability in the early stages of glucose intolerance

AIMS

Since it is unknown whether glucose variability (GV) is increased and whether this is related to worsening of insulin secretion and action in prediabetes, we have assessed insulin secretion and sensitivity, and daily GV in early stages of dysglycemia.

MATERIALS AND METHODS

Twenty subjects with normal glucose tolerance (NGT; age 45.0 ± 9.5 years; BMI 31.1 ± 6.4 kg/m2), 25 with NGT and 1hrOGTT>8.6 mmol/L (1hrOGTT; 45.7 ± 8.5 years; 32.4 ± 7.0 kg/m2), and 59 with isolated impaired glucose tolerance (iIGT; 47.7 ± 11.2 years; 31.3 ± 6.1 kg/m2) underwent OGTT and MMTT. CGM was performed with blinded FreeStyle Libre Pro for 24 h under standard conditions. Parameters of beta-cell function, insulin sensitivity and GV were calculated.

RESULTS

Overall insulin secretion and action as well as GV progressively worsened across glucose tolerance categories. On a matrix analysis, GV parameters were inversely related to ISSI-2; r = -0.37 to -0.52; p < 0.0001; and IGI; r = -0.28 to -0.48; p < 0.0001 for CV, SD, J-index, LI, HBGI and MAGE. Insulin secretion (IGI) and b-cell function (ISSI-2) emerged as independent contributors to GV in early stage of dysglycemia accounting for about 16%-38% of its variability.

CONCLUSIONS

Our results show that daily GV worsens already with mild impairment of glucose tolerance. The increase in GV is inversely related to insulin secretion and action.

Time in Range Assessed by Capillary Blood Glucose in Relation to Insulin Sensitivity and β-Cell Function in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study in China

AIMS

This study investigated the association of capillary blood glucose (CBG)-assessed time in range (TIR) (3.9-10.0 mmol/L) with insulin sensitivity and islet β-cell function (BCF).

MATERIALS AND METHODS

We recruited 455 patients with type 2 diabetes mellitus. Seven-point glucose-profile data (pre- and 120-min post-main meals, bedtime) were collected over three consecutive days. Plasma glucose and serum insulin concentrations were measured at 0, 60, and 120 min after a 100-g standard steamed bread meal test. The homeostasis model assessment of insulin resistance (HOMA-IR) and Matsuda index were computed to evaluate insulin resistance (IR). HOMA of β-cell function (HOMA-β) and the area under the curve between insulin and blood glucose (IAUC_0-120 /GAUC_0-120 ) were used to estimate BCF.

RESULTS

TIR was positively correlated with 60- and 120-min insulin values, IAUC_0-120 , the Matsuda index, HOMA-β, and IAUC_0-120 /GAUC_0-120 (r_s : 0.154, 0.129, 0.137, 0.194, 0.341, and 0.334, respectively; P <0.05) but inversely correlated with HOMA-IR (r_s : -0.239, P <0.001). After adjusting for confounders, multinomial multiple logistic regression analysis revealed that the odds ratios (ORs) of achieving the target TIR (>70%) increased by 12% (95% confidence interval [CI]: 3-21%), 7% (95% CI: 1-14%), 10% (95% CI: 5-16%), and 45% (95% CI: 25-68%) for each 10-mIU/L increase in 60- and 120-min insulin value, 10-unit increase in HOMA-β, and unit increase in IAUC_0-120 /GAUC_0-120 , respectively (P <0.05). Nevertheless, the OR decreased by 10% (95% CI: 1-18%) for each unit increase in HOMA-IR (P <0.05).

CONCLUSIONS

IR and BCF are related to CBG-assessed TIR.

Aging of glucose profiles in an adult population without diabetes

AIMS

This study aimed to determine the effect of aging on glucose profiles in a population without diabetes.

METHODS

We investigated the evolution of glucose profiles in an adult population without diabetes using continuous glucose monitoring (CGM) in two periods separated by 5 years. Anthropometrics, laboratory tests (HbA1c, fasting blood glucose) and CGM data (mean glycemia level, coefficient of variation, time in range) were measured in both periods to study the change in values over time.

RESULTS

125 participants (68% women) mean age 43.1 ± 12.4 years and classified as normoglycemic at baseline were included. Of the total population 15.2% had worsened glycemic status after 5 years, age and baseline glucose values (HbA1c and percentage of values above 175 mg/dL) were the variables related with this change. Related to CGM, we found that after 5 years there was a decrease in the percentage of values between 70 and 99 mg/dl (45.0% to 38.7%, p = 0.002) and an increase in the 100-139 mg/dL range (52.9% to 57.5% p = 0.016).

CONCLUSIONS

Our results indicate that in an adult population without diabetes there are changes in glucose profiles with aging highlighting the reduction of blood glucose values below 100 mg/dL.

Fifteen-minute consultation: Practical use of continuous glucose monitoring

Type 1 diabetes is a self-managed condition. Regular monitoring of blood glucose (BG) levels has been the cornerstone of diabetes management. Finger prick BG testing traditionally has been the standard method employed. More recently, rapid advancements in the development of continuous glucose monitoring devices have led to increased use of technology to help children and young people with diabetes manage their condition. These devices have the potential to improve diabetes control and reduce hypoglycaemia especially if used in conjunction with a pump to automate insulin delivery. This paper aims to provide an update on main CGM devices available and practical considerations for doctors if they come across a child with diabetes who is using one of these devices.

Glycemic control after switching to faster aspart in adults with type 1 diabetes

AIMS

Post-prandial hyperglycemia remains an unmet need in the management of type 1 diabetes (T1D). In randomized trials, faster insulin aspart (FIA) showed modest but significant reductions of glycemic spikes after meals. Whether such benefit is evident in routine clinical practice is unclear.

METHODS

We analyzed data of patients with T1D at the time they switched from a prior bolus insulin to FIA and at the first available follow-up. The primary endpoint was the change in the time spent in hyperglycemia > 250 mg/dl during daytime from flash glucose monitoring (FGM). Secondary outcomes included the change in HbA1c, body weight, insulin dose and other FGM metrics.

RESULTS

We included 117 patients with T1D on multiple daily injections who switched to FIA, 57 of whom had data from FGM. Patients were 41-year-old, 51.3% men, with 19.3 years diabetes duration and a baseline HbA1c of 7.7% (60 mmol/mol). Mean observation time was 4.3 months. After switching to FIA, HbA1c declined by 0.1% (1 mmol/mol) only in patients with baseline HbA1c > 7.0% (53 mmol/mol). Time spent in hyperglycemia > 250 mg/dl during daytime was significantly reduced from 14.8 to 11.9% (p = 0.006). Time in range improved from 48.3 to 51.0% (p = 0.028). Results were consistent across various patient characteristics.

CONCLUSIONS

Under routine care, patients with T1D who switched to FIA experienced a reduction in the time spent in hyperglycemia > 250 mg/dl during daytime and an increase in time in range. These improvements may be due to better control of post-prandial hyperglycemia, as observed in trials.

Analyzing outcomes following pancreas transplantation: Definition of a failure or failure of a definition

Pancreas transplantation has an identity crisis and is at a crossroads. Although outcomes continue to improve in each successive era, the number of pancreas transplants performed annually in the United States has been static for several years in spite of increasing numbers of deceased donors. For most practitioners who manage diabetes, pancreas transplantation is considered an extreme measure to control diabetes. With expanded recipient selection (primarily simultaneous pancreas-kidney transplantation) in patients who are older, have a higher BMI, are minorities, or who have a type 2 diabetes phenotype, the controversy regarding type of diabetes detracts from the success of intervention. The absence of a clear and precise definition of pancreas graft failure, particularly one that lacks a measure of glycemic control, inhibits wider application of pancreas transplantation with respect to reporting long-term outcomes, comparing this treatment to alternative therapies, developing listing and allocation policy, and having a better understanding of the patient perspective. It has been suggested that the definition of pancreas graft failure should differ depending on the type of pretransplant diabetes. In this commentary, we discuss current challenges regarding the development of a uniform definition of pancreas graft failure and propose a potential solution to this vexing problem.

Complications of Diabetes and Metrics of Glycemic Management Derived From Continuous Glucose Monitoring

CONTEXT

Although glycated hemoglobin A1c is currently the best parameter used clinically to assess risk for the development of diabetes complications, it does not provide insight into short-term fluctuations in glucose levels. This review summarizes the relationship between continuous glucose monitoring (CGM)-derived metrics of glycemic variability and diabetes-related complications.

EVIDENCE ACQUISITION

PubMed and Embase databases were searched from January 1, 2010 to August 22, 2020, using the terms type 1 diabetes, type 2 diabetes, diabetes-related microvascular and macrovascular complications, and measures of glycaemic variability. Exclusion criteria were studies that did not use CGM and studies involving participants who were not diabetic, acutely unwell (post stroke, post surgery), pregnant, or using insulin pumps.

EVIDENCE SYNTHESIS

A total of 1636 records were identified, and 1602 were excluded, leaving 34 publications in the final review. Of the 20 852 total participants, 663 had type 1 diabetes (T1D) and 19 909 had type 2 diabetes (T2D). Glycemic variability and low time in range (TIR) showed associations with all studied microvascular and macrovascular complications of diabetes. Notably, higher TIR was associated with reduced risk of albuminuria, retinopathy, cardiovascular disease mortality, all-cause mortality, and abnormal carotid intima-media thickness. Peripheral neuropathy was predominantly associated with standard deviation of blood glucose levels (SD) and mean amplitude of glycemic excursions (MAGE).

CONCLUSION

The evidence supports the association between diabetes complications and CGM-derived measures of intraday glycemic variability. TIR emerged as the most consistent measure, supporting its emerging role in clinical practice. More longitudinal studies and trials are required to confirm these associations, particularly for T1D, for which there are limited data.

The Emerging Role of Continuous Glucose Monitoring in the Management of Diabetic Peripheral Neuropathy: A Narrative Review

The aim of this narrative review is to present data on the role of continuous glucose monitoring (CGM) in the management of peripheral diabetic neuropathy (DPN) among individuals with type 1 and type 2 diabetes mellitus. Adequate glycaemic control is crucial to prevent the development or progression of DPN. CGM systems are valuable tools for improving glycaemic control and reducing glycaemic variability (GV). Chronic hyperglycaemia is known to be a risk factor for the development of diabetic microvascular complications, including DPN. In addition, there is now evidence that GV, evaluated by mean amplitude of glycaemic excursions, may be a novel factor in the pathogenesis of diabetic complications. Increased GV appears to be an independent risk factor for DPN and correlates with painful neuropathy. Similarly, time-in-range correlates positively with peripheral nerve function and negatively with sudomotor dysfunction. However, relevant studies are rather limited in scope, and the vast majority are cross-sectional and use different methodologies for the assessment of DPN. Therefore, the causal relationship between CGM-derived data and the development of DPN cannot be firmly established at the present time. It also remains to be elucidated whether CGM measures can be considered the new therapeutic targets for DPN management.

Level of Agreement and Correlation Between the Estimated Hemoglobin A1c Results Derived by Continuous or Conventional Glucose Monitoring Systems Compared with the Point-of-Care or Laboratory-Based Measurements: An Observational Study

INTRODUCTION

Hemoglobin A1C (HbA1c) is an important marker for diabetes care management. With the increasing use of new technologies such as continuous glucose monitoring (CGM) and point-of-care testing (POCT), patients and their physicians have been able to monitor and continuously check their blood glucose levels in an efficient and timely manner. This study aimed to investigate the level of agreement between the standard laboratory test for HbA1c (Lab-HbA1c) with point-of-care testing (POCT-HbA1c) and glucose monitoring index (GMI) derived by intermittently scanned CGM (isCGM) or estimated average glucose (eAG) derived by conventional self-monitored blood glucose (SMBG) devices.

METHODS

A cross-sectional study was conducted at the Diabetes Treatment Center, Prince Sultan Military Medical City, Saudi Arabia, between May and December 2020 with 81 patients with diabetes who used the isCGM system (n = 30) or conventional finger-pricking SMBG system (n = 51). At the same visit, venous and capillary blood samples were taken for routine HbA1c analysis by the standard laboratory and POCT methods, respectively. Also, for isCGM users, the GMI data for 28 days (GMI-28) and 90 days (GMI-90) were obtained, while for SMBG users, eAG data for 30 days (eAG-30) and 90 days (eAG-90) were calculated. The limits of agreement in different HbA1c measurements were evaluated using a Bland-Altman analysis. Pearson correlation and multivariate linear regression analyses were also performed.

RESULTS

Based on the Bland-Altman analysis, HbA1c levels for 96.7% and 96.1% of the patients analyzed by the POCT and the standard laboratory methods were within the range of the 95% limit of agreement in both isCGM and conventional SMBG users, respectively. About 93.3% of the GMI measurements were within the 95% limit of agreement. Also, about 94.12% of the eAG-30 and 90.2% of the eAG-90 measurements were within the 95% limit of agreement. Moreover, the correlation analysis revealed a statistically significant positive correlation and linear regression among Lab-HbA1c, POCT-HbA1c, GMI, and eAG in both conventional SMBG and isCGM users (all p < 0.001). These positive results persisted significantly after adjusting for different factors (all p < 0.001).

CONCLUSION

GMI derived by isCGM or eAG derived by conventional SMBG systems, as well as the POCT-HbA1c measurements, showed a high level of agreement; therefore, we recommend them as potential methods for diabetes monitoring, especially when a rapid result is needed or with patients with uncontrolled diabetes or on intensive insulin therapy.

Thrice daily consumption of a novel, premeal shot containing a low dose of whey protein increases time in euglycemia during 7 days of free-living in individuals with type 2 diabetes

INTRODUCTION

During acute feeding trials, consuming a large dose of whey protein (WP) before meals improves postprandial glucose regulation in people with type 2 diabetes. It is unclear if the reported benefits of premeal WP supplementation are translatable to everyday care or are associated with clinically meaningful, real-world glycemic outcomes. This study examined the application of a novel, premeal shot containing a low dose of WP on parameters of free-living glycemic control in people with type 2 diabetes.

RESEARCH DESIGN AND METHODS

In a randomized, placebo-controlled, single-blind crossover design, 18 insulin naive individuals with type 2 diabetes ((mean±SD) age, 50±6 years; HbA_1c (glycated hemoglobin), 7.4%±0.8%; duration of diabetes, 6±5 years) consumed a ready-to-drink WP shot (15 g of protein) or a nutrient-depleted placebo beverage 10 min before breakfast, lunch, and dinner over a 7-day free-living period. Free-living glucose control was measured by blinded continuous glucose monitoring and determined by the percentage of time spent above range (>10 mmol/L), in euglycemic range (3.9-10.0 mmol/L), below range (<3.9 mmol/L) and mean glucose concentrations.

RESULTS

Mealtime WP supplementation reduced the prevalence of daily hyperglycemia by 8%±19% (30%±25% vs 38%±28%, p<0.05), thereby enabling a 9%±19% (~2 hours/day) increase in the time spent in euglycemia (p<0.05). Mean 24-hour blood glucose concentrations were 0.6±1.2 mmol/L lower during WP compared with placebo (p<0.05). Similar improvements in glycemic control were observed during the waken period with premeal WP supplementation (p<0.05), whereas nocturnal glycemic control was unaffected (p>0.05). Supplemental compliance/acceptance was high (>98%), and no adverse events were reported.

CONCLUSIONS

Consuming a novel premeal WP shot containing 15 g of protein before each main meal reduces the prevalence of daily hyperglycemia, thereby enabling a greater amount of time spent in euglycemic range per day over 7 days of free-living in people with type 2 diabetes.

TRIAL REGISTRATION NUMBER

ISRCTN17563146; www.isrctn.com/ISRCTN17563146.

Metabolic control during the SARS-CoV-2 lockdown in a large German cohort of pediatric patients with type 1 diabetes: Results from the DPV initiative

OBJECTIVE

To assess if metabolic control worsened during the SARS-CoV2 lockdown in spring 2020 in youth with type 1 diabetes (T1D) in Germany.

METHODS

Data from 19,729 pediatric T1D patients from the diabetes prospective follow-up (DPV) registry were available. Data sets from four time-periods between January 1 and June 30, 2020, were compared with data from the whole year 2019 in the same patient; differences were adjusted for seasonality, increasing age, and longer diabetes duration. HbA1c values from laboratory measurements and estimates derived from continuous glucose monitoring (CGM) were aggregated into a combined glucose indicator (CGI), expressed in analogy to HbA1c.

RESULTS

Based on regression models adjusted for differences of sex, age, diabetes duration, and migratory background between the four time-periods, CGI values in 2020 were slightly higher than in 2019, for example, by 0.044% (0.042-0.046) (median [95% CI]) in the second lockdown month, time-period 3. Insulin dose and BMI-SDS were also marginally higher. In 2020, there were fewer hospitalizations (e.g., incidence risk ratio in time-period 3 compared with 2019: 0.52 [95% CI: 0.46-0.58]). In a subgroup of patients reporting CGM data in both years, metrics in 2020 improved: time in target increased, and mean sensor glucose fell, for example, by 2.8% (2.7-2.9), and by 4.4 mg/dl (4.3-4.6) in time-period 3.

CONCLUSION

Before, during, and after the lockdown in spring 2020, metabolic control in youth with T1D in Germany did not differ significantly from the preceding year. Further effects of the ongoing pandemic on pediatric T1D patients need to be evaluated.

HbA1c and Glucose Management Indicator Discordance Associated with Obesity and Type 2 Diabetes in Intermittent Scanning Glucose Monitoring System

Glucose management indicator (GMI) is frequently used as a substitute for HbA1c, especially when using telemedicine. Discordances between GMI and HbA1c were previously mostly reported in populations with type 1 diabetes (T1DM) using real-time CGM. Our aim was to investigate the accordance between GMI and HbA1c in patients with diabetes using intermittent scanning CGM (isCGM). In this retrospective cross-sectional study, patients with diabetes who used isCGM >70% of the time of the investigated time periods were included. GMI of four different time spans (between 14 and 30 days), covering a period of 3 months, reflected by the HbA1c, were investigated. The influence of clinical- and isCGM-derived parameters on the discordance was assessed. We included 278 patients (55% T1DM; 33% type 2 diabetes (T2DM)) with a mean HbA1c of 7.63%. The mean GMI of the four time periods was between 7.19% and 7.25%. On average, the absolute deviation between the four calculated GMIs and HbA1c ranged from 0.6% to 0.65%. The discordance was greater with increased BMI, a diagnosis of T2DM, and a greater difference between the most recent GMI and GMI assessed 8 to 10 weeks prior to HbA1c assessment. Our data shows that, especially in patients with increased BMI and T2DM, this difference is more pronounced and should therefore be considered when making therapeutic decisions.

Factors associated with glycemic variability in children with type 1 diabetes mellitus based on flash glucose monitoring system

OBJECTIVES

Patients with classical type 1 diabetes mellitus (T1DM) require lifelong dependence on exogenous insulin therapy due to pancreatic beta-cell destruction and absolute insulin deficiency. T1DM accounts for about 90% of children with diabetes in China, with a rapid increase in incidence and a younger-age trend. Epidemiological studies have shown that the overall glycated haemoglobin (HbA1c) and compliance rate are low in Chinese children with T1DM. Optimal glucose control is the key for diabetes treatment, and maintaining blood glucose within the target range can prevent or delay chronic vascular complications in patients with T1DM. Therefore, this study aims to investigate the glycemic control of children with T1DM from Hunan and Henan Province with flash glucose monitoring system (FGMS), and to explore factors associated with glycemic variability.

METHODS

A total of 215 children with T1DM under 14 years old were enrolled continuously in 16 hospitals from August 2017 to August 2020. All subjects wore a FGMS device to collect glucose data. Correlation of HbA1c, duration of diabetes, or glucose scan rates with glycemic variability was analyzed. Glucose variability was compared according to the duration of diabetes, HbA1c, glucose scan rates and insulin schema.

RESULTS

HbA1c and duration of diabetes were positively correlated with mean blood glucose, standard deviation of glucose, mean amplitude of glucose excursions (MAGE), and coefficient of variation (CV) of glucose (all P<0.01). The glucose scan rates during FGMS wearing was significantly positively correlated with time in range (TIR) (P=0.001) and negatively correlated with MAGE and mean duration of hypoglycemia (all P<0.01). Children with duration ≤1 year had lower time below range (TBR) and MAGE when compared with those with duration >1 year (all P<0.05). TIR and TBR in patients with HbA1c ≤7.5% were higher (TIR: 65% vs 45%, TBR: 5% vs 4%, P<0.05), MAGE was lower (7.0 mmol/L vs 9.4 mmol/L, P<0.001) than those in HbA1c >7.5% group. Compared to the multiple daily insulin injections group, TIR was higher (60% vs 52%, P=0.006), MAGE was lower (P=0.006) in the continuous subcutaneous insulin infusion group. HbA1c was lower in the high scan rates (≥14 times/d) group (7.4% vs 8.0%, P=0.046), TIR was significantly higher (58% vs 47%, P<0.001), and MAGE was lower (P<0.001) than those in the low scan rate (<14 times/d) group.

CONCLUSIONS

The overall glycemic control of T1DM patients under 14 years old in Hunan and Henan Province is under a high risk of hypoglycemia and great glycemic variability. Shorter duration of diabetes, targeted HbA1c, higher glucose scan rates, and CSII are associated with less glycemic variability.

Remote Pharmacist-Assisted Flash Continuous Glucose Monitoring Improves Glycemic Outcomes in Patients With Poorly Controlled Diabetes: A Retrospective Case Series

This article reports on a retrospective case series evaluating glycemic outcomes using a flash continuous glucose monitoring (CGM) system in pharmacist-managed diabetes cases. The flash CGM system was used during initial assessment of patients' diabetes control and then continued throughout the intervention to ensure the safety and efficacy of the glycemic interventions. The Cloud-based CGM software was used to monitor patients remotely and assess their glycemic metrics. Action plans were created to address areas of most pressing concern, ensuring reduction or elimination of hypoglycemia, correction of hyperglycemia, and minimization of glycemic variability. In these complex cases, use of the flash CGM system in conjunction with lifestyle and medication interventions safely and effectively improved diabetes management and achieved targeted glucose outcomes.

Continuous Glucose Monitoring Profiles in Healthy, Nondiabetic Young Children

Context

Continuous glucose monitoring (CGM) is increasingly being used for both day-to-day management in patients with diabetes and in clinical research. While data on glycemic profiles of healthy, non-diabetic individuals exists, data on non-diabetic very young children are lacking.

Objective

To establish reference sensor glucose ranges in healthy, non-diabetic young children, using a current generation CGM sensor.

Design

Prospective observational study

Setting

Institutional practice

Participants

Healthy, non-diabetic children 1-6 years old; with normal body mass index

Intervention

A blinded Dexcom G6 Pro CGM was worn for approximately 10 days by each participant.

Main Outcome Measure

CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability

Results

39 participants were included in the analyses. Mean average glucose was 103 mg/dL (5.7 mmol/L). Median % time between 70-140 mg/dL (3.9-7.8 mmol/L) was 96% (IQR 92%-97%), mean within-individual coefficient of variation was 17±3%, median time spent with glucose levels &gt;140mg/dL was 3.4% (49 min/day), and median time &lt;70 mg/dL (3.9 mmol/L) was 0.4% (6 min/day).

Conclusions

Collecting normative sensor glucose data and describing glycemic measures for young children fills an important informational gap and will be useful as a benchmark for future clinical studies.