Alternate glycemic markers reflect glycemic variability in continuous glucose monitoring in youth with prediabetes and type 2 diabetes

Glycemic variability assessed using continuous glucose monitoring in individuals without diabetes and associations with cardiometabolic risk markers: A systematic review and meta-analysis

BACKGROUND & AIMS

Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes.

METHODS

Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for ≥24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome.

RESULTS

Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease.

CONCLUSION

GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes.

Usefulness of glycated albumin level as a glycemic index complementing glycosylated hemoglobin in diabetic children and adolescents

PURPOSE

Glycated albumin (GA) is a glycemic marker reflecting the average serum glucose of the previous 2 weeks. This study aimed to evaluate the usefulness of GA as a glycemic index to complement glycosylated hemoglobin (HbA1c) in children and adolescents.

METHODS

Fifty-four children and adolescents with diabetes mellitus (DM) and 97 children and adolescents without DM (NDM) were enrolled. The correlation between mean blood glucose (MG) and GA compared to HbA1c was investigated in the DM group. The correlation between fasting glucose (FG) and GA compared to HbA1c was investigated in the NDM group. Factors affecting GA, HbA1c, and GA/HbA1c were analyzed.

RESULTS

In the DM group, positive correlations were observed between MG and GA (P=0.003), between MG and HbA1c (P=0.001), and between GA and HbA1c (P<0.001). The correlation coefficient between MG and GA did not differ from that between MG and HbA1c in the DM group (P=0.811). Among patients with DM, those whose standardized body mass index standard deviation score (BMI SDS) was ≥2 had a lower GA/HbA1c compared with those whose BMI SDS was <2 (P=0.001). In the NDM group, there were no significant correlations between FG and GA, between FG and HbA1c, or between GA and HbA1c. The NDM subjects whose BMI SDS was ≥2 had a lower GA/HbA1c than did the NDM subjects whose BMI SDS was <2 (P=0.003).

CONCLUSION

GA is comparable with HbA1c in reflecting glycemic control in children and adolescents with DM. GA is affected by obesity in children and adolescents with or without DM.

Continuous Glucose Monitoring in Children and Adolescents with Congenital Adrenal Hyperplasia

Objective

Patients with congenital adrenal hyperplasia (CAH) require lifelong therapy with glucocorticoids to suppress androgen excess and substitute for deficient cortisol. An important aspect of care is the prevention of metabolic sequelae. In infants, potentially lethal nocturnal hypoglycaemia has been described. In adolescence, visceral obesity, hypertension, hyperinsulinism and insulin resistance are reported. To date, systematic studies of glucose profiles in this age group with CAH are lacking.

Methods

This was a monocentric, prospective, observational study to determine the glucose profiles under different treatment regimens in a cohort of young patients with CAH. The continuous glucose monitoring device used was the latest generation FreeStyle Libre 3® sensor in blinded mode. Therapeutic and auxological data were obtained.

Results

The cohort consisted of 10 children/adolescents with a mean age of 11 years. Three patients exhibited morning fasting hyperglycaemia. Overall, 6 out of 10 patients had unacceptably few total values in the desired range of 70-120 mg/dL. Tissue glucose values above 140-180 mg/dL were found in 5 of 10 patients. The mean value for glycosylated haemoglobin for the cohort was of 5.8%. All pubertal adolescents with reverse circadian regimens had significantly higher glucose levels at night. Two adolescents showed asymptomatic nocturnal hypoglycaemia.

Conclusion

Most of the patients exhibited abnormalities in glucose metabolism. Two-thirds had elevated total 24h glucose values outside the age-appropriate reference values. Thus, this aspect may need to be addressed early in life by adjusting the doses, treatment regimen or dietary measures. Consequently, reverse circadian therapy regimens should be critically indicated and closely monitored due to the potential metabolic risk.

Glycemic dispersion: a new index for screening high glycemic variability

OBJECTIVE

For patients with diabetes, high-frequency and -amplitude glycemic variability may be more harmful than continuous hyperglycemia; however, there is still a lack of screening indicators that can quickly and easily assess the level of glycemic variability. The aim of this study was to investigate whether the glycemic dispersion index is effective for screening high glycemic variability.

METHODS

A total of 170 diabetes patients hospitalized in the Sixth Affiliated Hospital of Kunming Medical University were included in this study. After admission, the fasting plasma glucose, 2-hour postprandial plasma glucose, and glycosylated hemoglobin A1c were measured. The peripheral capillary blood glucose was measured seven times in 24 h, before and after each of three meals and before bedtime. The standard deviation of the seven peripheral blood glucose values was calculated, and a standard deviation of > 2.0 was used as the threshold of high glycemic variability. The glycemic dispersion index was calculated and its diagnostic efficacy for high glycemic variability was determined by the Mann-Whitney U test, receiver operating characteristic (ROC) curve and, Pearson correlation analysis.

RESULTS

The glycemic dispersion index of patients with high glycemic variability was significantly higher than that of those with low glycemic variability (p < 0.01). The best cutoff value of the glycemic dispersion index for screening high glycemic variability was 4.21. The area under the curve (AUC) was 0.901 (95% CI: 0.856-0.945) and had a sensitivity of 0.781 and specificity of 0.905. It was correlated with the standard deviation of blood glucose values (r = 0.813, p < 0.01).

CONCLUSIONS

The glycemic dispersion index had good sensitivity and specificity for screening high glycemic variability. It was significantly associated with the standard deviation of blood glucose concentration and is simple and easy to calculate. It was an effective screening indicator of high glycemic variability.

The performance of glycated albumin as a biomarker of hyperglycemia and cardiometabolic risk in children and adolescents in the United States

OBJECTIVE

Diabetes and prediabetes are growing concerns among US youth. Fasting glucose (FG) and HbA1c are standard diabetes screening tests, but HbA1c may be unreliable in some settings and fasting is burdensome in children. Glycated albumin (GA) is a non-fasting test that was recently cleared for clinical use in the United States, but studies in youth without diabetes are limited.

RESEARCH DESIGN AND METHODS

We conducted a cross-sectional analysis in 6826 youth without diabetes aged 8-19 years in the 1999-2004 National Health and Nutrition Examination Survey. We evaluated the associations of GA with HbA1c, FG, and cardiometabolic risk factors.

RESULTS

GA was poorly correlated with HbA1c (ρ = 0.074) and FG (ρ = -0.047) and was negatively associated with body mass index (BMI) and cardiometabolic risk factors. Compared to youth in the highest tertile of GA (≥13.5%), those in the lowest GA tertile (<12.4%) had a higher prevalence of obesity (29.9% vs. 7.6%), low high-density lipoprotein cholesterol (29.7% vs. 16.5%), and hypertensive blood pressure (4.0% vs. 2.7%). These inverse associations persisted after adjustment for age, sex, race/ethnicity, serum albumin, and C-reactive protein.

CONCLUSIONS

GA was poorly correlated with traditional markers of hyperglycemia in youth without diabetes. Counterintuitively, there was a negative association between GA and BMI. Among youth without diabetes, GA does not identify youth at high cardiometabolic risk, and it does not appear to be an appropriate biomarker for screening of hyperglycemia.

Continuous Glucose Monitoring in Adolescents With Obesity: Monitoring of Glucose Profiles, Glycemic Excursions, and Adherence to Time Restricted Eating Programs

Background

Randomized controlled trials of time restricted eating (TRE) in adults have demonstrated improvements in glucose variability as captured by continuous glucose monitors (CGM). However, little is known about the feasibility of CGM use in TRE interventions in adolescents, or the expected changes in glycemic profiles in response to changes in meal-timing. As part of a pilot trial of TRE in adolescents with obesity, this study aimed to 1) assess the feasibility of CGM use, 2) describe baseline glycemic profiles in adolescents with obesity, without diabetes, and 3) compare the difference between glycemic profiles in groups practicing TRE versus control.

Methods

This study leverages data from a 12-week pilot trial (ClinicalTrials.gov Identifier: NCT03954223) of late TRE in adolescents with obesity compared to a prolonged eating window. Feasibility of CGM use was assessed by monitoring 1) the percent wear time of the CGM and 2) responses to satisfaction questionnaires. A computation of summary measures of all glycemic data prior to randomization was done using EasyGV and R. Repeat measures analysis was conducted to assess the change in glycemic variability over time between groups. Review of CGM tracings during periods of 24-hour dietary recall was utilized to describe glycemic excursions.

Results

Fifty participants were enrolled in the study and 43 had CGM and dietary recall data available (16.4 + 1.3 years, 64% female, 64% Hispanic, 74% public insurance). There was high adherence to daily CGM wear (96.4%) without negative impacts on daily functioning. There was no significant change in the glycemic variability as measured by standard deviation, mean amplitude glycemic excursion, and glucose area under the curve over the study period between groups.

Conclusions

CGM use appears to be a feasible and acceptable tool to monitor glycemic profiles in adolescents with obesity and may be a helpful strategy to confirm TRE dosage by capturing glycemic excursions compared to self-reported meal timing. There was no effect of TRE on glucose profiles in this study. Further research is needed to investigate how TRE impacts glycemic variability in this age group and to explore if timing of eating window effects these findings.

Time in range correlates glycated albumin measured immediately after 2 weeks of continuous glucose monitoring

AIMS

Time in range (TIR), an index of glycemic control and also blood glucose fluctuation, obtained from continuous glucose monitoring (CGM), has been increasing its importance along with the spread of CGM in recent years. For a while, glycated albumin (GA) has been also used as a glycemic control index during about 2-weeks in routine clinical practice. It has not yet been confirmed under optimal condition whether TIR and GA correlates. Clarification of the correlation between TIR and GA, which was measured immediately after 2-weeks of CGM, might be a finding that further supports the utility of TIR.

METHODS

GA was measured at the conclusion of 2-week CGM in 71 diabetes outpatients at our hospital, and the correlation between GA and indices such as TIR obtained from CGM was statistically analyzed.

RESULTS

It was found that TIR and time above range (TAR) were significantly correlated with GA. Upon performing multiple regression analysis, TIR, TAR and BMI. indicated a significant regression coefficient with respect to GA.

CONCLUSIONS

These findings further support the utility of TIR as a marker of glycemic control that it might also be correlated with GA, and also suggest a relation between GA and blood glucose fluctuation.

Comparison of Premixed Human Insulin 30/70 to Biphasic Aspart 30 in Well-Controlled Patients with Type 2 Diabetes Using Continuous Glucose Monitoring

AIM

To compare in terms of glycemic variability two premixed insulins, Premixed Human Insulin 30/70 (PHI) and Biphasic Aspart 30 (BiAsp30), using Continuous Glucose Monitoring (CGM) and to estimate the correlation of Glycated Albumin (GA) and Fructosamine (FA) with CGM data. Patients-Data: A total of 36 well-controlled patients with type 2 Diabetes Mellitus (T2DM) underwent 7-day CGM with PHI and subsequently with BiAsp30. GA and FA were measured at the first and last day of each week of CGM.

RESULTS

BiAsp30 was associated with lower Average Blood Glucose (ABG) during the 23:00-03:00 period (PHI: 135.08 ± 28.94 mg/dL, BiAsp30: 117.75 ± 21.24 mg/dL, p < 0.001) and the 00:00-06:00 period (PHI: 120.42 ± 23.13 mg/dL, BiAsp30: 111.17 ± 14.74 mg/dL, p = 0.008), as well as with more time below range (<70 mg/dL) (TBR) during the 23:00-03:00 period in the week (PHI: 3.65 ± 5.93%, BiAsp30: 11.12 ± 16.07%, p = 0.005). PHI was associated with lower ABG before breakfast (PHI: 111.75 ± 23.9 mg/dL, BiAsp30: 128.25 ± 35.9 mg/dL, p = 0.013). There were no differences between the two groups in ABG, Time In Range and Time Below Range during the entire 24-h period for 7 days, p = 0.502, p = 0.534, and p = 0.258 respectively, and in TBR for the 00:00-06:00 period p = 0.253. Total daily insulin requirements were higher for BiAsp30 (PHI: 47.92 ± 12.18 IU, BiAsp30: 49.58 ± 14.12 IU, p = 0.001). GA and FA correlated significantly with ABG (GA: r = 0.512, p = 0.011, FA: r = 0.555, p = 0.005).

CONCLUSIONS

In well-controlled patients with T2DM, BiAsp30 is an equally effective alternative to PHI.

Starch digestibility modulation significantly improves glycemic variability in type 2 diabetic subjects: A pilot study

BACKGROUND AND AIMS

In type 2 diabetes (T2D) patients, the reduction of glycemic variability and postprandial glucose excursions is essential to limit diabetes complications, beyond HbA1c level. This study aimed at determining whether increasing the content of Slowly Digestible Starch (SDS) in T2D patients' diet could reduce postprandial hyperglycemia and glycemic variability compared with a conventional low-SDS diet.

METHODS AND RESULTS

For this randomized cross-over pilot study, 8 subjects with T2D consumed a controlled diet for one week, containing starchy products high or low in SDS. Glycemic variability parameters were evaluated using a Continuous Glucose Monitoring System. Glycemic variability was significantly lower during High-SDS diet compared to Low-SDS diet for MAGE (Mean Amplitude of Glycemic Excursions, p < 0.01), SD (Standard Deviation, p < 0.05), and CV (Coefficient of Variation, p < 0.01). The TIR (Time In Range) [140-180 mg/dL[ was significantly higher during High-SDS diet (p < 0.0001) whereas TIRs ≥180 mg/dL were significantly lower during High-SDS diet. Post-meals tAUC (total Area Under the Curve) were significantly lower during High-SDS diet.

CONCLUSION

One week of High-SDS Diet in T2D patients significantly improves glycemic variability and reduces postprandial glycemic excursions. Modulation of starch digestibility in the diet could be used as a simple nutritional tool in T2D patients to improve daily glycemic control. REGISTRATION NUMBER: in clinicaltrials.gov: NCT03289494.

Glycemic Variability and CNS Inflammation: Reviewing the Connection

Glucose is the primary energy source for the brain, and exposure to both high and low levels of glucose has been associated with numerous adverse central nervous system (CNS) outcomes. While a large body of work has highlighted the impact of hyperglycemia on peripheral and central measures of oxidative stress, cognitive deficits, and vascular complications in Type 1 and Type 2 diabetes, there is growing evidence that glycemic variability significantly drives increased oxidative stress, leading to neuroinflammation and cognitive dysfunction. In this review, the latest data on the impact of glycemic variability on brain function and neuroinflammation will be presented. Because high levels of oxidative stress have been linked to dysfunction of the blood-brain barrier (BBB), special emphasis will be placed on studies investigating the impact of glycemic variability on endothelial and vascular inflammation. The latest clinical and preclinical/in vitro data will be reviewed, and clinical/therapeutic implications will be discussed.

Exposure to Low Doses of Dechlorane Plus Promotes Adipose Tissue Dysfunction and Glucose Intolerance in Male Mice

The prevalence of type 2 diabetes (T2D) continues to increase worldwide. It is well established that genetic susceptibility, obesity, overnutrition and a sedentary life style are risk factors for the development of T2D. However, more recently, studies have also proposed links between exposure to endocrine-disrupting chemicals (EDCs) and altered glucose metabolism. Human exposure to environmental pollutants that are suspected to have endocrine disruptor activity is ubiquitous. One such chemical is Dechlorane Plus (DP), a flame retardant, that is now detected in humans and the environment. Here we show that exposure of mice to low, environmentally relevant doses of DP promoted glucose intolerance in mice fed a high-fat diet independent of weight gain. Furthermore, DP had pronounced effects on the adipose tissue, where it induced the development of hypertrophied white adipose tissue (WAT), and increased serum levels of resistin, leptin, and plasminogen activator inhibitor-1. In addition, DP exposure induced "whitening" of brown adipose tissue (BAT), and reduced BAT uncoupling protein 1 expression. Importantly, some of these effects occurred even when the mice were fed a regular, low-fat, diet. Finally, WAT adipogenic markers were reduced with DP treatment in the WAT. We also show that DP directly inhibited insulin signaling in murine adipocytes and human primary subcutaneous adipocytes in vitro. Taken together, our results show that the exposure to low and environmentally relevant levels of DP may contribute to the development of T2D.

The impact of shift work on glycemic characteristics assessed by CGM and its association with metabolic indices in non-diabetic subjects

AIM

To explore the glycemic characteristics of non-diabetic shift workers and associations with metabolic indices.

METHODS

In this cross-sectional study, 450 non-diabetic males, including 238 shift workers, aged 23-58 years, were recruited after a screening oral glucose tolerance test. Blood samples and anthropometric data were collected. Hundred and fifty of them finished a continuous glucose monitoring for 3-7 days.

RESULTS

Compared to daytime workers, shift workers presented with larger WHR (p < 0.001), higher HOMA-IR (p < 0.001), higher hs-CRP level (p < 0.001) and worse lipid profiles. In glycemic characteristics, shift workers with normal glucose regulation had a similar mean blood glucose (MBG), daytime MBG, percentage of time of hyperglycemia, hypoglycemia, euglycemia, and fluctuation parameters, including standard deviation of blood glucose (SDBG), mean amplitude of glycemic excursions (MAGE) and mean of daily differences (p > 0.05, respectively), while they had a higher nighttime MBG (p = 0.026) and blood glucose (BG) at 3 a.m. (p = 0.015). For subjects with impaired glucose regulation, both groups had no difference in any clinical characteristics or glycemic parameters (p > 0.05, respectively). Further regression analysis revealed the association between MBG/SDBG/MAGE/nighttime MBG/BG at 3 a.m. and age/WHR/hs-CRP/TC.

CONCLUSION

For non-diabetic shift workers, the glycemic characteristic was the elevated nighttime glycemia, presented as higher nighttime MBG and BG at 3 a.m. And both metrics were closely associated with central obesity. Elevated nighttime glycemia was an early signal of glucose metabolism disorder in shift workers.

Continuous subcutaneous insulin infusion combined with liraglutide reduced glycemic variability and oxidative stress in type 2 diabetes mellitus: a study based on the flash glucose monitoring system

We aimed to explore the use of the flash glucose monitoring (FGM) system in hospitalized newly diagnosed type 2 diabetes mellitus (T2DM) patients and to evaluate a new combination therapy of continuous subcutaneous insulin infusion (CSII) with or without liraglutide. This was an open-label, randomized study that was conducted in 60 newly diagnosed T2DM patients. The patients were randomized to receive either CSII (n = 30) or CSII + liraglutide (n = 30). The FGM system was used to assess the glycemic control and glycemic variability (GV) indices for 2 weeks. Mean blood glucose concentration (MBG), estimated hemoglobin A1c (HbA1c), and measures of GV, including the standard deviation of the mean glucose (SD), coefficient of variation (CV), interquartile range (IQR), mean amplitude of glycemic excursions (MAGE), largest amplitude of glycemic excursions (LAGE), and mean of daily difference (MODD) were compared between the two groups. Two oxidative stress biomarkers, 4-hydroxynonenal (4-HNE) and 8-hydroxydeoxyguanosine (8-OHdG), were measured before and after treatment. The estimated HbA1c and MBG decreased in both groups, especially the CSII + liraglutide group. SD, IQR, LAGE, and MODD were significantly lower in the CSII + liraglutide group than in the CSII group (all p < 0.05); there was no difference in CV or MAGE (p > 0.05). Similarly, the 4-HNE and 8-OHdG levels were significantly lower in the CSII + liraglutide group (p < 0.05). Our findings suggest that CSII with liraglutide was superior to CSII monotherapy in improving glycemic control and glycemic variability and in decreasing oxidative stress markers. Flash glucose monitoring can successfully provide ambulatory glucose profile data in the real world.

Polyherbal dietary supplementation for prediabetic adults: study protocol for a randomized controlled trial

Background

Prediabetes describes a state of hyperglycemia outside of normal limits that does not meet the criteria for diabetes diagnosis, is generally symptomless, and affects an estimated 38% of adults in the United States. Prediabetes typically precedes the diagnosis of type 2 diabetes, which accounts for increased morbidity and mortality. Although the use of dietary and herbal supplements is popular worldwide, and a variety of single herbal medicines have been examined for glycemic management, the potential of increasingly common polyherbal formulations to return glycemic parameters to normal ranges among adults with prediabetes remains largely unexplored. The purpose of this study is to evaluate the efficacy of a commercially available, polyherbal dietary supplement on glycemic and lipid parameters in prediabetic individuals.

Methods

In this multi-site, double-blinded, randomized controlled clinical trial, 40 participants with prediabetes will be randomized to either a daily oral polyherbal dietary supplement (GlucoSupreme™ Herbal; Designs for Health®, Suffield, CT, USA; containing cinnamon bark (Cinnamomum cassia), banaba leaf (Lagerstroemia speciosa standardized to 1% corosolic acid), kudzu root (Pueraria lobata standardized to 40% isoflavones), fenugreek seed (Trigonella foenum-graceum standardized to 60% saponins), gymnema leaf (Gymnema sylvestre standardized to 25% gymnemic acid), American ginseng root (Panax quinquefolius standardized to 5% ginsenosides), and berberine HCl derived from bark (Berberis aristata)) or placebo for 12 weeks. Short-, medium-, and comparatively long-term markers of glycemic control (blood glucose and fasting insulin, fructosamine, and glycated hemoglobin/A1c, respectively), and other glycemic parameters (GlycoMark, β-cell function, and insulin sensitivity/resistance) will be obtained. Lipid profile (total cholesterol, LDL, HDL, and triglycerides), inflammation (hs-CRP), progression to type 2 diabetes mellitus, as well as safety indices (ALT, AST) will be obtained. An intention-to-treat analysis will be used to assess changes in study outcomes.

Discussion

Treatment options for adults with prediabetes are currently limited. This study aims to evaluate the safety and efficacy of a commercially available dietary supplement in the popular, but as yet insufficiently studied, category of polyherbal formulas for the management of glycemic parameters and other biomarkers associated with prediabetes.

Trial registration

ClinicalTrials.gov, ID: NCT03388762. Retrospectively registered on 4 January 2018.

Electronic supplementary material

The online version of this article (10.1186/s13063-018-3032-6) contains supplementary material, which is available to authorized users.

Reduced insulin sensitivity is correlated with impaired sleep in adolescents with cystic fibrosis

BACKGROUND

Prevalence of cystic fibrosis-related diabetes (CFRD) rises sharply in adolescence/young-adulthood and is associated with increased morbidity/mortality. Sleep may be a modifiable risk factor for diabetes but its relationship with metabolic function has not been fully examined in youth with CF. The aim of the study was to examine the relationship between objectively measured sleep and glucose metabolism in youth with CF.

METHODS

Adolescents (43 with CF and 11 healthy controls) completed 1-week of concurrent home continuous glucose monitoring (CGM) and actigraphy. Fasting labs and an oral glucose tolerance test were obtained. T-tests and analysis of variance (ANOVA) were used to test differences between actigraphy outcomes in CF participants and controls. Spearman's rank correlation coefficients were used to test for correlations between actigraphy, CGM, and insulin sensitivity (IS) measures.

RESULTS

All participants averaged insufficient sleep (mean = 7.5 hours per night) compared to the 8 to 10 hours recommended for this age group. CF participants had poorer sleep by actigraphy measures than healthy controls. Higher minimum daytime glucoses on CGM correlated with shorter total sleep time (TST) and worse sleep efficiency (SE). Reduced IS in CF participants with dysglycemia was correlated with shorter TST, longer sleep latency, more wake after sleep onset, and poorer SE.

CONCLUSIONS

Poor sleep appears to correlate with higher blood glucose and lower IS in CF adolescents with dysglycemia. Further research is needed to better understand the mechanisms and directionality behind this relationship.

Hemoglobin A1c Accurately Predicts Continuous Glucose Monitoring-Derived Average Glucose in Youth and Young Adults With Cystic Fibrosis

OBJECTIVE

In cystic fibrosis (CF), hemoglobin A_1c (HbA_1c) is thought to underestimate glycemia. However, few studies have directly assessed the relationship between HbA_1c and average glucose in CF. We determined the relationships among glycemic markers-HbA_1c, fructosamine (FA), glycated albumin (%GA), and 1,5-anhydroglucitol (1,5-AG)-and continuous glucose monitoring (CGM) in CF, hypothesizing that alternate markers would better predict average sensor glucose (ASG) than HbA_1c.

RESEARCH DESIGN AND METHODS

CF participants and a group of healthy control subjects (HCs), ages 6-25 years, wore CGM for up to 7 days. Pearson correlations assessed the relationships between CGM variables and HbA_1c, FA, %GA, and 1,5-AG. The regression line between HbA_1c and ASG was compared in CF versus HC. Linear regressions determined whether alternate markers predicted ASG after adjustment for HbA_1c.

RESULTS

CF (n = 93) and HC (n = 29) groups wore CGM for 5.2 ± 1 days. CF participants were 14 ± 3 years of age and 47% were male, with a BMI z score -0.1 ± 0.8 and no different from HCs in age, sex, or BMI. Mean HbA_1c in CF was 5.7 ± 0.8% (39 ± 9 mmol/mol) vs. HC 5.1 ± 0.2% (32 ± 2 mmol/mol) (P < 0.0001). All glycemic markers correlated with ASG (P ≤ 0.01): HbA_1c (r = 0.86), FA (r = 0.69), %GA (r = 0.83), and 1,5-AG (r = -0.26). The regression line between ASG and HbA_1c did not differ in CF versus HC (P = 0.44). After adjustment for HbA_1c, %GA continued to predict ASG (P = 0.0009) in CF.

CONCLUSIONS

HbA_1c does not underestimate ASG in CF as previously assumed. No alternate glycemic marker correlated more strongly with ASG than HbA_1c. %GA shows strong correlation with ASG and added to the prediction of ASG beyond HbA_1c. However, we are not advocating use of HbA_1c for diabetes screening in CF based on these results. Further study will determine whether glycemic measures other than ASG differ among different types of diabetes for a given HbA_1c.

Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data

Many glycaemic variability (GV) indices extracted from continuous glucose monitoring systems data have been proposed for the characterisation of various aspects of glucose concentration profile dynamics in both healthy and non-healthy individuals. However, the inter-index correlations have made it difficult to reach a consensus regarding the best applications or a subset of indices for clinical scenarios, such as distinguishing subjects according to diabetes progression stage. Recently, a logistic regression-based method was used to address the basic problem of differentiating between healthy subjects and those affected by impaired glucose tolerance (IGT) or type 2 diabetes (T2D) in a pool of 25 GV-based indices. Whereas healthy subjects were classified accurately, the distinction between patients with IGT and T2D remained critical. In the present work, by using a dataset of CGM time-series collected in 62 subjects, we developed a polynomial-kernel support vector machine-based approach and demonstrated the ability to distinguish between subjects affected by IGT and T2D based on a pool of 37 GV indices complemented by four basic parameters-age, sex, BMI, and waist circumference-with an accuracy of 87.1%.

Use of Continuous Glucose Monitoring in Youth-Onset Type 2 Diabetes

PURPOSE OF REVIEW

Continuous glucose monitoring (CGM) technology has long been accepted as a tool for managing glycemia in type 1 diabetes (T1D) and is receiving increased attention as a tool for monitoring glucose patterns in patients with other forms of diabetes, in particular type 2 diabetes (T2D). Recent studies in adults with T2D have shown benefits of CGM in the investigation of glycemic variability, as well as utility as a tool for improving glycemic control. The literature on CGM use in youth-onset T2D, however, is sparse. This paper reviews the various roles for CGM in T2D, with a focus on published reports of CGM use in youth-onset T2D. The gaps in knowledge are highlighted, along with a discussion regarding need for future studies of potential applications for CGM in this younger population.

RECENT FINDINGS

CGM systems provide insight into glycemic abnormalities in obese youth with and at risk for T2D. This technology has enabled examination of the relationship between free-living glycemic profiles and traditional diabetes screening tests, as well as markers of cardiometabolic risk in this high-risk population. Investigators are incorporating CGM technology into the study of T2D in youth, but interventional studies of CGM as a tool for glycemic control in youth-onset T2D are limited. Youth with T2D face a more aggressive disease than adults with T2D, and further studies utilizing advances in glucose monitoring technology to improve outcomes in this population are needed.