Type 2 Diabetes and Glycemic Variability: Various Parameters in Clinical Practice

Olfactory function in diabetes mellitus

Diabetes mellitus (DM) is an increasingly common disease in both children and adults. In addition to neuronal and/or vascular disorders, it can cause chemosensory abnormalities including olfactory deterioration. The purpose of this article is to summarize current knowledge on olfactory function in DM, highlighting the impact of co-morbidities, especially obesity, thyroid dysfunction, chronic kidney disease and COVID-19 on olfactory outcomes. Research to date mostly shows that olfactory impairment is more common in people with diabetes than in the general population. In addition, the presence of concomitant diseases is a factor increasing olfactory impairment. Such a correlation was shown for type 1 diabetes, type 2 diabetes and gestational diabetes. At the same time, not only chronic diseases, but also DM in acute conditions such as COVID-19 leads to a higher prevalence of olfactory disorders during infection. Analyzing the existing literature, it is important to be aware of the limitations of published studies. These include the small number of patients studied, the lack of uniformity in the methods used to assess the sense of smell, frequently relying on rated olfactory function only, and the simultaneous analysis of patients with different types of diabetes, often without a clear indication of diabetes type. In addition, the number of available publications is small. Certainly, further research in this area is needed. From a practical point of view decreased olfactory performance may be an indicator for central neuropathy and an indication for assessing the patient's nutritional status, examining cognitive function, especially in older patients and performing additional diagnostic tests, such as checking thyroid function, because all those changes were correlated with smell deterioration.

Acute Glycemic Variability and Early Outcomes After Cardiac Surgery: A Meta-Analysis

The influence of acute glycemic variability (GV) on early outcomes of patients after cardiac surgery remains not fully determined. We performed a systematic review and meta-analysis to evaluate the association between acute GV and in-hospital outcomes of patients after cardiac surgery. Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library, and Web of Science. A randomized-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. Nine cohort studies involving 16 411 patients after cardiac surgery were included in this meta-analysis. Pooled results showed that a high acute GV was associated with an increased risk of major adverse events (MAE) during hospitalization for patients after cardiac surgery [odds ratio [OR]: 1.29, 95% CI: 1.15 to 1.45, p<0.001, I22=38%]. Sensitivity analysis limited to studies of on-pump surgery and GV evaluated by coefficient of variation of blood glucose showed similar results. Subgroup analysis suggested that a high acute GV was related to an increased incidence of MAE in patients after coronary artery bypass graft, but not for those after isolated valvular surgery (p=0.04), and the association was weakened after adjustment of glycosylated hemoglobin (p=0.01). Moreover, a high acute GV was also related to an increased risk of in-hospital mortality (OR: 1.55, 95% CI: 1.15 to 2.09, p=0.004; I22=0%). A high acute GV may be associated with poor in-hospital outcomes in patients after cardiac surgery.

Cross-sectional association of metrics derived from continuous glucose monitoring with cognitive performance in older adults with type 2 diabetes

AIM

To examine the association between continuous glucose monitoring (CGM)-derived metrics and cognitive performance in older adults with type 2 diabetes (T2D).

MATERIALS AND METHODS

A total of 100 outpatients with T2D aged 70 years or older were analysed. Participants underwent CGM for 14 days. As CGM-derived metrics, mean sensor glucose (SG), glucose coefficient of variation (CV), time in range (TIR; 70-180 mg/dl), time above range (TAR; > 180 mg/dl) and time below range (TBR; < 70 mg/dl), were calculated. Participants underwent cognitive tests, including the Japanese version of the Montreal Cognitive Assessment (MoCA-J), a delayed word-recall test from the Alzheimer's Disease Assessment Scale-cognitive subscale, a digit symbol substitution test, a letter word fluency test, a trail-making test (TMT) and digit span test (DSP).

RESULTS

In multiple regression analyses adjusted for confounders, a higher mean SG was associated with a lower performance in MoCA-J and TMT part B (TMT-B) (P < .05). A higher TAR was associated with a lower performance in TMT-B and DSP-backward (P < .05). By contrast, a higher TIR was associated with better function in TMT-B and DSP-backward (P < .05). Furthermore, CV and TBR were not associated with any cognitive function.

CONCLUSION

Hyperglycaemia metrics and TIR derived from CGM are associated with cognitive functions, especially with executive function and working memory, in older adults with T2D.

Endothelial Dysfunction and Platelet Hyperactivation in Diabetic Complications Induced by Glycemic Variability

The development and progression of the complications of chronic diabetes mellitus are attributed not only to increased blood glucose levels but also to glycemic variability. Therefore, a deeper understanding of the role of glycemic variability in the development of diabetic complications may provide more insight into targeted clinical treatment strategies in the future. Previously, the mechanisms implicated in glycemic variability-induced diabetic complications have been comprehensively discussed. However, endothelial dysfunction and platelet hyperactivation, which are two newly recognized critical pathogenic factors, have not been fully elucidated yet. In this review, we first evaluate the assessment of glycemic variability and then summarise the roles of endothelial dysfunction and platelet hyperactivation in glycemic variability-induced complications of diabetes, highlighting the molecular mechanisms involved and their interconnections.

Sodium Glucose Cotransporter-2 Inhibitor Protects Against Diabetic Neuropathy and Nephropathy in Modestly Controlled Type 2 Diabetes: Follow-Up Study

AIMS

This three-year follow-up study aimed to elucidate whether sodium-glucose cotransporter-2 inhibitors (SGLT2is) have any protection against diabetic neuropathy and nephropathy in patients with type 2 diabetes via reducing variability in glycemia and extraglycemic factors or their averages.

METHODS

Two type 2 diabetic cohorts of 40 and 73 patients treated with or without SGLT2i along with 60 control subjects were recruited. Two diabetic cohorts matched for HbA1c levels and oral hypoglycemic agents other than SGLT2is underwent glycemic control with or without SGLT2is more than two years. The urinary albumin to creatinine ratio (ACR), estimated glomerular filtration rate (eGFR) every 3 months and neuropathy outcome measures and mean Z-score of 8 neurophysiological tests were determined at the baseline and endpoint. Glycemic variability, evaluated by the coefficient of variation of monthly measured HbA1c levels and casual postprandial plasma glucose (CPPG), and coefficient of variation and average of extraglycemic parameters in diabetic cohorts were determined.

RESULTS

The glycemic variability and variability of some extraglycemic factors in SGLT2i cohort were smaller than those in non-SGLT2i cohort. However, only smaller coefficient of variation of HbA1c improved some neuropathy outcome measures, and ameliorated eGFR decline. SGLT2i improved the Z-score of neurophysiological tests. The optimized changes in the blood pressure, HDL-cholesterol and uric acid by SGLT2i led to neurological and renal protection. SGLT2i decreased the prevalence of nephropathy significantly and the prevalence of neuropathy insignificantly.

CONCLUSION

Over 3 years period, SGLT2i significantly improved some neuropathy outcome measures, mean Z-score of 8 neurophysiological tests, and attenuated nephropathy in modestly controlled type 2 diabetes by reducing glycemic variability and mean nonglycemic factors of diabetic microvascular complication.

Predictive Ability of Visit-to-Visit Variability of HbA1c Measurements for the Development of Diabetic Kidney Disease: A Retrospective Longitudinal Observational Study

AIMS

This study is aimed at clarifying the relationship between visit-to-visit variability of glycated hemoglobin (HbA1c) and the risk of diabetic kidney disease (DKD) and to identifying the most useful index of visit-to-visit variability of HbA1c.

METHODS

This clinic-based retrospective longitudinal study included 699 Japanese type 2 diabetes mellitus patients. Visit-to-visit variability of HbA1c was calculated as the internal standard deviation of HbA1c (HbA1c-SD), the coefficient of variation of HbA1c (HbA1c-CV), the HbA1c change score (HbA1c-HVS), and the area under the HbA1c curve (HbA1c-AUC) with 3-year serial HbA1c measurement data, and the associations between these indices and the development/progression of DKD were examined.

RESULTS

Cox proportional hazards models showed that the HbA1c-SD and HbA1c-AUC were associated with the incidence of microalbuminuria, independently of the HbA1c level. These results were verified and replicated in propensity score (PS) matching and bootstrap analyses. Moreover, the HbA1c-SD and HbA1c-AUC were also associated with oxidized human serum albumin (HSA), an oxidative stress marker.

CONCLUSIONS

Visit-to-visit variability of HbA1c was an independent risk factor of microalbuminuria in association with oxidative stress among type 2 diabetes mellitus patients. HbA1c-AUC, a novel index of HbA1c variability, may be a potent prognostic indicator in predicting the risk of microalbuminuria.

Determination of carbohydrates in the herbal antidiabetic mixtures by GC-MC

Due to the wide range of biologically active substances, the herbal mixtures can influence the development of diabetes mellitus and its complications. Carbohydrates attract particular attention due to their hypoglycemic, hypolipidemic, anticholesterolemic, antioxidant, antiinflammatory and detoxifying activities. The aim of this study was to investigate the content of carbohydrates through their monomeric composition in the herbal mixture samples: a) Urtica dioica leaf, Cichorium intybus roots, Rosa majalis fruits, Elymys repens rhizome, Taraxacum officinale roots, b) Arctium lappa roots, Elymys repens rhizome, Zea mays columns with stigmas, Helichrysum arenarium flowers, Rosa majalis fruits, c) Inula helenium rhizome with roots, Helichrysi arenarium flowers, Zea mays columns with stigmas, Origanum vulgare herb, Rosa majalis fruits, Taraxacum officinale roots, d) Cichorium intybus roots, Elymys repens rhizome, Helichrysum arenarium flowers, Rosa majalis fruits, Zea mays columns with stigmas and e) Urtica dioica leaf, Taraxacum officinale roots, Vaccinium myrtillus leaf, Rosa majalis fruits, Mentha piperita herb, which were used in Ukrainian folk medicine for the prevention and treatment of diabetes mellitus type 2.The carbohydrates were separated by gas chromatography-mass spectrometry after conversion into volatile aldononitrile acetate derivatives. The monomeric composition of polysaccharides was studied after their hydrolysis to form monosaccharides and poly-alcohols.Quantitative analyses of free carbohydrates showed that the predominant sugars were fructose, glucose and disaccharide - sucrose, in all samples. Concerning the determination of polysaccharide monomers after hydrolysis, glucose was the most abundant in all samples. The chromatographic study revealed a number of polyalcohols that are important for the treatment and prevention of progression of diabetes mellitus and its complications, namely, mannitol, pinitol and myo-inositol.

A New Stochastic Approach for Modeling Glycemic Disturbances in Type 2 Diabetes

OBJECTIVE

To improve insulin treatment in type 2 diabetes (T2D) using model-based control techniques, the underlying model needs to be individualized to each patient. Due to the impact of unknown meals, exercise and other factors on the blood glucose, it is difficult to utilize available data from continuous glucose monitors (CGMs) for model fitting and parameter estimation purposes.

METHODS

To overcome this problem, we propose a novel method for modeling the glycemic disturbances as a stochastic process. To differentiate meals from other glycemic disturbances, we model the meal intake as a separate stochastic process while encompassing all other disturbances in another stochastic process. Using particle filtering, we validate the model on simulations as well as on clinical data.

RESULTS

Based on simulated CGM data, the residuals generated by the particle filter are white, indicating a good model fit. For the clinical data, we use parameter values estimated based on fasting glucose data. The residuals obtained from clinical CGM data contain correlations up to lag 5.

CONCLUSION

The proposed model is shown to adequately describe the meal-induced glucose fluctuations in simulated CGM data while validations on clinical CGM data show promising results as well.

SIGNIFICANCE

The proposed model may lay the grounds for new ways of utilizing available CGM data, including CGM-based parameter estimation and stochastic optimal control.

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.

Long-Term Glycemic Variability Is Associated With Arterial Stiffness in Chinese Adults

OBJECTIVE

The aim of the study was to investigate the association between the visit-to-visit variability (VVV) of fasting plasma glucose (FPG) and arterial stiffness in Chinese adults.

METHODS

We performed a cohort study involving 2002 Chinese adults with no history of myocardial infarction or stroke. All the participants attended three visits (the baseline visit in 2008, the 2^nd visit in 2009 and the 3^rd visit in 2013). We used four measures to define the VVV of FPG across the three visits: the standard deviation (SD), the coefficient of variation (CV), the average successive variability (ASV) and the variability independent of the mean (VIM). We used brachial-ankle pulse wave velocity (ba-PWV) to measure arterial stiffness at the 2^nd and the 3^rd visits.

RESULTS

Compared with the lowest tertile of all the four measurements of VVV of FPG, significantly increased levels of ba-PWV change, ratio of ba-PWV change and the occurrence of the elevated ba-PWV were found in the highest tertile. The odds ratio (OR) and 95% confidence interval (CI) comparing participants in the highest tertile vs. the lowest tertile of FPG-SD was 1.37 (1.01-1.86) for risks of having elevated ba-PWV, even after adjustment for covariates including the mean FPG. Similar results were found for FPG-CV and FPG-VIM.

CONCLUSION

Greater long-term variability of FPG was associated with an increased risk of arterial stiffness, suggesting that the VVV of FPG could be used for an early detection of subclinical atherosclerosis.

"Comparison of cardiovascular autonomic activity (heart rate variability and baroreceptor sensitivity) in young healthy females during fasting and hyperglycaemia"

BACKGROUND AND AIM

The present study compared cardiovascular autonomic activity and reactivity during fasting (FS) and hyperglycemia (HS) states in young healthy females.

METHODS

This case crossover study was conducted on 30 females recruited by convenient sampling. Blood glucose levels were measured in FS and after oral glucose load i.e., HS. Finger arterial blood pressure (BP) and ECG were recorded constantly to monitor baroreceptor sensitivity (BRS) and heart rate variability (HRV). Autonomic reactivity was tested with deep breathing (DB), Valsalva manoeuvre (VM), and head-up-tilt (HUT) test under FS and HS. HRV parameters not normally distributed were natural log (ln) transformed.

RESULTS

Significantly reduced Valsalva ratio and higher heart rate and BP were observed in HS that continued during HUT (P < 0.05). The lnSDNN (standard deviation of normal-to-normal intervals) and lnRMSSD (root mean square of successive differences) were significantly lower (p < 0.05) in HS during HUT. After HUT, lnRMSSD remained lower (P = 0.031), whereas lnLF/HF (low frequency/high frequency power) ratio (P = 0.042) and LFnu (normalized units) (P = 0.024) were higher in HS. BRS was significantly lower in supine position in HS compared to FS and further reduced in HUT position in both FS and HS (P < 0.05).

CONCLUSION

Compared to FS, the HS exhibited heightened sympathetic activity with attenuation of parasympathetic activity and this phenomenon was further accentuated by HUT. BRS was more sensitive indicator of autonomic effects of hyperglycemia in resting state. In addition to standard tests, autonomic reactivity in vulnerable young subjects could be useful to detect autonomic imbalance at an early stage.

Glycemic variability and subsequent malignancies among the population without diabetes

BACKGROUND

Glycemic variability has been suggested to be related to some unfavorable outcomes, but malignancy development has not been evaluated. The aim of this study was to evaluate the association of glycemic variability with malignancy development among the population without diabetes.

METHODS

We conducted a retrospective cohort study at a large teaching hospital in Tokyo, Japan, from 2005 to 2016. We included all participants without diabetes who underwent voluntary health check-ups. Our outcome was the development of any malignancy. As a measure of glycemic variability, we calculated the quotient of CV in HbA1c and categorized subjects into quartile groups. A Cox proportional hazard model was applied, adjusting for patient demographics and social and family histories.

RESULTS

A total of 42,731 participants were included in this study; the mean age was 53.8 and 48.3% were male. During the median follow up of 2639 (interquartile range (IQR):1787-3662) days, 2435 participants (5.7%) developed malignancies. Participants who had larger glycemic variability (CV in HbA1c; hazard ratio (HR) 1.15, 95%confidence interval (CI):1.02-0.31 for the second quartile group; HR 2.20, 95%CI:1.95-2.48 for the third quartile group, HR 4.66, 95%CI:4.16-5.21 for the fourth quartile group, compared to first quartile group) had a significantly higher risk of malignancies.

CONCLUSION

We found an association between large glycemic variability and a high risk of future malignancies in a dose-dependent manner among people without diabetes. This finding suggests that maintaining a constant level of glucose may have favorable effects on cancer prevention in people without diabetes.

A View Beyond HbA1c: Role of Continuous Glucose Monitoring

Hemoglobin A1C (HbA1c) is used as an index of average blood glucose measurement over a period of months and is a mainstay of blood glucose monitoring. This metric is easy to measure and relatively inexpensive to obtain, and it predicts diabetes-related microvascular complications. However, HbA1c provides only an approximate measure of glucose control; it does not address short-term glycemic variability (GV) or hypoglycemic events. Continuous glucose monitoring (CGM) is a tool which helps clinicians and people with diabetes to overcome the limitations of HbA1c in diabetes management. Time spent in the glycemic target range and time spent in hypoglycemia are the main CGM metrics that provide a more personalized approach to diabetes management. Moreover, the glucose management indicator (GMI), which calculates an approximate HbA1c level based on the average CGM-driven glucose level, facilitates individual decision-making when the laboratory-measured HbA1c and estimated HbA1c are discordant. GV, on the other hand, is a measure of swings in blood glucose levels over hours or days and may contribute to diabetes-related complications. In addition, addressing GV is a major challenge during the optimization of glycemia. The degree of GV is associated with the frequency, duration, and severity of the hypoglycemic events. Many factors affect GV in a patient, including lifestyle, diet, the presence of comorbidities, and diabetes therapy. Recent evidence supports the use of some glucose-lowering agents to improve GV, such as the new ultra-long acting insulin analogs, as these agents have a smoother pharmacodynamic profile and improve glycemic control with fewer fluctuations and fewer nocturnal hypoglycemic events. These newer glucose-lowering agents (such as incretin hormones or sodium-glucose cotransporter 2 inhibitors) can also reduce the degree of GV. However, randomized trials are needed to evaluate the effect of GV on important diabetes outcomes. In this review, we discuss the role of HbA1c as a measure of glycemic control and its limitations. We also explore additional glycemic metrics, with a focus on time (duration) in glucose target range, time (duration) in hypoglycemia, GV, GMI, and their correlation with clinical outcomes.