Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review

Improved glycaemic control induced by evening activity breaks does not persist overnight amongst healthy adults: A randomized crossover trial

AIMS

To compare the effects of 4 hours of laboratory-based regular activity breaks (RABs) and prolonged sitting (SIT) on subsequent 48-h free-living interstitial glucose levels in a group of healthy adults.

MATERIALS AND METHODS

In this randomized crossover trial, participants completed two 4-h laboratory-based interventions commencing at ~5:00 pm: (1) SIT and (2) SIT interrupted with 3 min of body weight resistance exercise activity breaks every 30 min (RABs). Continuous glucose monitoring was performed during the intervention and for 48-h after, during which time participants returned to a free-living setting.

RESULTS

Twenty-eight adults (female n = 20, mean ± SD age 25.5 ± 5.6 years, body mass index 29.2 ± 6.9 kg/m2) provided data for this analysis. During the intervention period, RABs lowered mean interstitial glucose by 8.3% (-0.47 mmol/L/4 h, 95% confidence interval [CI] -0.74 to -0.20; p = 0.001) and area under the curve (AUC) by 8.9% (-2.01 mmol/L/4 h, 95% CI -3.05 to -0.97; p < 0.001) compared to SIT. Measures of glycaemic variability were not significantly different during the intervention. There were no significant differences in mean glucose and AUC between conditions during the first nocturnal period and 24-h post intervention. When compared to SIT, RABs increased continuous overall net action of glucose at 1 h and SD glucose by 22% (0.18 mmol/L, 95% CI 0.03 to 0.29; p = 0.018) and 26% (95% CI 4.9 to 42.7; p = 0.019) in the first nocturnal period and by 10% (0.09 mmol/L, 95% CI 0.01, 0.17; p = 0.025) and 15% (95% CI 6.6 to 22.4; p = 0.001) in the 24-h post intervention period, respectively.

CONCLUSION

Performing activity breaks in the evening results in acute reductions in interstitial glucose concentrations; however, the magnitude of these changes is not maintained overnight or into the following 48 hours.

Metabolic Dysregulation and Its Multifaceted Impact on Cardiovascular Autonomic Control in Type 2 Diabetes Mellitus: Insights From Comprehensive Assessment

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with a spectrum of metabolic dysfunctions that significantly elevate the risk of cardiovascular disorders. Understanding the intricate relationship between metabolic control and cardiovascular autonomic function in individuals with T2DM is crucial for effective management and the prevention of associated complications. This insight is foundational in developing targeted strategies that can mitigate the heightened cardiovascular risks inherent to this condition, thereby enhancing patient outcomes and quality of life.

AIM

The primary aim of the study was to explore the interconnections between various aspects of metabolic control in individuals with T2DM. This includes examining how glycemic variability, lipid profiles, body mass index (BMI), duration of diabetes, inflammatory markers, and cardiovascular autonomic function are interrelated.

METHODS

A cross-sectional study was conducted involving 100 individuals with T2DM and 100 control participants. HbA1C levels, glycemic variability, lipid profile, BMI, duration of diabetes, and inflammatory markers were assessed. Cardiovascular autonomic function parameters, including resting heart rate and blood pressure responses, were evaluated using standardized tests.

RESULTS

People with T2DM had significantly higher levels of glycosylated hemoglobin (HbA1C) compared to controls (mean difference = 2.95%, p < 0.001). Elevated HbA1C levels were correlated with increased resting heart rate (mean difference = 10 bpm, p < 0.001) and aberrant blood pressure responses during autonomic function assessments (p < 0.01 for systolic blood pressure; p < 0.05 for diastolic blood pressure). Glycemic variability (correlation coefficient (𝑟) = 0.75, p < 0.001) and dyslipidemia (elevated triglycerides and LDL cholesterol, reduced HDL cholesterol) were associated with cardiovascular autonomic dysfunction. Higher BMI values in T2DM individuals were independently correlated with alterations in autonomic function (𝑟 = 0.60, p < 0.001). The prolonged duration of diabetes was linked to greater impairment in autonomic function (mean decrease = 0.5 points per year, p < 0.01). In the T2DM group, higher levels of inflammatory markers (C-reactive protein and interleukin-6) were seen, which may have led to problems with the autonomic nervous system.

CONCLUSION

Metabolic dysregulation, such as high HbA1C levels, glycemic variability, dyslipidemia, obesity, having diabetes for a long time, and inflammation, is linked to cardiovascular autonomic dysfunction in T2DM. Early intervention targeting these metabolic abnormalities may mitigate the risk of cardiovascular complications in individuals with T2DM.

To What Extent Is HbA1c Associated with Glycemic Variability in Patients with Type 1 Diabetes? A Retrospective, Noninterventional Study

BACKGROUND

Glycemic variability (GV) is a novel parameter used in evaluating the quality of diabetes management. Current guidelines recommend the use of GV indexes alongside the traditional parameter to evaluate glycemic control: hemoglobin A1c (HbA1c). This study aims to evaluate the extent to which HbA1c explains the GV phenomena in patients with Type 1 diabetes (T1DM).

METHODS

In 147 patients with T1DM, associations between HbA1c and several GV indexes were analyzed.

RESULTS

Patients with an HbA1c < 7% had a lower median standard deviation of glycemia (60 vs. 48; p < 0.001), a lower coefficient of variation (34.1 vs. 38.0; p < 0.001), and a significantly increased median time in range (78 vs. 58; p < 0.001). HbA1c was positively correlated with the coefficient of variation (r = 0.349; p < 0.001) and the standard deviation (r = 0.656; p < 0.001) but reversely correlated with a lower time in range (r = -0.637; p < 0.001).

CONCLUSIONS

HbA1c only partially explains the GV phenomena in patients with T1DM. The HbA1c value is associated more strongly with the time in range and standard deviation than with the coefficient of variation.