Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Mo, Yifei; Lu, Jingyi; Zhou, Jian

doi:10.1111/jdi.14112

Cited by 7 publications

(1 citation statement)

References 90 publications

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“…This result suggests that GMI should be carefully interpreted in subjects with brittle glycemic control and frequent glycemic fluctuations. The use of CGM systems has recently provided valuable insights into short-term glucose variability patterns in T1D subjects, with emerging evidence suggesting glycemic variability as an independent risk factor for diabetes-related long-term complications and severe hypoglycemia [33]. Several cross-sectional studies examining CGM data in individuals with T1D have identified a correlation between increased glycemic variability metrics and the occurrence of retinopathy, elevated albuminuria, neuropathy, and coronary artery calcification, regardless of HbA1c levels [34].…”

Section: Discussionmentioning

confidence: 99%

Discordance between Glucose Management Indicator and Glycated Hemoglobin in a Pediatric Cohort with Type 1 Diabetes: A Real-World Study

Foti Randazzese,

Bombaci,

Costantino

et al. 2024

Children

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The introduction of continuous glucose monitoring (CGM) systems in clinical practice has allowed a more detailed picture of the intra- and interdaily glycemic fluctuations of individuals with type 1 diabetes (T1D). However, CGM-measured glucose control indicators may be occasionally inaccurate. This study aims to assess the discrepancy between the glucose management indicator (GMI) and glycated hemoglobin (HbA1c) (ΔGMI-HbA1c) within a cohort of children and adolescents with T1D, exploring its correlation with other CGM metrics and blood count parameters. In this single-center, cross-sectional study, we gathered demographic and clinical data, including blood count parameters, HbA1c values, and CGM metrics, from 128 pediatric subjects with T1D (43% female; mean age, 13.4 ± 3.6 years). Our findings revealed higher levels of the coefficient of variation (CV) (p < 0.001) and time above range > 250 mg/dL (p = 0.033) among subjects with ΔGMI-HbA1c > 0.3%. No association was observed between blood count parameters and ΔGMI-HbA1c. In conclusion, despite the advancements and the widespread adoption of CGM systems, HbA1c remains an essential parameter for the assessment of glycemic control, especially in individuals with suboptimal metabolic control and extreme glycemic variability.

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Section: Discussionmentioning

confidence: 99%

Discordance between Glucose Management Indicator and Glycated Hemoglobin in a Pediatric Cohort with Type 1 Diabetes: A Real-World Study

Foti Randazzese,

Bombaci,

Costantino

et al. 2024

Children

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Seasonal fluctuations of CGM metrics in individuals with type 1 diabetes using an intermittently scanned CGM device or sensor augmented pump

Oi-Yo,

Urai,

Yamamoto

et al. 2024

Endocrine

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Objective To elucidate the fluctuations in glucose levels measured using CGM-metrics during the four distinct seasons of the year in individuals with type 1 diabetes mellitus (T1DM) using an intermittently scanned CGM (isCGM) device or sensor augmented pump (SAP). Research design and methods This retrospective, single-center study enrolled 93 individuals with T1DM who were equipped with an isCGM device or SAP at Kobe University Hospital. The subjects had a median age of 47.0 years [interquartile range, 37.0–62.0 years], 25 individuals (26.9%) were male, median body mass index was 22.0 kg/m2 [20.8–23.8 kg/m2], and median hemoglobin A1c level was 7.4% [6.9–8.0%]. CGM data were reviewed from January to December 2019, and the mean sensor glucose (SG) value, time above range (TAR), time in range (TIR), time below range (TBR), and standard deviation (SD) of SG were calculated for each season (spring, March–May; summer, June–August; autumn, September–November; winter, December–February). Results Seasonal fluctuations were detected for mean SG, TAR, TIR, and SD, with TIR being lower and mean SG, TAR, and SD being higher in cold seasons (spring or winter) than in warm seasons (summer or autumn). Conclusion Seasonal fluctuations in CGM metrics should be taken into account in future studies performed to evaluate the favorable impact of CGM on glycemic management in individuals with T1DM.

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

Gale,

Haszard,

Peddie

2024

Diabetes Obesity Metabolism

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AimsTo 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 MethodsIn 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.ResultsTwenty‐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.ConclusionPerforming 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.

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Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Cited by 7 publications

References 90 publications

Discordance between Glucose Management Indicator and Glycated Hemoglobin in a Pediatric Cohort with Type 1 Diabetes: A Real-World Study

Discordance between Glucose Management Indicator and Glycated Hemoglobin in a Pediatric Cohort with Type 1 Diabetes: A Real-World Study

Seasonal fluctuations of CGM metrics in individuals with type 1 diabetes using an intermittently scanned CGM device or sensor augmented pump

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

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