Diabetes

Continuous Glucose Monitoring, Glycemic Control, and Diabetic Complications

Colby Stong
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In a 2006 meta-analysis published in JAMA investigating the impact of strategic quality improvement on glycemic control among adults with type 2 diabetes, researchers found that the use of multidisciplinary care teams, shared care between primary care physicians and specialists, and effective case management led to reductions in HbA1c by at least 0.5%.3 Additional positive outcomes of care team management include increased patient satisfaction, improved quality of life, fewer hospitalizations, decreased health care costs, and lower risks for diabetes complications.1
In a 2006 meta-analysis published in JAMA investigating the impact of strategic quality improvement on glycemic control among adults with type 2 diabetes, researchers found that the use of multidisciplinary care teams, shared care between primary care physicians and specialists, and effective case management led to reductions in HbA1c by at least 0.5%.3 Additional positive outcomes of care team management include increased patient satisfaction, improved quality of life, fewer hospitalizations, decreased health care costs, and lower risks for diabetes complications.1
Continuous glucose monitoring was compared to glycated hemoglobin (HbA1c) levels for the measurement of short-term glucose fluctuations.

Diabetes complications are associated with continuous glucose monitoring (CGM)–derived measures of intra-day glycemic variability, with time in range (TIR) the most consistent measure, according to a study in the Journal of Clinical Endocrinology and Metabolism.

The findings are based on a systematic literature search of PubMed and Embase from January 1, 2010 to August 22, 2020 of studies demonstrating direct links between CGM-derived metrics of glycemic management and diabetes-related complications.

A total of 34 studies with 20,852 participants were included in the analysis. Among the overall cohort, 663 had type 1 diabetes (T1D), 19,909 had type 2 diabetes (T2D), 192 had latent autoimmune diabetes of adulthood (LADA), and 88 were control participants without diabetes.

Nephropathy was addressed in 6 studies with 1563 participants. Of 5 studies that investigated albuminuria, 4 showed statistically significant associations with glycemic variability. The largest 2 studies (n = 866 and n = 281) found these associations with TIR.

Retinopathy was addressed in 6 studies with 6599 participants. Among 5 studies that assessed the presence of established retinopathy, 4 demonstrated statistically significant associations with glycemic variability, and the 2 largest studies (n = 3262 and n = 3119) found these associations for standard deviation (SD) of blood glucose levels (SD) and reduced TIR. Structural changes in T1D associated with changes in the retina were associated with glycemic variations, especially low blood glucose index.

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Glycemic variability markers, especially SD, mean amplitude of glycemic excursions (MAGE), and reduced TIR, were associated with peripheral neuropathy and abnormal nerve conduction in 7 studies.

Among 13 studies that addressed macrovascular disease (defined as cardiovascular, cerebrovascular, and peripheral vascular disease) the largest (n = 6225) prospective cohort study showed that TIR was associated with cardiovascular disease mortality and all-cause mortality. A total of 22 of 34 studies investigated associations between CGM metrics and diabetes complications after adjustment for HbA1c. Of the 22 studies, 19 found that some CGM metrics (MAGE, TIR, coefficient of variation for glucose [CV], and time-below-range [TBR]) remained associated with diabetes complications after adjustment for HbA1c. In addition, 5 studies found a glycemic variability metric to lose significance after adjustment for glycated hemoglobin (HbA1c).

The researchers noted several limitations, including a considerable heterogeneity among studies regarding selection of participants, treatment adjustments, and reporting of data. Therefore, a meta-analysis was not possible. In addition, 30 of the 34 studies were cross-sectional study designs, so causal relationships between CGM-derived measurements and outcomes could not be proven. Furthermore, many studies inferred the presence of disease from measuring risk factors or markers of disease rather than using definitive outcomes.

The investigators commented that although “higher glycemic variability and lower TIR tended to associate with diabetic complications, future research, particularly in the form of longitudinal studies, meta-analyses and randomized controlled trials are required to better evaluate relationships between these CGM-derived metrics and all diabetes complications, especially in type 1 diabetes. Future studies should also consider the impact of closed-loop pump therapy on the development of diabetes complications.”

Disclosure: One study author declared affiliations with several pharmaceutical companies. Please see the original reference for a full list of authors’ disclosures.

Reference

Yapanis M, James S, Craig ME, O’Neal D, Ekinci EI. Complications of diabetes and metrics of glycaemic management derived from continuous glucose monitoring. J Clin Endocrinol Metab. Published online January 30, 2022. doi: 10.1210/clinem/dgac034

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