Glycemic Variability Assessment with a 14-Day Continuous Glucose Monitoring System: When and How Long to Measure MAGE (Mean Amplitude of Glucose Excursion) for Optimal Reliability?

Enhancement of Ambulatory Glucose Profile for Decision Assistance and Treatment Adjustments

The ambulatory glucose profile (AGP) lacks sufficient statistical metrics and insightful graphs; indeed, it is missing important information on the temporal patterns of glucose variations. The AGP graph is difficult to interpret due to the overlapping metrics and fluctuations in glucose levels over 14 days. The objective of this proposed work is to overcome these challenges, specifically the lack of insightful information and difficulty in interpreting AGP graphs, to create a platform for decision assistance. The present work proposes 20 findings built from decision rules that were developed from a combination of AGP metrics and additional statistical metrics, which have the potential to identify patterns and insightful information on hyperglycemia and hypoglycemia. The "CGM Trace" webpage was developed, in which insightful metrics and graphical representations can be used to make inferences regarding the glucose data of any user. However, doctors (endocrinologists) can access the "Findings" tab for a summarized presentation of their patients' glycemic control. The findings were implemented for 67 patients' data, in which the data of 15 patients were collected from a clinical study and the data of 52 patients were gathered from a public dataset. The findings were validated by means of MANOVA (multivariate analysis of variance), wherein a p value of < 0.05 was obtained, depicting a strong significant correlation between the findings and the metrics. The proposed work from "CGM Trace" offers a deeper understanding of the CGM data, enhancing AGP reports for doctors to make treatment adjustments based on insightful information and hidden patterns for better diabetic management.

How to Measure Glycemic Variability? A Literature Review

Optimal glycemic control without the presence of diabetes-related complications is the primary goal for adequate diabetes management. Recent studies have shown that hemoglobin A1c level cannot fully evaluate diabetes management as glycemic fluctuations are demonstrated to have a major impact on the occurrence of diabetes-related micro- and macroangiopathic comorbidities. The use of continuous glycemic monitoring systems allowed the quantification of glycemic fluctuations, providing valuable information about the patients' glycemic control through various indicators that evaluate the magnitude of glycemic fluctuations in different time intervals. This review highlights the significance of glycemic variability by describing and providing a better understanding of common and alternative indicators available for use in clinical practice.

Influence of dipeptidyl peptidase-4 inhibitors on glycemic variability in patients with type 2 diabetes: A meta-analysis of randomized controlled trials

OBJECTIVE

The influence of dipeptidyl peptidase-4 (DPP4) inhibitors on glycemic variability compared to other oral antidiabetic drugs (OADs), measured based on the mean amplitude of glycemic excursions (MAGE), has not been comprehensively analyzed. The aim of the study was to perform a meta-analysis to compare the effects of DPP4 inhibitors on MAGE with other OADs in type 2 diabetes mellitus (T2DM) patients without concurrent insulin treatments.

METHODS

The Medline (PubMed), Embase (Ovid), and CENTER (Cochrane Library) databases were searched for relevant randomized controlled trials (RCTs). Study characteristics and outcome data were independently extracted by two authors. A random-effect model was used to combine the results.

RESULTS

Fourteen studies with 855 patients were included. Compared to other OADs, DPP4 inhibitors significantly reduced MAGE (mean difference [MD]: -0.69 mmol/L, 95% confidence interval [CI]: -0.95 to -0.43, P<0.001) with mild heterogeneity (I^{2 =} 28%). Predefined subgroup analyses suggested that DPP4 inhibitors were more effective in reducing MAGE compared to insulin secretagogues (MD: -0.92 mmol/L, P<0.001) and non-secretagogues (MD: -0.43 mmol/L, P=0.02), as well as compared to sulfonylureas (MD: -0.91 mmol/L, P<0.001) and sodium glucose cotransporter 2 inhibitors (MD: -0.67 mmol/L, P=0.03).

CONCLUSIONS

DPP4 inhibitors may significantly reduce glycemic variability compared to other oral anti-diabetic drugs, as evidenced by MAGE in T2DM patients with no concurrent insulin treatment.

SYSTEMATIC REVIEW REGISTRATION

INPLASY, registration number: INPLASY2021120113.