Effectiveness of Continuous Glucose Monitoring on Metrics of Glycemic Control in Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis of Randomized Controlled Trials.
To provide a systematic review and meta-analysis synthesizing the findings of randomized controlled trials (RCTs) of continuous glucose monitors (CGMs) in the management of adults with type 2 diabetes mellitus (T2DM) on glucose control and clinical outcomes.
MEDLINE, Embase, and Cochrane were searched for RCTs that assessed the effectiveness of real-time CGM (rt-CGM) or flash CGM (FGM) in adults (≥18 years) with T2DM that reported on at least 1 of the following outcomes: hemoglobin A1c (HbA1c), time in range, time in hyperglycemia, or time in hypoglycemia. The GRADE approach was used to assess certainty of evidence for primary outcomes.
Fourteen RCTs assessing CGM were included, with 825 patients in 9 RCTs using rt-CGM and 822 in 5 RCTs using FGM. Moderate certainty of evidence indicated that use of CGM had a modest but statistically significant reduction in HbA1c levels of about 0.32%. Our analyses of each device type separately showed similar reductions in HbA1c (0.34% and 0.33%, respectively, for rt-CGM and FGM), with trends for improvement in other glucose metrics favoring rt-CGM over self-monitored blood glucose.
Both rt-CGM and flash CGM led to modest but statistically significant declines in HbA1c among individuals with T2DM, with little heterogeneity in the results. However, the duration of the included RCTs was relatively short and few studies reported on important clinical outcomes, such as adverse events, emergency department use, or hospitalization. Longer term studies are needed to determine if the short-term improvements in glucose control leads to improvements in clinically important outcomes.
Uhl S
，Choure A
，Rouse B
，Loblack A
，Reaven P
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Study of Glycemic Variability in Well-controlled Type 2 Diabetic Patients Using Continuous Glucose Monitoring System.
The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS).
To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c.
A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over a period of 7 days by using FreeStyle® Libre Pro™, which is a flash glucose monitoring system. The CGM sensor was attached to the left upper arm of the patient on day 0 and removed on day 7. The data recorded in the sensor was then retrieved using pre-installed computer software and analyzed using standard CGM metrics like standard deviation (SD), percentage coefficient of variation (%CV), time above range (TAR), time below range (TBR), and time in range (TIR), out of which %CV was used to quantify GV. %CV has been used to cluster patients into four cohorts from best to worst, namely: best/low CV ≤ 10%, intermediate CV from 10 to 20%, high CV from 20 to 30%, and very high CV of >30%. Scatterplots are used to establish correlations between various parameters.
Data from a total of 30 patients were analyzed using CGMS and thus used for calculating standard CGM metrics; glucose readings every 15 minutes were recorded consecutively for 7-day periods, making it a total of 672 readings for each patient. Interpreting the CGM data of all 30 patients, the following results were found: the mean blood glucose of all cases is 134.925 ± 22.323 mg/dL, the mean SD of blood glucose of all cases is 35.348 ± 9.388 mg/dL, the mean of %CV of all cases is 26.376 ± 6.193%. CGM parameters of time are used in the form of percentages, and the following results were found: the mean of TAR, TBR, and TIR is 14.425 ± 13.211, 5.771 ± 6.808, and 82.594 ± 12.888%, respectively. Clustering the patients into cohorts, the proportion of patients exhibiting best/low %CV (10%) is 0, intermediate %CV (10-20%) is 16.67% (five out of 30 patients), high %CV (20-30%) is 50% (15 out of 30 patients) and very high %CV (>30%) is 33.33% (10 out of 30 patients). Also, there is no significant correlation found between HbA1c and %CV (ρ = 0.076, p-value = 0.690); a significant negative correlation was found between %CV and TIR (ρ = -0.604, p < 0.001S); a positive correlation of %CV with TAR and TBR is significant (ρ = 0.816, p-value of <0.001).
Using a flash CGMS device and considering %CV as the parameter and primary measure of GV, the study demonstrated the overall instability of a person's glycemic control, making note of unrecognized events of hypoglycemia and hyperglycemia in asymptomatic well-controlled T2DM patients, revealing the overall volatile glycemic control. The most important finding of this study is that even those diabetics who are considered well-controlled experience a great degree of GV as assessed by CGM-derived metrics. This study also demonstrated that there is no significant correlation between HbA1c and GV, suggesting that patients may not have optimal control of their diabetes despite having "normal HbA1c" values; hence, GV can be considered an HbA1c-independent danger factor, having more harmful effects than sustained hyperglycemia in the growth of diabetic complications. So, by using CGM-derived metrics, the measurement of GV has the potential to complement HbA1c data. In this manner, a more comprehensive assessment of glycemic excursions can be provided for better treatment decisions, thereby facilitating optimal glycemic control, which is essential for reducing overall complications and promoting good quality of life.
Swami V
，Yadav SK
，Saxena P
，Sharma A
，Dash CK
，Gupta A
... -
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