Effects of Continuous Glucose Monitoring on Metrics of Glycemic Control in Diabetes: A Systematic Review With Meta-analysis of Randomized Controlled Trials

Abstract

BACKGROUNDContinuous glucose monitoring (CGM) provides important information to aid in achieving glycemic targets in people with diabetes. PURPOSEWe performed a meta-analysis of randomized controlled trials (RCTs) comparing CGM with usual care for parameters of glycemic control in both type 1 and type 2 diabetes. DATA SOURCESMany electronic databases were searched for articles published from inception until 30 June 2019. STUDY SELECTIONWe selected RCTs that assessed both changes in HbA 1c and time in target range (TIR), together with time below range (TBR), time above range (TAR), and glucose variability expressed as coefficient of variation (CV). DATA EXTRACTIONData were extracted from each trial by two investigators. DATA SYNTHESISAll results were analyzed by a random effects model to calculate the weighted mean difference (WMD) with the 95% CI. We identified 15 RCTs, lasting 12-36 weeks and involving 2,461 patients. Compared with the usual care (overall data), CGM was associated with modest reduction in HbA 1c (WMD 20.17%, 95% CI 20.29 to 20.06, I 2 5 96.2%), increase in TIR (WMD 70.74 min, 95% CI 46.73-94.76, I 2 5 66.3%), and lower TAR, TBR, and CV, with heterogeneity between studies. The increase in TIR was significant and robust independently of diabetes type, method of insulin delivery, and reason for CGM use. In preplanned subgroup analyses, real-time CGM led to the higher improvement in mean HbA 1c (WMD 20.23%, 95% CI 20.36 to 20.10, P < 0.001), TIR (WMD 83.49 min, 95% CI 52.68-114.30, P < 0.001), and TAR, whereas both intermittently scanned CGM and sensor-augmented pump were associated with the greater decline in TBR. LIMITATIONSHeterogeneity was high for most of the study outcomes; all studies were sponsored by industry, had short duration, and used an open-label design. CONCLUSIONSCGM improves glycemic control by expanding TIR and decreasing TBR, TAR, and glucose variability in both type 1 and type 2 diabetes.

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Glycemic control in people with type 1 diabetes using a hybrid closed loop system and followed by telemedicine during the COVID-19 pandemic in Italy

“…Engaging in effective diabetes self-management often requires a great attention to meals, regulating insulin doses, planning physical exercise or working activities and facing psychological stress [1]. The recent innovations in technologies aimed at diabetes management have largely enhanced the ability to improve glycemic control with glucose sensing, glucose-responsive insulin delivery systems and tools for data management which lessened the burden of self-care [2,3].…”

Accuracy of the Dexcom G6 Glucose Sensor during Aerobic, Resistance, and Interval Exercise in Adults with Type 1 Diabetes

“…The emergence of continuous glucose monitoring (CGM) has transformed how type 1 diabetes is managed and enabled better monitoring of glucose during exercise [ 11 , 12 ]. The use of CGM systems has been shown to improve time-in-range, while reducing HbA1c levels and risk of hypoglycemia [ 13 , 14 , 15 , 16 ]. Additionally, it has led to the development of closed-loop systems associated with significant improvements in time-in-range [ 17 ].…”