Nonadjunctive Use of Continuous Glucose Monitoring: The End of Fingersticks?

Effect of divergent continuous glucose monitoring technologies on glycaemic control in type 1 diabetes mellitus: A systematic review and meta-analysis of randomised controlled trials

AIMS

We aimed to conduct a systematic review and meta-analysis of randomised controlled clinical trials (RCTs) assessing separately and together the effect of the three distinct categories of continuous glucose monitoring (CGM) systems (adjunctive, non-adjunctive and intermittently-scanned CGM [isCGM]), compared with traditional capillary glucose monitoring, on HbA1c and CGM metrics.

METHODS

PubMed, Web of Science, Scopus and Cochrane Central register of clinical trials were searched. Inclusion criteria were as follows: randomised controlled trials; participants with type 1 diabetes of any age and insulin regimen; investigating CGM and isCGM compared with traditional capillary glucose monitoring; and reporting glycaemic outcomes of HbA1c and/or time-in-range (TIR). Glycaemic outcomes were extracted post-intervention and expressed as mean differences and 95%CIs between treatment and comparator groups. Results were pooled using a random-effects meta-analysis. Risk of bias was assessed using the Cochrane Rob2 tool.

RESULTS

This systematic review was conducted between January and April 2021; it included 22 RCTs (15 adjunctive, 5 non-adjunctive, and 2 isCGM)). The overall analysis of the pooled three categories showed a statistically significant absolute improvement in HbA1c percentage points (mean difference (95% CI): -0.22% [-0.31 to -0.14], I²  = 79%) for intervention compared with comparator and was strongest for adjunctive CGM (-0.26% [-0.36, -0.16]). Overall TIR (absolute change) increased by 5.4% (3.5 to 7.2), I²  = 71% for CGM intervention compared with comparator and was strongest with non-adjunctive CGM (6.0% [2.3, 9.7]).

CONCLUSIONS

For individuals with T1D, use of CGM was beneficial for impacting glycaemic outcomes including HbA1c, TIR and time-below-range (TBR). Glycaemic improvement appeared greater for TIR for newer non-adjunctive CGM technology.

Accuracy Assessment of the GlucoMen® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study

The aim of this study was to evaluate the accuracy and usability of a novel continuous glucose monitoring (CGM) system designed for needle-free insertion and reduced environmental impact. We assessed the sensor performance of two GlucoMen® Day CGM systems worn simultaneously by eight participants with type 1 diabetes. Self-monitoring of blood glucose (SMBG) was performed regularly over 14 days at home. Participants underwent two standardized, 5-h meal challenges at the research center with frequent plasma glucose (PG) measurements using a laboratory reference (YSI) instrument. When comparing CGM to PG, the overall mean absolute relative difference (MARD) was 9.7 [2.6–14.6]%. The overall MARD for CGM vs. SMBG was 13.1 [3.5–18.6]%. The consensus error grid (CEG) analysis showed 98% of both CGM/PG and CGM/SMBG pairs in the clinically acceptable zones A and B. The analysis confirmed that GlucoMen® Day CGM meets the clinical requirements for state-of-the-art CGM. In addition, the needle-free insertion technology is well tolerated by users and reduces medical waste compared to conventional CGM systems.

Evaluation of Three Lancing Devices: What Do Blood Volume and Lancing Pain Depend On?

BACKGROUND

Globally millions of people with diabetes still prick their fingers to measure blood glucose. The aim of this study was to comprehensively evaluate and to compare three lancing devices set at the minimum ("1") and at the maximum ("5") lancing depth with respect to blood volume (BV) and pain related to lancing.

METHODS

Lancing devices tested were A-Glucoject Dual PLUS, B-droplet (both: HTL-Strefa S.A., Poland), and C-Microlet Next (Ascensia Diabetes Care, Switzerland), all used with personal lancets of three sizes 28G, 30G, and 33G. BVs were measured with calibrated capillaries. Pain related to lancing was expressed as a derivative of pain rating with visual analog scale.

RESULTS

In 90 participants with diabetes, 360 lancing procedures were performed. Overall, BV and pain were higher for "maximum" compared to "minimum" lancing depth (for both P < .001). Pain differed between devices (P ≤ .001), overall was higher for device A compared to B or C; in paired comparisons differences were significant for the following settings: A > B for 28G/1 and 33G/1, B > C for 30G/1, and A > C for 28G/1, 30G/1, and 33G/1. In aggregated comparison we did not prove a significant effect of lancet size on either BV nor pain (P = .1109, P = .4966, respectively).

CONCLUSIONS

BV depended mainly on lancing depth. Pain depended on lancing depth and to some degree on device type. The results may serve as a source of comparative data of lancing devices performance for studies in which other lancing devices and/or lancets would be tested.The study was registered at ClinicalTrials.gov: NCT03479619.

Real-World Patient-Reported Outcomes and Glycemic Results with Initiation of Control-IQ Technology

Background: The t:slim X2™ insulin pump with Control-IQ™ technology, an advanced hybrid closed-loop system, became available in the United States in early 2020. Real-world outcomes with use of this system have not yet been comprehensively reported. Methods: Individuals with type 1 diabetes (T1D) (≥14 years of age) who had ≥21 days of pump usage data were invited via email to participate. Participants completed psychosocial questionnaires (Technology Acceptance Scale [TAS], well-being index [WHO-5], and Diabetes Impact and Devices Satisfaction [DIDS] scale) at timepoint 1 (T1) (at least 3 weeks after starting Control-IQ technology) and the DIDS and WHO-5 at timepoint 2 (T2) (4 weeks from T1). Patient-reported outcomes (PROs) and glycemic outcomes were reviewed at each timepoint. Results: Overall, 9,085 potentially eligible individuals received the study invite. Of these, 3,116 consented and subsequently 1,435 participants completed questionnaires at both T1 and T2 and had corresponding glycemic data available on the t:connect® web application. Time in range was 78.2% (70.2%-85.1%) at T1 and 79.2% (70.3%-86.2%) at T2. PROs reflected high device-related satisfaction and reduced diabetes impact at T2. Factors contributing to high trust in the system included sensor accuracy, improved diabetes control, reduction in extreme blood glucose levels, and improved sleep quality. In addition, participants reported improved quality of life, ease of use, and efficient connectivity to the continuous glucose monitoring system as being valuable features of the system. Conclusions: Continued real-world use of the t:slim X2 pump with Control-IQ technology showed improvements in psychosocial outcomes and persistent achievement of recommended TIR glycemic outcomes in people with T1D.