Acceptability and experiences of real-time continuous glucose monitoring in adults with type 2 diabetes using insulin: a qualitative study.

Aims: To explore the lived experiences of initiating real-time continuous glucose monitoring (rt-CGM) use in individuals with type 2 diabetes using insulin. Methods: Twelve semi-structured interviews were conducted amongst individuals with type 2 diabetes taking insulin who were enrolled in the 2GO-CGM randomised controlled trial and had completed 3 months of rtCGM. Interviews were transcribed verbatim and analysed to identify common themes regarding their experiences. Results: The interviews revealed three key themes: i) rtCGM as a facilitator of improved health behaviours; ii) the acceptability of rtCGM systems compared to capillary blood glucose testing; and iii) barriers to the continual usage of rtCGM technology - including: connection difficulties, longevity of the sensors, and local cutaneous reactions to the sensor adhesive. Conclusion: Adults on insulin with type 2 diabetes find rtCGM systems widely acceptable, and easier to engage with than traditional self-monitoring of capillary blood glucose. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-024-01403-9.

Protocol for a prospective, multicenter, parallel-group, open-label randomized controlled trial comparing standard care with Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control: the CO-PILOT trial.

Purpose: Advanced hybrid closed loop (AHCL) systems have the potential to improve glycemia and reduce burden for people with type 1 diabetes (T1D). Children and youth, who are at particular risk for out-of-target glycemia, may have the most to gain from AHCL. However, no randomized controlled trial (RCT) specifically targeting this age group with very high HbA1c has previously been attempted. Therefore, the CO-PILOT trial (Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control) aims to evaluate the efficacy and safety of AHCL in this group. Methods: A prospective, multicenter, parallel-group, open-label RCT, comparing MiniMed™ 780G AHCL to standard care (multiple daily injections or continuous subcutaneous insulin infusion). Eighty participants aged 7-25 years with T1D, a current HbA1c ≥ 8.5% (69 mmol/mol), and naïve to automated insulin delivery will be randomly allocated to AHCL or control (standard care) for 13 weeks. The primary outcome is change in HbA1c between baseline and 13 weeks. Secondary outcomes include standard continuous glucose monitor glycemic metrics, psychosocial factors, sleep, platform performance, safety, and user experience. This RCT will be followed by a continuation phase where the control arm crosses over to AHCL and all participants use AHCL for a further 39 weeks to assess longer term outcomes. Conclusion: This study will evaluate the efficacy and safety of AHCL in this population and has the potential to demonstrate that AHCL is the gold standard for children and youth with T1D experiencing out-of-target glucose control and considerable diabetes burden. Trial registration: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 14 November 2022 (ACTRN12622001454763) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1284-8452). Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-024-01397-4.

Real time continuous glucose monitoring in high-risk people with insulin-requiring type 2 diabetes: A randomised controlled trial.

AIMS: To investigate the impact of real-time continuous glucose monitoring (rtCGM) on glycaemia in a predominantly indigenous (Maori) population of adults with insulin-requiring type 2 diabetes (T2D) in New Zealand. METHODS: Twelve-week, multicentre randomised controlled trial (RCT) of adults with T2D using ≥0.2 units/kg/day of insulin and elevated glycated haemoglobin (HbA1c) ≥64 mmol/mol (8.0%). Following a 2-week blinded CGM run-in phase, participants were randomised to rtCGM or control (self-monitoring blood glucose [SMBG]). The primary outcome was time in the target glucose range (3.9-10 mmol/L; TIR) during weeks 10-12, with data collected by blinded rtCGM in the control group. RESULTS: Sixty-seven participants entered the RCT phase (54% Maori, 57% female), median age 53 (range 16-70 years), HbA1c 85 (IQR 74, 94) mmol/mol (9.9 [IQR 8.9, 10.8]%), body mass index (36.7 ± 7.7 kg/m2). Mean (±SD) TIR increased from 37 (24)% to 53 (24)% [Δ 13%; 95% CI 4.2 to 22; P = 0.007] in the rtCGM group but did not change in the SMBG group [45 (21)% to 45 (25)%, Δ 2.5%, 95% CI -6.1 to 11, P = 0.84]. Baseline-adjusted between-group difference in TIR was 10.4% [95% CI -0.9 to 21.7; P = 0.070]. Mean HbA1c (±SD) decreased in both groups from 85 (18) mmol/mol (10.0 [1.7]%) to 64 (16) mmol/mol (8.0 [1.4]%) in the rtCGM arm and from 81 (12) mmol/mol (9.6 [1.1]%) to 65 (13) mmol/mol (8.1 [1.2]%) in the SMBG arm (P < 0.001 for both). There were no severe hypoglycaemic or ketoacidosis events in either group. CONCLUSIONS: Real-time CGM use in a supportive treat-to-target model of care likely improves glycaemia in a population with insulin-treated T2D and elevated HbA1c.

Improved Glycemic Outcomes With Diabetes Technology Use Independent of Socioeconomic Status in Youth With Type 1 Diabetes.

OBJECTIVE: Technology use in type 1 diabetes (T1D) is impacted by socioeconomic status (SES). This analysis explored relationships between SES, glycemic outcomes, and technology use. RESEARCH DESIGN AND METHODS: A cross-sectional analysis of HbA1c data from 2,822 Australian youth with T1D was undertaken. Residential postcodes were used to assign SES based on the Index of Relative Socio-Economic Disadvantage (IRSD). Linear regression models were used to evaluate associations among IRSD quintile, HbA1c, and management regimen. RESULTS: Insulin pump therapy, continuous glucose monitoring, and their concurrent use were associated with lower mean HbA1c across all IRSD quintiles (P < 0.001). There was no interaction between technology use and IRSD quintile on HbA1c (P = 0.624), reflecting a similar association of lower HbA1c with technology use across all IRSD quintiles. CONCLUSIONS: Technology use was associated with lower HbA1c across all socioeconomic backgrounds. Socioeconomic disadvantage does not preclude glycemic benefits of diabetes technologies, highlighting the need to remove barriers to technology access.

Glucose and Psychosocial Outcomes 12 Months Following Transition from Multiple Daily Injections to Advanced Hybrid Closed Loop in Youth with Type 1 Diabetes and Suboptimal Glycemia.

Objective: To investigate 12-month glycemic and psychosocial changes following transition from multiple daily injections (MDI) to advanced hybrid closed-loop (AHCL) therapy in youth (aged 13-25 years) with type 1 diabetes and suboptimal glycemia (glycated hemoglobin [HbA1c] ≥8.5% [69 mmol/mol]). Research Design and Methods: Prospective, single arm, dual-center study in 20 participants. Extension phase outcomes reported after 12 months, including HbA1c, time in glycemic ranges, AHCL system performance, and psychosocial questionnaires assessing quality of life, diabetes treatment, and sleep. Results: After 12 months, 19 out of 20 participants continued to use AHCL. Average time-in-range 70-180 mg/dL (3.9-10.0 mmol/L) improved from 27.6% ± 13.2% to 62.5% ± 11.4%. This translated to an average 2.5 percentage-point (27.1 mmol/mol) improvement in HbA1c from 10.5% ± 2.1% (91.2 mmol/mol) at baseline to 8.0% ± 0.9% (64.1 mmol/mol) at 12 months. Psychosocial questionnaires and very high HbA1c at study entry indicated significant diabetes-associated burden for both individuals and parents. After 12 months, improvements were observed in general and diabetes-specific health-related quality of life, as well as in diabetes treatment satisfaction. Safety data were reassuring with a diabetic ketoacidosis rate of 0.15 per participant-year after 12 months of AHCL (compared to 0.25 per participant-year in the 12 months before the study). Conclusions: After 12 months of AHCL usage, this study highlights the potential for substantial and sustained glycemic and psychosocial improvements among individuals experiencing considerable diabetes burden and suboptimal glycemia, following their switch from MDI to AHCL.

Study protocol: glycaemic outcomes in people with type 2 diabetes initiating continuous glucose monitoring: the 2GO-CGM study.

Purpose: Improving glycaemic control in type 2 diabetes (T2D) is essential to reducing social and health-economic burden of diabetes-related complications. Continuous glucose monitoring (CGM) has been established as beneficial in improving glycaemic control and reducing hypoglycaemia in people with type 1 diabetes, however data in T2D is limited. This study has been designed to assess the effect of initiating real-time CGM (rtCGM) on glycaemic control in a high-risk population of adults with T2D. Secondary objectives are to assess the cost-effectiveness and safety of rtCGM, and the effects of rtCGM on diet/lifestyle and the burden of diabetic complications, including cardiovascular risk. Methods: This multicentre randomised controlled trial (RCT) will be conducted at three sites in New Zealand (Waikato, Christchurch and Dunedin). Eighty adults with T2D on insulin with suboptimal glycaemic control (HbA1c > 8.0% or 64 mmol/mol) will be randomised 1:1 to rtCGM or routine care with self-monitoring of blood glucose levels (SMBG) for three months. This intervention phase will be followed by a three-month continuation phase where SMBG group crossover to use rtCGM. Participants will then be invited to join the extension phase with continued use of rtCGM for a further 12 months. During the extension phase, both groups will independently titrate their insulin under the remote supervision of prescribing diabetes nurse specialists following an insulin titration algorithm. The primary outcome of the study is time in target glucose range (3.9-10 mmol/L or 70-180 mg/dL; TIR). Secondary outcomes include CGM metrics as per consensus statement recommendations, and HbA1c. Additional planned analyses include cardiovascular risk profile, incremental cost-effectiveness analyses, dietary patterns, and qualitative analyses. Trial registration number: The trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12621000889853) on 8 July 2021 and the World Health Organisation International Clinical Trial Registry Platform (Universal Trial Number U1111-1264-5822).

Knowledge, safety, and impact of alcohol consumption in young adults with type 1 diabetes mellitus: a qualitative study.

PURPOSE: To explore the lived experiences of alcohol consumption among young adults with type 1 diabetes. METHODS: Fourteen semi-structured interviews were conducted amongst young adults aged between 18 and 25 years, inclusive, with type 1 diabetes and experience consuming alcohol. Interviews were transcribed verbatim and analysed to identify common themes regarding their experiences. RESULTS: The interviews confirmed that young adults with type 1 diabetes engage in social, and occasionally excessive, drinking behaviour. Furthermore, the interviews revealed four key themes: (i) Several sources contribute to a widely inconsistent understanding of the impact and management of alcohol consumption; (ii) Perceived inconvenience of maintaining healthy glycaemic control whilst drinking socially; (iii) Engagement in proactive strategies for harm reduction occurred when convenient; and (iv) Impact of modern diabetes technology in overcoming previous burdens and promoting glycaemic safety. CONCLUSION: Young adults with type 1 diabetes continue to need anticipatory education surrounding safe alcohol consumption and behaviours, as well as ongoing support and encouragement to ensure engagement with traditional self-management tasks. Significant alcohol-diabetes related safety issues, particularly hypoglycaemia do occur, and were captured within this small sample and study. Diabetes technology has an important complementary role along with education and tailored support strategies to support health and safe glucose control during alcohol consumption.

Socioeconomic status and diabetes technology use in youth with type 1 diabetes: a comparison of two funding models.

Background: Technology use, including continuous glucose monitoring (CGM) and insulin pump therapy, is associated with improved outcomes in youth with type 1 diabetes (T1D). In 2017 CGM was universally funded for youth with T1D in Australia. In contrast, pump access is primarily accessed through private health insurance, self-funding or philanthropy. The study aim was to investigate the use of diabetes technology across different socioeconomic groups in Australian youth with T1D, in the setting of two contrasting funding models. Methods: A cross-sectional evaluation of 4957 youth with T1D aged <18 years in the national registry was performed to determine technology use. The Index of Relative Socio-Economic Disadvantage (IRSD) derived from Australian census data is an area-based measure of socioeconomic status (SES). Lower quintiles represent greater disadvantage. IRSD based on most recent postcode of residence was used as a marker of SES. A multivariable generalised linear model adjusting for age, diabetes duration, sex, remoteness classification, and location within Australia was used to determine the association between SES and device use. Results: CGM use was lower in IRSD quintile 1 in comparison to quintiles 2 to 5 (p<0.001) where uptake across the quintiles was similar. A higher percentage of pump use was observed in the least disadvantaged IRSD quintiles. Compared to the most disadvantaged quintile 1, pump use progressively increased by 16% (95% CI: 4% to 31%) in quintile 2, 19% (6% to 33%) in quintile 3, 35% (21% to 50%) in quintile 4 and 51% (36% to 67%) in the least disadvantaged quintile 5. Conclusion: In this large national dataset, use of diabetes technologies was found to differ across socioeconomic groups. For nationally subsidised CGM, use was similar across socioeconomic groups with the exception of the most disadvantaged quintile, an important finding requiring further investigation into barriers to CGM use within a nationally subsidised model. User pays funding models for pump therapy result in lower use with socioeconomic disadvantage, highlighting inequities in this funding approach. For the full benefits of diabetes technology to be realised, equitable access to pump therapy needs to be a health policy priority.

Extended Use of an Open-Source Automated Insulin Delivery System in Children and Adults with Type 1 Diabetes: The 24-Week Continuation Phase Following the CREATE Randomized Controlled Trial.

Aim: To assess long-term efficacy and safety of open-source automated insulin delivery (AID) in children and adults (7-70 years) with type 1 diabetes. Methods: Both arms of a 24-week randomized controlled trial comparing open-source AID (OpenAPS algorithm within a modified version of AndroidAPS, preproduction DANA-i™ insulin pump, Dexcom G6 continuous glucose monitor) with sensor-augmented pump therapy (SAPT), entered a 24-week continuation phase where the SAPT arm (termed SAPT-AID) crossed over to join the open-source AID arm (termed AID-AID). Most participants (69/94) used a preproduction YpsoPump® insulin pump during the continuation phase. Analyses incorporated all 52 weeks of data, and combined between-group and within-subject differences to calculate an overall "treatment effect" of AID versus SAPT. Results: Mean time in range (TIR; 3.9-10 mmol/L [70-180 mg/dL]) was 12.2% higher with AID than SAPT (95% confidence interval [CI] 10.4 to 14.1; P < 0.001). TIR was 56.9% (95% CI 54.2 to 59.6) with SAPT and 69.1% (95% CI 67.1 to 71.1) with AID. The treatment effect did not differ by age (P = 0.39) or insulin pump type (P = 0.37). HbA1c was 5.1 mmol/mol lower [0.5%] with AID (95% CI -6.6 to -3.6; P < 0.001). There were no episodes of diabetic ketoacidosis or severe hypoglycemia with either treatment over the 48 weeks. Six participants (all in SAPT-AID) withdrew: three with hardware issues, two preferred SAPT, and one with infusion-site skin irritation. Conclusion: Further evaluation of the community derived automated insulin delivery (CREATE) trial to 48 weeks confirms that open-source AID is efficacious and safe with different insulin pumps, and demonstrates sustained glycemic improvements without additional safety concerns.

Impact of Advanced Hybrid Closed Loop on Youth With High-Risk Type 1 Diabetes Using Multiple Daily Injections.

OBJECTIVE: To evaluate glycemic outcomes in youth (aged 13-25 years) with type 1 diabetes and high-risk glycemic control (HbA1c ≥8.5% [69 mmol/mol]) on multiple daily injection (MDI) therapy after transitioning to advanced hybrid closed loop (AHCL) therapy. RESEARCH DESIGN AND METHODS: This prospective, 3-month, single-arm, dual-center study enrolled 20 participants, and all completed the study. RESULTS: HbA1c decreased from 10.5 ± 2.1% (91.2 ± 22.8 mmol/mol) at baseline to 7.6 ± 1.1% (59.7 ± 11.9 mmol/mol), and time spent in target range 70-180 mg/dL (3.9-10.0 mmol/L) increased from 27.6 ± 13.2% at baseline to 66.5 ± 9.8% after 3 months of AHCL. Two episodes of diabetic ketoacidosis attributed to infusion set failure occurred. CONCLUSIONS: AHCL has the potential to improve suboptimal glycemia in youth with type 1 diabetes previously on MDI therapy.

Inequity in access to continuous glucose monitoring and health outcomes in paediatric diabetes, a case for national continuous glucose monitoring funding: A cross-sectional population study of children with type 1 diabetes in New Zealand.

Background: Continuous glucose monitoring (CGM) improves glycaemia for people affected by type 1 diabetes (T1D), but is not funded in Aotearoa/New Zealand. This study explores the impact of non-funded CGM on equity of access and associated glycaemic outcomes. Methods: Cross-sectional population-based study collected socio-demographic (age, gender, prioritised ethnicity, socioeconomic status) and clinical data from all regional diabetes centres in New Zealand with children <15 years with T1D as of 1st October 2021. De-identified data were obtained from existing databases or chart review. Outcomes compared socio-demographic characteristics between those using all forms of CGM and self-monitoring of blood glucose (SMBG), and association with HbA1c. Findings: 1209 eligible children were evaluated: 70.2% European, 18.1% Maori, 7.1% Pacific, 4.6% Asian, with even distribution across socioeconomic quintiles. Median HbA1c was 64 mmol/mol (8.0%), 40.2% utilised intermittently scanned (is)CGM, and 27.2% real-time (rt)CGM. CGM utilisation was lowest with Pacific ethnicity (38% lower than Maori) and the most deprived socioeconomic quintiles (quintile 5 vs. 1 adjusted RR 0.69; 95% CI, 0.57 to 0.84). CGM use was associated with regional diabetes centre (P < 0.001). The impact of CGM use on HbA1c differed by ethnicity: Maori children had the greatest difference in HbA1c between SMBG and rtCGM (adjusted difference -15.3 mmol/mol; 95% CI, -21.5 to -9.1), with less pronounced differences seen with other ethnicities. Interpretation: Inequities in CGM use exist based on prioritised ethnicity and socioeconomic status. Importantly, CGM was independently associated with lower HbA1c, suggesting that lack of CGM funding contributes to health disparity in children with T1D. Funding: Australasian Paediatric Endocrine Group (APEG), Canterbury Medical Research Foundation, Starship Foundation.

Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice.

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.

The OPTIMISE study protocol: a multicentre optimisation trial comparing continuous glucose monitoring, snacking habits, sleep extension and values-guided self-care interventions to improve glucose time-in-range in young people (13-20 years) with type 1 diabetes.

Purpose: The OPTIMISE study uses a Multiphase Optimisation Strategy (MOST) to identify the best combination of four interventions targeting key diabetes self-care behaviours for use in clinical practice to improve short-term glycaemic outcomes. Methods: This 4-week intervention trial will recruit 80 young people (aged 13-20 years) with type 1 diabetes ≥ 6 months duration), and pre-enrolment HbA1c ≥ 58 mmol/mol (7.5%) in the prior 6 months. Both main intervention and interaction effects will be estimated using a linear regression model with change in glucose time-in-range (TIR; 3.9-10.0 mmol/L) as the primary outcome. Participants will be randomised to one of 16 conditions in a factorial design using four intervention components: (1) real-time continuous glucose monitoring (CGM), (2) targeted snacking education, (3) individualised sleep extension, and (4) values-guided self-care goal setting. Baseline and post-intervention glucose TIR will be assessed with blinded CGM. Changes in self-care (snacking behaviours, sleep habits and duration, and psychosocial outcomes) will be assessed at baseline and post-intervention to determine if these interventions impacted behaviour change. Discussion: The study outcomes will enable the selection of effective and efficient intervention components that increase glucose TIR in young people who struggle to achieve targets for glycaemic control. The optimised intervention will be evaluated in a future randomised controlled trial and guide the planning of effective clinical interventions in adolescents and young adults living with type 1 diabetes. Trial registration: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 7 October 2020 (ACTRN12620001017910) and the World Health Organisation International Clinical Trails Registry Platform on 26 July 2020 (Universal Trial Number WHO U1111-1256-1248).

Open-Source Automated Insulin Delivery in Type 1 Diabetes.

BACKGROUND: Open-source automated insulin delivery (AID) systems are used by many patients with type 1 diabetes. Data are needed on the efficacy and safety of an open-source AID system. METHODS: In this multicenter, open-label, randomized, controlled trial, we assigned patients with type 1 diabetes in a 1:1 ratio to use an open-source AID system or a sensor-augmented insulin pump (control). The patients included both children (defined as 7 to 15 years of age) and adults (defined as 16 to 70 years of age). The AID system was a modified version of AndroidAPS 2.8 (with a standard OpenAPS 0.7.0 algorithm) paired with a preproduction DANA-i insulin pump and Dexcom G6 CGM, which has an Android smartphone application as the user interface. The primary outcome was the percentage of time in the target glucose range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter) between days 155 and 168 (the final 2 weeks of the trial). RESULTS: A total of 97 patients (48 children and 49 adults) underwent randomization (44 to open-source AID and 53 to the control group). At 24 weeks, the mean (±SD) time in the target range increased from 61.2±12.3% to 71.2±12.1% in the AID group and decreased from 57.7±14.3% to 54.5±16.0% in the control group (adjusted difference, 14 percentage points; 95% confidence interval, 9.2 to 18.8; P<0.001), with no treatment effect according to age (P = 0.56). Patients in the AID group spent 3 hours 21 minutes more in the target range per day than those in the control group. No severe hypoglycemia or diabetic ketoacidosis occurred in either group. Two patients in the AID group withdrew from the trial owing to connectivity issues. CONCLUSIONS: In children and adults with type 1 diabetes, the use of an open-source AID system resulted in a significantly higher percentage of time in the target glucose range than the use of a sensor-augmented insulin pump at 24 weeks. (Supported by the Health Research Council of New Zealand; Australian New Zealand Clinical Trials Registry number, ACTRN12620000034932.).

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.

The effect of do-it-yourself real-time continuous glucose monitoring on psychological and glycemic variables in children with type 1 diabetes: A randomized crossover trial.

BACKGROUND: Continuous glucose monitoring (CGM) decreases fear of hypoglycemia (FOH) and improves glycemic control among those affected by type 1 diabetes (T1D). No studies to date have examined the impact of using do-it-yourself real-time continuous glucose monitoring (DIY RT-CGM) on psychological and glycemic outcomes. METHODS: Child-parent dyads were recruited for a multicentre randomized crossover trial. Children with T1D were current intermittently scanned CGM (isCGM) users and aged 2-13 years. Families received either 6 weeks of DIY RT-CGM with parental remote monitoring (intervention) or 6 weeks of isCGM plus usual diabetes care (control), followed by a 4-week washout period, then crossed over. The primary outcome was parental FOH. Secondary outcomes were glycemic control using traditional CGM metrics, as well as a range of other psychosocial measures. FINDINGS: Fifty five child-parent dyads were recruited. The child mean age was 9.1 ± 2.8 years. Although, there was no effect on parental FOH, -0.1 (95%CI: -0.3, 0.1, p = 0.4), time-in-range (TIR) (%3.9-10 mmol/L) was significantly higher with DIY RT-CGM over isCGM (54.3% ± 13.7 vs. 48.1% ± 13.6), mean difference, 5.7% (95%CI 1.8, 9.6, p <0.004). There was no difference for time spent in hypoglycemia. Parent diabetes treatment satisfaction was significantly higher following DIY RT-CGM compared to isCGM, mean difference 5.3 (95%CI: 2.3, 8.2, p <0.001). CONCLUSION: The use of DIY RT-CGM versus isCGM did not improve parental FOH; however, TIR and parental satisfaction with diabetes treatment were significantly improved. This suggests in the short term, DIY RT-CGM appears safe and may offer families some clinically important advantages over isCGM.

Use of intermittently scanned continuous glucose monitoring in young people with high-risk type 1 diabetes-Extension phase outcomes following a 6-month randomized control trial.

AIMS: To describe the impact of a 12-month intervention using intermittently scanned continuous glucose monitoring (isCGM) on glycaemic control and glucose test frequency in adolescents and young adults with type 1 diabetes (T1D) and high-risk glycaemic control (HbA1c ≥75 mmol/mol [≥9.0%]). METHODS: In total, 64 young people (aged 13-20 years, 16.6 ± 2.1 years; 48% female; 41% Maori or Pacific ethnicity; mean diabetes duration 7.5 ± 3.8 years) with T1D were enrolled in a 6-month, randomized, parallel-group study comparing glycaemic outcomes from the isCGM intervention (n = 33) to self monitoring blood glucose (SMBG) controls (n = 31). In this 6-month extension phase, both groups received isCGM; HbA1c , glucose time-in-range (TIR), and combined glucose test frequency were assessed at 9 and 12 months. RESULTS: At 12 months, the mean difference in HbA1c from baseline was -4 mmol/mol [-0.4%] (95% confidence interval, CI: -8, 1 mmol/mol [-0.8, 0.1%]; p = 0.14) in the isCGM intervention group, and -7 mmol/mol [-0.7%] (95% CI: -16, 1 mmol/mol [-1.5, 0.1%]; p = 0.08) in the SMBG control group. No participants achieved ≥70% glucose TIR (3.9-10.0 mmol/L). The isCGM intervention group mean rate of daily glucose testing was highest at 9 months, 2.4 times baseline rates (p < 0.001), then returned to baseline by 12 months (incidence rate ratio = 1.4; 95% CI: 0.9, 2.1; p = 0.091). CONCLUSIONS: The use of isCGM in young people with high-risk T1D resulted in transient improvements in HbA1c and glucose monitoring over a 9-month time frame; however, benefits were not sustained to 12 months.

Parental experiences of short term supported use of a do-it-yourself continuous glucose monitor (DIYrtCGM): A qualitative study.

AIMS: To investigate the experiences of parents caring for young children with type 1 diabetes type 1 diabetes using a do-it-yourself continuous glucose monitor (DIYrtCGM) in a supported setting. METHODS: Exit interviews were conducted with parents from 11 families at the end of the MiaoMiao study: a randomised cross-over trial focusing on parental fear of hypoglycaemia. Technical support was provided to participants while using DIYrtCGM during the trial. A convenience sampling approach was used to recruit parents. An in-depth, semi-structured interview approach was used. Thematic analysis was used to identify key themes and subthemes. RESULTS: Parents identified that remote monitoring enabled proactive management and that overall alarms/glucose alerts were useful. Some parents reported reductions in anxiety, increased independence for their child, and improvements in the child-parent relationship. However, parents also reported regular signal loss with DIYrtCGM, along with complicated apps and challenges troubleshooting technical problems. Despite this, nine of the 11 families continued to use the system after the end of the trial. CONCLUSIONS: Do-it-yourself continuous glucose monitoring (CGM) was on balance beneficial for the parents interviewed. However, while access to CGM shifted the burden of care experienced by parents, burden did not significantly reduce for all parents, as the improved glycaemic control that they achieved was accompanied with the responsibility for continually monitoring their child's data. Supported use of do-it-yourself CGM may be an achievable, cost-effective option for parents caring for children with type 1 diabetes in countries without funded access to CGM.

Improved technology satisfaction and sleep quality with Medtronic MiniMed® Advanced Hybrid Closed-Loop delivery compared to predictive low glucose suspend in people with Type 1 Diabetes in a randomized crossover trial.

BACKGROUND: Automated insulin delivery aims to lower treatment burden and improve quality of life as well as glycemic outcomes. METHODS: We present sub-study data from a dual-center, randomized, open-label, two-sequence crossover study in automated insulin delivery naïve users, comparing Medtronic MiniMed® Advanced Hybrid Closed-Loop (AHCL) to Sensor Augmented Pump therapy with Predictive Low Glucose Management (SAP + PLGM). At the end of each 4-week intervention, impacts on quality of life, sleep and treatment satisfaction were compared using seven age-appropriate validated questionnaires given to patients or caregivers. RESULTS: 59/60 people completed the study (mean age 23.3 ± 14.4yrs). Statistically significant differences favoring AHCL were demonstrated in several scales (data shown as mean ± SE). In adults (≥ 18yrs), technology satisfaction favored AHCL over PLGM as shown by a higher score in the DTSQs during AHCL (n = 28) vs SAP + PLGM (n = 29) (30.9 ± 0.7 vs 27.9 ± 0.7, p = 0.004) and DTSQc AHCL (n = 29) vs SAP + PLGM (n = 30) (11.7 ± 0.9 vs 9.2 ± 0.8, p = 0.032). Adolescents (aged 13-17yrs) also showed a higher DTSQc score during AHCL (n = 16) versus SAP + PLGM (n = 15) (14.8 ± 0.7 vs 12.1 ± 0.8, p = 0.024). The DTQ "change" score (n = 59) favored AHCL over SAP + PLGM (3.5 ± 0.0 vs 3.3 ± 0.0, p < 0.001). PSQI was completed in those > 16 years (n = 36) and demonstrated improved sleep quality during AHCL vs SAP + PLGM (4.8 ± 0.3 vs 5.7 ± 0.3, p = 0.048) with a total score > 5 indicating poor quality sleep. CONCLUSION: These data suggest that AHCL compared to SAP + PLGM mode has the potential to increase treatment satisfaction and improve subjective sleep quality in adolescents and adults with T1D.