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Introduction: In 2022, updated guidance from NICE expanded the options for self-monitoring of blood glucose for patients with type 2 diabetes (T2DM), to include continuous glucose monitoring (CGM). In this budget impact analysis, the cost impact of CGM was compared with traditional self-monitoring of blood glucose (SMBG) in adults with T2DM over 1 year from the commissioner perspective in England. Research Design and methods: The NICE-eligible T2DM cohort was split into 4 subgroups to enable nuanced costing by insulin administration frequency: basal human insulin, premixed insulin, basal-bolus insulin and bolus insulin. The model's cost components comprised mild and severe hypoglycaemia (SH), diabetic ketoacidosis (DKA), consumables and healthcare resource utilisation in primary and secondary care. Results: The introduction of CGM is estimated to be cost additive by approximately £4.6 million in the basecase, driven by increased spending on the CGM device. Overall, healthcare activity was reduced by approximately 20,000 attendances, due to fewer SH and DKA episodes in the CGM arm. General Practitioner (GP) practice-based activity is expected to drop after the first year as patients requiring CGM training is reduced. The budget impact could be neutralised if the CGM sensor was discounted by 13.2% (£29.76 to £25.83). Conclusions: CGM may result in increased spending in the NICE-eligible T2DM cohort but is expected to reduce demand on secondary care services and GP time. These findings may be of interest to local decision-makers who wish to resolve the COVID-19 backlog with transformational investment in primary care to reduce secondary care activity. [ABSTRACT FROM AUTHOR]

Many efforts are continuously undertaken to develop glucose-sensitive biomaterials able of controlling glucose levels in the body and self-regulating insulin delivery. Hydrogels that swell or shrink as a function of the environmental free glucose content are suitable systems for monitoring blood glucose, delivering insulin doses adapted to the glucose concentration. In this context, the development of sensors based on reversible binding to glucose molecules represents a continuous challenge. Concanavalin A (Con A) is a bioactive protein isolated from sword bean plants (Canavalia ensiformis) and contains four sugar-binding sites. The high affinity for reversibly and specifically binding glucose and mannose makes Con A as a suitable natural receptor for the development of smart glucose-responsive materials. During the last few years, Con A was used to develop smart materials, such as hydrogels, microgels, nanoparticles and films, for producing glucose biosensors or drug delivery devices. This review is focused on Con A-based materials suitable in the diagnosis and therapeutics of diabetes. A brief outlook on glucose-derived theranostics of cancer is also presented. [ABSTRACT FROM AUTHOR]

Objective: Continuous glucose monitoring (CGM) is the standard of care for glucose monitoring in children with diabetes, however there are limited data reporting their use in hyperinsulinaemic hypoglycaemia (HH). Here, we evaluate CGM accuracy and its impact on quality of life in children with HH. Methods: Real-time CGM (Dexcom G5 and G6) was used in children with HH aged 0-16years. Data from self-monitoring capillary blood glucose (CBG) and CGM were collected over a period of up to 28days and analysed. Quality of life was assessed by the PedsQL4.0 general module and PedsQL2.0 family impact module, completed by children and their parents/carers before and after CGM insertion. Analysis of accuracy metrics included mean absolute relative difference (MARD) and proportion of CGM values within 15, 20, and 30% or 15, 20, and 30 mg/dL of reference glucose values >100 mg/dL or ≤100 mg/dL, respectively (%15/15, % 20/20, % 30/30). Clinical reliability was assessed with Clarke error grid (CEG) analyses. Results: Prospective longitudinal study with data analysed from 40 children. The overall MARD between reference glucose and paired CGM values (n=4,928) was 13.0% (Dexcom G5 12.8%, Dexcom G6 13.1%). The proportion of readings meeting %15/15 and %20/20 were 77.3% and 86.4%, respectively, with CEG analysis demonstrating 97.4% of all values in zones A and B. Within the hypoglycaemia range (<70 mg/dL), the median ARD was 11.4% with a sensitivity and specificity of 64.2% and 91.3%, respectively. Overall PedsQL child report at baseline and endpoint were 57.6 (50.5 - 75.8) and 87.0 (82.9 - 91.2), and for parents were 60.3 (44.8 - 66.0) and 85.3 (83.7 - 91.3), respectively (both p<0.001). Conclusion: Use of CGM for children with HH is feasible, with clinically acceptable accuracy, particularly in the hypoglycaemic range. Quality of life measures demonstrate significant improvement after CGM use. These data are important to explore use of CGM in disease indications, including neonatal and paediatric diabetes, cystic fibrosis and glycogen storage disorders. [ABSTRACT FROM AUTHOR]

Aims: To determine the cost‐effectiveness of the Dexcom G6 real‐time continuous glucose monitoring (rt‐CGM) system compared with both the self‐monitoring of blood glucose (SMBG) and the Abbott FreeStyle Libre 1 and 2 intermittently scanned CGM (is‐CGM) devices in people with type 1 diabetes receiving multiple daily insulin injections in Denmark. Materials and Methods: The analysis was performed using the IQVIA Core Diabetes Model, which associates rt‐CGM use with glycated haemoglobin reductions of 0.6% and 0.36% based on data from the DIAMOND and ALERTT1 trials, respectively, compared with SMBG and is‐CGM use. The analysis was performed from the payer perspective over a 50‐year time horizon; future costs and clinical outcomes were discounted at 4% per annum. Results: The use of rt‐CGM was associated with an incremental gain of 1.37 quality‐adjusted life years (QALYs) versus SMBG. Total mean lifetime costs were Danish Krone (DKK) 894 535 for rt‐CGM and DKK 823 474 for SMBG, resulting in an incremental cost‐utility ratio of DKK 51 918 per QALY gained versus SMBG. Compared with is‐CGM, the use of rt‐CGM led to a gain of 0.87 QALYs and higher mean lifetime costs resulting in an incremental cost‐utility ratio of DKK 40 879 to DKK 34 367 per QALY gained. Conclusions: In Denmark, the rt‐CGM was projected to be highly cost‐effective versus both SMBG and is‐CGM, based on a willingness‐to‐pay threshold of 1× per capita gross domestic product per QALY gained. These findings may help inform future policies to address regional disparities in access to rt‐CGM. [ABSTRACT FROM AUTHOR]

Aim: To systematically assess the impact of commercially available hybrid closed loop (HCL) systems on psychological outcomes in youths with type 1 diabetes and their parents. Methods: We performed a systematic review including studies published in the last 10 years. PICOS framework was used in the selection process, and evidence was assessed using the GRADE system. Results: A total of 215 studies were identified after duplicate removal, and 31 studies were included in this systematic review: 20 on first‐generation HCL and 11 on second‐generation HCL systems. According to studies with moderate‐ to high‐level quality of evidence, HCL systems led to better, or in some studies, unchanged psychological outcomes such as distress and burden related to diabetes management, fear of hypoglycemia, quality of life, satisfaction; instead, quality of sleep was perceived as improved, although results were not confirmed in studies using actigraphy. From semi‐structured interviews, answers were more homogeneous, and participants reported a positive experience and attitude towards HCL technology, which was felt to be easy to use and apt to achieve glycemic targets. Conclusions: Evidence confirms the importance of evaluating the psychosocial needs of youths with diabetes and their families when starting HCL systems and during follow‐up, and to set realistic expectations of what can be achieved along with awareness of the limitations of the systems, and educate and motivate families to overcome barriers. [ABSTRACT FROM AUTHOR]

Aim. To assess children's subsequent device usage and caregiver attitudes to do-it-yourself real-time continuous glucose monitoring (DIY-rtCGM) at least 3 months after completing a randomized controlled trial (RCT). Methods. A brief online questionnaire or telephone call was used to collect the subsequent device usage and caregivers' attitudes from a total of 55 families at least 3 months after their completion of an RCT investigating DIY-rtCGM adapted from their preexisting intermittently scanned glucose sensors plus education on using DIY-rtCGM system. To be eligible for the RCT, children had to be aged 2–13 years, have type 1 diabetes ≥6 months, and be rtCGM naïve. Data collected investigated current CGM use post-RCT and attitudes/user experiences to DIY-rtCGM in the months since RCT study support ended. Results. Overall, responses from 81.8% (45/55) of caregivers were received. Mean age of children was 9.0 ± 2.7 years, and 31 (68.9%) children used insulin pumps. After 3 months, 44.4% (20/45) of responding caregivers reported ongoing DIY-rtCGM use, and of these, only 13 used DIY-rtCGM as the primary glucose monitoring method 100% of time. Of the 25 (55.6%) families who ceased DIY-rtCGM, 40% (10/25) had transitioned to commercial rtCGM. More than half of families (60%, 12/20) who continued DIY-rtCGM use had a very or extremely positive attitude toward the technology and 75% (15/20) of these families planned to continue DIY-rtCGM use. However, signal loss and sensor inaccuracy remained the major reasons among all responders both for decreased DIY-rtCGM wear time and eventual cessation. Burden of use primarily related to technical errors that could not be solved, and alarms, both of which were reported to contribute to discontinuation. Conclusions. This study highlights that, among families voluntarily using DIY-rtCGM at least 3 months following support from a trial, more than half have ceased using DIY-rtCGM, with 40% of those discontinuing switching to commercial rtCGM. While overall perceptions of DIY-rtCGM remain largely positive, burdens of use are high and contribute to discontinuation. [ABSTRACT FROM AUTHOR]

Background and aims: Blood glucose prediction (BGP) has increasingly been adopted for personalized monitoring of blood glucose levels in diabetic patients, providing valuable support for physicians in diagnosis and treatment planning. Despite the remarkable success achieved, applying BGP in multipatient scenarios remains problematic, largely due to the inherent heterogeneity and uncertain nature of continuous glucose monitoring (CGM) data obtained from diverse patient profiles. Methodology: This study proposes the first graph-based Heterogeneous Temporal Representation (HETER) network for multi-patient Blood Glucose Prediction (BGP). Specifically, HETER employs a flexible subsequence repetition method (SSR) to align the heterogeneous input samples, in contrast to the traditional padding or truncation methods. Then, the relationships between multiple samples are constructed as a graph and learned by HETER to capture global temporal characteristics. Moreover, to address the limitations of conventional graph neural networks in capturing local temporal dependencies and providing linear representations, HETER incorporates both a temporallyenhanced mechanism and a linear residual fusion into its architecture. Results: Comprehensive experiments were conducted to validate the proposed method using real-world data from 112 patients in two hospitals, comparing it with five well-known baseline methods. The experimental results verify the robustness and accuracy of the proposed HETER, which achieves the maximal improvement of 31.42%, 27.18%, and 34.85% in terms of MAE, MAPE, and RMSE, respectively, over the second-best comparable method. Discussions: HETER integrates global and local temporal information from multipatient samples to alleviate the impact of heterogeneity and uncertainty. This method can also be extended to other clinical tasks, thereby facilitating efficient and accurate capture of crucial pattern information in structured medical data. [ABSTRACT FROM AUTHOR]

Aims and objectives: The aim of this study was to assess the effect of the FreeStyle Libre device implantation in adult type 1 diabetics in a Health Area of Castilla La Mancha (Spain) during the COVID‐19 pandemic. Background: FreeStyle Libre is a so‐called mHealth device that supports health care. During COVID‐1 confinement, diabetic patients could have improved their glycaemic monitoring thanks to these devices, although health care in these patients may have been limited due to confinement. Methods: A 12‐month longitudinal study in which a total of 206 type I diabetics participated, belonging to a single health area. Sociodemographic and analytical data and the Self Care Inventory Revised questionnaire (SCI‐R) were collected. STROBE checklist was followed. Results: The analysis showed differences related to the use of the sensor. After the study period, patients obtained better levels of basal glucose, glycosylated haemoglobin, creatinine, cholesterol, triglycerides and LDL. In addition, a significant increase in the total score of the SCI‐R questionnaire was observed after the use of the monitor (MD −7.77; 95% CI −10.43, −8.29). The same occurred with different SCI‐R items such as diet (MD ‐2.995; 95% CI −3.24, −2.57), glucose determination (MD −3.21; 95% CI −3.52, −2.91), medication administration (MD −2.58; 95% CI −2.53, −1.96) and hypoglycaemic episodes (MD −1.07; 95% CI −1.21, −0.93). In the analysis by groups, worse values of glycosylated haemoglobin and adherence to treatment (p <.05) were observed in overweight/obese subjects versus those with normal weight after one year of study. Conclusion: The use of flash monitoring is related to better adherence to most of the recommended habits in diabetes. Nevertheless, there seems to be no relationship with an improvement in physical exercise and preventive aspects of diabetes. A good nursing intervention to support physical exercise and the use of mHealth devices could improve the control of diabetic patients. Relevance to clinical practice: The use of this mHealth device has shown positive results and reduced complications. Despite less contact with healthcare facilities due to the pandemic, type 1 diabetic patients have improved their blood results and adherence after using the device for one year. Nursing staff should focus on promoting physical activity and routine disease care in type 1 diabetics. [ABSTRACT FROM AUTHOR]

Aims: Severe hypoglycaemia requiring emergency medical services remains prevalent despite advances in all aspects of diabetes self‐management. Real‐time continuous glucose monitoring (RTCGM) technologies can reduce the risk of severe hypoglycaemia for adults with type 1 diabetes, but the impact of these devices has not been assessed in the acute phase after an episode of severe hypoglycaemia. Methods: We recruited and randomised 35 adults with type 1 diabetes in the acute period after an episode of severe hypoglycaemia requiring emergency medical services and randomised participants to RTCGM with alerts and alarms, or usual care with self‐monitored blood glucose for 12 weeks with intermittent blinded CGM. The primary outcome was the difference between groups in percentage time spent in hypoglycaemia (≤3.0 mmol/L, 55 mg/dL). Results: Thirty participants completed the study (median (IQR) age, duration of diabetes, and BMI was 43 (36–56) years, 26 (19–37) years, and 24.9 (21.9–29.0) kg/m2, respectively). Sufficient CGM data was available for 15 participants in RT‐CGM group and 8 in SMBG group for the primary outcome analysis. The RTCGM group had a significantly larger reduction in exposure to glucose below 3.0 mmol/L (RTCGM −0.16 [−1.23 to 0.01] vs. SMBG 1.58 [0.41 to 3.48], p = 0.03) and episodes of nocturnal hypoglycaemia (RT‐CGM −0.03 [−0.15 to 0.02] vs. SMBG 0.05 [−0.03 to 0.40], p = 0.02). Episodes of severe hypoglycaemia were significantly lower in the RTCGM group (RTCGM 0.0 vs. SMBG 4.0, p 0.04). Conclusions: RTCGM implemented acutely after an episode of severe hypoglycaemia is feasible and clinically effective with important implications for hypoglycaemia management pathways and self‐monitoring cost effectiveness. [ABSTRACT FROM AUTHOR]

Continuous glucose monitoring (CGM) is now an integral part of glycaemic management in people with type 1 diabetes and those with insulin‐treated type 2 diabetes. Immediate access to information on CGM glucose levels and trends helps to inform food choices, titration and timing of insulin doses and prompts corrective actions in the event of impending hypo‐ or hyperglycaemia. Although glycated haemoglobin (HbA1c) remains an important measure of the average of glucose, CGM metrics including time‐in‐range (TIR) and other metrics on glycaemic variability and hypoglycaemia are strongly endorsed by people with diabetes as impacting their daily lives. There is growing consensus on definitions and targets of CGM metrics with an increasing number of studies demonstrating correlations between CGM metrics and incident complications of diabetes. Implementation of new technologies needs to take into consideration factors such as cost‐effectiveness, accessibility as well as acceptability of the person with diabetes and healthcare professional. The United Kingdom is one of the few countries that have developed clinical pathways for integrating CGM into the routine care of people with type 1 diabetes. Besides type 1 diabetes, special groups such as people with impaired kidney function and women during pregnancy may derive additional benefits from CGM. [ABSTRACT FROM AUTHOR]

Background. The bidirectional relationship between sleep and blood glucose levels may particularly affect adolescents and young adults (AYA), who are more likely to experience less healthy glycemic outcomes and more disrupted sleep patterns. To date, few data exist describing the impact of intermittently scanned continuous glucose monitoring (isCGM) on habitual sleep patterns and sleep quality in AYA with type 1 diabetes (T1D). Objective. To evaluate the impact of 6-month use of isCGM on habitual sleep and wake timing, sleep duration, frequency, and duration of night-time awakenings, sleep efficiency, and perceived sleep quality in young people with T1D and HbA1c ≥ 75 mmol/mol. Participants. The study recruited 64 participants aged 13–20 years (mean 16.6 ± 2.1), 48% female, diabetes duration 7.5 ± 3.8 years, 41% Māori or Pasifika, and a mean HbA1c 96.0 ± 18.0 mmol/mol [10.9 ± 3.8%]; 33 were allocated to an isCGM plus self-monitoring blood glucose [SMBG] intervention, and 31 were allocated to the SMBG control group. Methods. Participants completed 7-day actigraphy measures and the Pittsburgh Sleep Quality Index questionnaire at the baseline and at 6 months. Regression analyses were used to model between-group comparisons, adjusted for baseline sleep measures. Results. At 6 months, subjective measures for overall sleep quality, latency, duration, efficiency, night-time disturbances, use of sleep medications, and daytime dysfunction were similar between the groups. Regression analyses of actigraphy found no significant differences in objectively measured sleep timing and duration across the week after adjusting for age, the period of the school year, and baseline sleep values. Conclusions. The use of first-generation isCGM in addition to finger-prick testing did not impact objective or subjective sleep measures in AYA with T1D, elevated HbA1c, and highly variable sleep patterns. Research using alternative interventions for improving glycemic outcomes and habitual sleep-wake timing, duration, and perceived sleep quality is warranted in this population group. [ABSTRACT FROM AUTHOR]

Aims: To examine real‐world capillary blood glucose (CBG) data according to HbA1c to define proportions of CBG readings at different HbA1c levels, and evaluate patterns in CBG measurements to suggest areas to focus on with regard to self‐management. Methods: A retrospective analysis stratified 682 adults with type 1 diabetes split into quartiles based on their HbA1c. The proportions of results in different CBG ranges and associations with HbA1c were evaluated. Patterns in readings following episodes of hyperglycaemia and hypoglycaemia were examined, using glucose to next glucose reading table (G2G). Results: CBG readings in the target range (3.9‐10 mmol/L) increase by ~10% across each CBG quartile (31% in the highest versus 63% in the lowest quartile, p < 0.05). The novel G2G table helps the treatment‐based interpretation of data. Hypoglycaemia is often preceded by hyperglycaemia, and vice‐versa, and is twice as likely in the highest HbA1c quartile. Re‐testing within 30 min of hypoglycaemia is associated with less hypoglycaemia, 1.6% versus 7.2%, p < 0.001, and also reduces subsequent hyperglycaemia and further hypoglycaemia in the proceeding 24 h. The coefficient of variation, but not standard deviation, is highly associated with hypoglycaemia, r = 0.71, and a CV ≤ 36% equates to 3.3% of CBG readings in the hypoglycaemic range. Conclusions: HbA1c <58 mmol/mol (7.5%) is achievable even when only ~60% of CBG readings are between 3.9–10 mmol/L. Examining readings subsequent to out‐of‐range readings suggests useful behaviours which people with type 1 diabetes could be supported to adhere to, both in a clinic and structured education programmes, thereby decreasing the risk of hypoglycaemia whilst also reducing hyperglycaemia and improving HbA1c. [ABSTRACT FROM AUTHOR]

Aims: Regional variations in the adoption of diabetes technology may be reflected in population‐level metrics of glycaemic control. In this observational study, we aimed to assess the glycaemic impacts of transitioning from the Dexcom G5 Real‐Time Continuous Glucose Monitoring (RT‐CGM) System to the Dexcom G6 in three European countries. Methods: Anonymised RT‐CGM data (uploaded to the Dexcom Clarity app) were from users in Germany, Sweden, and the United Kingdom (UK) who transitioned from G5 to G6 between 9‐12 months after G6 launched in 2018. Primary endpoints were percent time in hypoglycaemia, percent time in range (TIR), user retention rates, device utilisation, and urgent low soon (ULS) alert utilisation. Metrics were computed for 3‐month intervals in the 2‐year study window. Results: In all three countries, the transition from G5 to G6 was associated with a clear decrease in hypoglycaemia. In months 0‐3 after transitioning, the median percent time 〈3 mmol/L (54 mg/dL) and 〈3.9 mmol/L (70 mg/dL) decreased by [0.12‐0.28] and [0.40‐0.43] percentage points, respectively, with another [0.11‐0.21] and [0.34‐0.65] percentage point decrease in months 3‐6 in the three countries analysed. TIR and CGM utilisation were sustained or improved slightly across all countries. At the end of the study window, the retention rate was [88.8‐94.8%] and ULS utilization was [83.9‐86.9%] in the three countries analysed. Conclusions: Similar RT‐CGM trends were observed across Germany, Sweden, and the UK. Improvements in hypoglycaemia occurred in all countries. The high retention of users may lead to sustained glycaemic benefits associated with RT‐CGM use. [ABSTRACT FROM AUTHOR]

Aims: To explore the association between the use of glycaemic technologies and person‐reported outcomes (PROs) in adults with type 1 diabetes (T1D). Methods: We included T1D and technology publications reporting on PROs since 2014. Only randomised controlled trials and cohort studies that used validated PRO measures (PROMs) were considered. Results: T1D studies reported on a broad range of validated PROMs, mainly as secondary outcome measures. Most studies examined continuous glucose monitoring (CGM), intermittently scanned CGM (isCGM), and the role of continuous subcutaneous insulin infusion (CSII), including sensor‐augmented CSII and closed loop systems. Generally, studies demonstrated a positive impact of technology on hypoglycaemia‐specific and diabetes‐specific PROs, including reduced fear of hypoglycaemia and diabetes distress, and greater satisfaction with diabetes treatment. In contrast, generic PROMs (including measures of health/functional status, emotional well‐being, depressive symptoms, and sleep quality) were less likely to demonstrate improvements associated with the use of glycaemic technologies. Several studies showed contradictory findings, which may relate to study design, population and length of follow‐up. Differences in PRO findings were apparent between randomised controlled trials and cohort studies, which may be due to different populations studied and/or disparity between trial and real‐world conditions. Conclusions: PROs are usually assessed as secondary outcomes in glycaemic technology studies. Hypoglycaemia‐specific and diabetes‐specific, but not generic, PROs show the benefits of glycaemic technologies, and deserve a more central role in future studies as well as routine clinical care. [ABSTRACT FROM AUTHOR]

Objectives: Elevated glucose variability may be one mechanism that increases risk for significant psychological and physiological health conditions among individuals with binge‐spectrum eating disorders (B‐EDs), given the impact of eating disorder (ED) behaviors on blood glucose levels. This study aimed to characterize glucose variability among individuals with B‐EDs compared with age‐matched, sex‐matched, and body mass index‐matched controls, and investigate the association between frequency of ED behaviors and glucose variability. Methods: Participants were 52 individuals with B‐EDs and 22 controls who wore continuous glucose monitors to measure blood glucose levels and completed ecological momentary assessment surveys to measure ED behaviors for 1 week. Independent samples t‐tests compared individuals with B‐EDs and controls and multiple linear regression models examined the association between ED behaviors and glucose variability. Results: Individuals with B‐EDs demonstrated numerically higher glucose variability than controls (t = 1.42, p =.08, d = 0.43), although this difference was not statistically significant. When controlling for covariates, frequency of ED behaviors was significantly, positively associated with glucose variability (t = 3.17, p =.003) with medium effect size (f2 = 0.25). Post hoc analyses indicated that binge eating frequency was significantly associated with glucose variability, while episodes of 5+ hours without eating were not. Discussion: Glucose variability among individuals with B‐EDs appears to be positively associated with engagement in ED behaviors, particularly binge eating. Glucose variability may be an important mechanism by which adverse health outcomes occur at elevated rates in B‐EDs and warrants future study. Public Significance: This study suggests that some individuals with binge ED and bulimia nervosa may experience elevated glucose variability, a physiological symptom that is linked to a number of adverse health consequences. The degree of elevation in glucose variability is positive associated with frequency of eating disorder behaviors, especially binge eating. [ABSTRACT FROM AUTHOR]

The article presents the discussion on general guidelines regarding the gold standard of ambulatory care for children, adolescents, and young adults with type 1 diabetes (T1D). Topics include guidance on current diabetes technology being expanded to include relevant information on telemedicine, data support, education and literacy; and clear and consistent communication around education and treatment plans being essential.

Background: The aim of this study was to assess and compare the time in range (TIR) of children with type 1 diabetes (T1D) before and during a diabetes summer camp using different therapy modalities. Methods: A retrospective analysis of continuous glucose monitoring (CGM) data collected from 26 children with T1D (mean age: 11.0 ± 1.4 years; 62% female; 62% on insulin pump; Hb1Ac 7.3 ± 0.8% (56.3 ± 8.7 mmol/mol) before and during a 14-day summer camp. CGM methods: 50% intermittently scanned CGM (isCGM) and 50% real-time CGM (rtCGM). No child was using a hybrid closed loop system. Results: Mean TIR during camp was significantly higher than before camp ((67.0 ± 10.7%) vs. 58.2% ± 17.4%, p = 0.004). There was a significant reduction in time above range (TAR) (p = 0.001) and increase in time below range (TBR) (p < 0.001), Children using isCGM showed a more pronounced improvement in TIR during camp compared to rtCGM-users (p = 0.025). The increase in TIR strongly correlated with numbers of scans per day in isCGM-users (r = 0.751, p = 0.003). Compared to isCGM-users, rtCGM-users showed significantly less TBR. The TIR target was met by 30.8% of participants during camp. Conclusion: Glycemic control improved significantly during the camp. However, on average, the therapy goal (TIR > 70%) could not be achieved despite great professional effort. [ABSTRACT FROM AUTHOR]

Real‐time continuous glucose monitoring (rtCGM) and intermittently scanned CGM (isCGM) have both been shown to improve glycaemic outcomes in people with T1D. The aim of this study was to compare real‐world glycaemic outcomes at 6–12 months in a propensity score matched cohort of CGM naïve adults with T1D who initiated a rtCGM or an isCGM. Among the matched rtCGM and isCGM cohorts (n = 143/cohort), rtCGM users had a significantly greater HbA1c benefit compared to isCGM users (adjusted difference, −3 mmol/mol [95% CI, −5 to −1]; −0.3% [95% CI, −0.5 to −0.1]; p = 0.01). There was a significantly greater lowering of HbA1c for rtCGM compared to isCGM when baseline HbA1c was <69 mmol/mol (8.5%) (adjusted difference, −4 mmol/mol [95% CI, −7 mmol/mol to −2 mmol/mol]; −0.4% [95% CI, −0.6% to −0.2%]; p < 0.001), and in MDI users (adjusted difference, −3 mmol/mol [95% CI, −6 mmol/mol to −0 mmol/mol]; −0.3% [95% CI ‐0.5% to 0.0%], p = 0.04). The rtCGM cohort had significantly greater time in range (58.3 ± 16.1% vs. 54.5 ± 17.1%, p = 0.03), lower time below range (2.1 ± 2.7% vs. 6.1 ± 5.0%, p < 0.001) and lower glycaemic variability compared to the isCGM cohort. In this real‐world analysis of adults with T1D, rtCGM users had a significantly greater reduction in HbA1c at 6–12 months compared to isCGM, and significantly greater time in range, lower time below range and lower glycaemic variability, compared to a matched cohort of isCGM users. [ABSTRACT FROM AUTHOR]

Background: With advances in technology, there is an emerging concern that inequalities exist in provision and diabetes outcomes in areas of greater deprivation. We assess the relationship between socio‐economic status and deprivation with access to diabetes technology and their outcomes in adults with type 1 diabetes. Methods: Retrospective, observational analysis of adults attending a tertiary centre, comprising three urban hospitals in the UK. Socio‐economic deprivation was assessed by the English Indices of Deprivation 2019. Data analysis was performed using one‐way ANOVAs and chi‐squared tests. Results: In total, 1631 adults aged 44 ± 15 years and 758 (47%) women were included, with 391 (24%) using continuous subcutaneous insulin infusion, 312 (19%) using real‐time continuous glucose monitoring and 558 (34%) using intermittently scanned continuous glucose monitoring. The highest use of diabetes technology was in the least deprived quintile compared to the most deprived quintile (67% vs. 45%, respectively; p < 0.001). HbA1c outcomes were available in 400 participants; no association with deprivation was observed (p = 0.872). Participation in structured education was almost twice as high from the most deprived to the least deprived groups (23% vs. 43%; p < 0.001). Adults with white or mixed ethnicity were more likely to use technology compared to black ethnicity (60% vs. 40%; p < 0.001). Conclusions: Adults living in the most deprived quintile had less technology use. Irrespective of socio‐economic status or ethnicity, glycaemia was positively affected in all groups. It is imperative that health disparities are further addressed. [ABSTRACT FROM AUTHOR]

Introduction: Real‐time continuous glucose monitoring (rt‐CGM) allows patients with diabetes to adjust insulin dosing, potentially improving glucose control. This study aimed to compare the long‐term cost‐effectiveness of the Dexcom G6 rt‐CGM device versus self‐monitoring of blood glucose (SMBG) and flash glucose monitoring (FGM) in Australia in people with type 1 diabetes (T1D). Methods: Long‐term costs and clinical outcomes were estimated using the CORE Diabetes Model. Clinical input data for the analysis of rt‐CGM versus SMBG and FGM were sourced from the DIAMOND study and a network meta‐analysis, respectively. Rt‐CGM and FGM were associated with quality of life (QoL) benefits due to reduced fear of hypoglycaemia (FoH) and fingerstick testing. Analyses were performed over a lifetime time horizon from an Australian healthcare payer perspective, including direct costs from published data. Future costs and clinical outcomes were discounted at 5% per annum. Results: Rt‐CGM was associated with an increased quality‐adjusted life expectancy of 1.199 quality‐adjusted life years (QALYs), increased mean total lifetime costs of AUD 21,596 and an incremental cost‐effectiveness ratio (ICER) of AUD 18,020 per QALY gained compared with SMBG. Compared with FGM, rt‐CGM was associated with an increased quality‐adjusted life expectancy of 0.569 QALYs, increased mean total lifetime costs of AUD 11,064 and an ICER of AUD 19,455 per QALY gained. Key drivers of outcomes included HbA1c benefits and QoL benefits associated with reduced FoH and fingerstick testing. Conclusions: Due to improved clinical outcomes and QoL gains rt‐CGM is highly cost‐effective compared with SMBG and FGM in people with T1D in Australia. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aims: Reliable estimation of the time spent in different glycaemic ranges (time‐in‐ranges) requires sufficiently long continuous glucose monitoring. In a 2019 paper (Battelino et al., Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care. 2019;42:1593‐1603), an international panel of experts suggested using a correlation‐based approach to obtain the minimum number of days for reliable time‐in‐ranges estimates. More recently (in Camerlingo et al., Design of clinical trials to assess diabetes treatment: minimum duration of continuous glucose monitoring data to estimate time‐in‐ranges with the desired precision. Diabetes Obes Metab. 2021;23:2446‐2454) we presented a mathematical equation linking the number of monitoring days to the uncertainty around time‐in‐ranges estimates. In this work, we compare these two approaches, mainly focusing on time spent in (70‐180) mg/dL range (TIR). Methods: The first 100 and 150 days of data were extracted from study A (148 subjects, ~180 days), and the first 100, 150, 200, 250 and 300 days of data from study B (45 subjects, ~365 days). For each of these data windows, the minimum monitoring duration was computed using correlation‐based and equation‐based approaches. The suggestions were compared for the windows of different durations extracted from the same study, and for the windows of equal duration extracted from different studies. Results: When changing the dataset duration, the correlation‐based approach produces inconsistent results, ranging from 23 to 64 days, for TIR. The equation‐based approach was found to be robust versus this issue, as it is affected only by the characteristics of the population being monitored. Indeed, to grant a confidence interval of 5% around TIR, it suggests 18 days for windows from study A, and 17 days for windows from study B. Similar considerations hold for other time‐in‐ranges. Conclusions: The equation‐based approach offers advantages for the design of clinical trials having time‐in‐ranges as final end points, with focus on trial duration. [ABSTRACT FROM AUTHOR]

Despite some negative reports regarding the need for the self-monitoring of blood glucose (SMBG), including the issue of cost-effectiveness, there are still many users, and in diabetes treatment, which is largely dependent on the patient's self-care, SMBG remains an important tool in establishing such self-care habits, with several reports supporting this notion. In addition, devices are needed to assist in SMBG for patients with diabetes who have difficulty performing SMBG, such as the elderly or those with visual impairment. In current diabetes care, it is reported that patient-centered care that respects the preferences, needs, and values of individual patients and personalized care that consider the characteristics and comorbidities of each patient are important. Through a case study of a patient with diabetes who had difficulty performing SMBG due to visual impairment, we learned of the needs of SMBG and its assistive devices and the importance of patient and family engagement with emphasis on patient-centered and personalized care. We herein report what we learned through this case in the form of perspectives. Through this report, we hope that medical professionals involved in diabetes care will learn of the importance and needs of these issues and apply them to their actual clinical practice. Graphical [ABSTRACT FROM AUTHOR]

Context: The interaction of glycated hemoglobin A1c (HbA1c) and glycemic variability in relation to diabetes-related outcomes remains unknown.Objective: To evaluate the relationship between HbA1c and all-cause mortality across varying degrees of glycemic variability in patients with type 2 diabetes.Design, Setting, and Patients: This was a prospective study conducted in a single referral center. Data of 6090 hospitalized patients with type 2 diabetes was analyzed. Glucose coefficient of variation [coefficient of variation (CV)] was obtained as the measure of glycemic variability by using continuous glucose monitoring for 3 days. Cox proportional hazards regression models were used to estimate hazard ratios and 95% CIs for all-cause mortality.Results: During a median follow-up of 6.8 years, 815 patients died. In patients with the lowest and middle tertiles of glucose CV, HbA1c ≥ 8.0% was associated with 136% (95% CI 1.46-3.81) and 92% (95% CI 1.22-3.03) higher risks of all-cause mortality, respectively, as compared with HbA1c 6.0%-6.9%, after adjusting for confounders. However, a null association of HbA1c with mortality was found in patients with the highest tertile of glucose CV.Conclusions: HbA1c may not be a robust marker of all-cause mortality in patients with high degree of glycemic variability. New metrics of glycemic control may be needed in these individuals to achieve better diabetes management. [ABSTRACT FROM AUTHOR]

Aims: Most people living with type 1 diabetes self‐manage using multiple daily injection (MDI) insulin regimens and self‐monitoring of blood glucose (SMBG). Continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) are adjuncts to education and support self‐management optimization. The aim of this systematic review and meta‐analysis was to assess which first‐line technology is most effective. Methods: Electronic databases (MEDLINE, EMBASE and WEB OF SCIENCE) were systematically searched from 1999 to September 2020. Randomized controlled trials comparing either CSII with MDI or CGM with SMBG in adults with type 1 diabetes were included. Data were extracted in duplicate by two reviewers, and were analysed to assess individual and overall treatment effect measures (PROSPERO registration: CRD42020149915). Results: Glycated haemoglobin was significantly reduced for CGM when compared with SMBG [Cohen's d − 0.62 (95% CI −0.79 to −0.45)] and for CSII when compared with MDI [Cohen's d − 0.44 (95% CI −0.67 to −0.22)]. Rates of severe hypoglycaemia were significantly reduced with CGM compared with SMBG, but did not change for CSII when compared with MDI. Episodes of diabetic ketoacidosis were more likely to occur with CSII than MDI. Both CSII and CGM reduced glucose standard deviation, compared with MDI and SMBG respectively. Conclusions: Both CGM and CSII remain impactful interventions compared with SMBG and MDI but in adults with type 1 diabetes and in the contexts in which they have been studied, CGM might have a greater positive impact on glycaemic variability and severe hypoglycaemia than CSII, when added to MDI and SMBG. A head‐to‐head study, including patient reported outcomes, is required to explore these findings further. [ABSTRACT FROM AUTHOR]

The author reflects on diabetes mellitus and diabetes remission. Other topics include the challenges faced by patients in glucose self-management due to factors like insulin resistance, the risk of cardiometabolic work facing night shift workers, and the study commissioned by the United Kingdom (UK) Government Scientific Advisory Committee on Nutrition on the effects of lower carbohydrate diets.