AIMS:The UNBIASED UK study is the first national study that explores disparities in access to diabetes technology among children and young people (CYP) with type 1 diabetes (T1D) from ethnic minority and low socioeconomic backgrounds in the United Kingdom. Despite the National Institute for Health and Care Excellence guidance ensuring free universal access to diabetes technologies since 2023, significant inequities persist. This article outlines key barriers and provides recommendations to improve equitable access and engagement with diabetes technologies for CYP. METHODS:A multimethod participatory approach was used, including semi-structured triad interviews with parents and CYP of underrepresented groups living in low socioeconomic areas and minority ethnic groups. Health care professionals from the National Health Service were also interviewed to explore perceived and systemic barriers to technology adoption. Thematic analysis identified key challenges and potential solutions, and new recommendations were sought from codesigned workshops and public consultations were further developed. RESULTS:The UNBIASED study identified key themes from parents, children, and young people, including barriers to access, experiences with diabetes technology, inconsistent services and education, intersectional challenges, communication issues, and emotional support needs. Health care professionals highlighted financial limits, language barriers, regional service differences, unconscious bias, and low awareness as major factors contributing to disparities. Key strategies and new recommendations are made to improve fair access to diabetes technologies, including systemic reforms, better communication and support, and stronger community engagement. CONCLUSIONS:This UK UNBIASED study highlights the urgent need for standardized policies, increased awareness campaigns, culturally tailored education, peer support initiatives, and improved health care provider training to ensure equitable access to diabetes technology for all CYP with T1D in the United Kingdom.

Achieving glucose targets without hypoglycaemia is the treatment goal in type 1 diabetes. Structured education, intensified insulin injection regimens, continuous glucose monitoring, automated insulin delivery, and ongoing support from a multidisciplinary team all support people with type 1 diabetes to achieve this goal. Despite these advances, significant barriers to achieving optimal management remain. Continuous intraperitoneal insulin infusion has comparable or better glucose outcomes to continuous subcutaneous insulin infusion and may reduce the frequency of hypoglycaemia, including severe episodes. Intraperitoneal insulin may be considered as a treatment modality for children and adults with type 1 diabetes using optimised intensive insulin therapy for whom subcutaneous insulin has failed due to lipoatrophy, -dystrophy or -hypertrophy, local allergy, subcutaneous insulin resistance or co-existing skin conditions. Failure of subcutaneous insulin may result in recurrent or unexplained severe hypoglycaemia or hyperglycaemia. Intraperitoneal insulin may also be considered as a treatment modality for people with type 1 diabetes with severe needle-phobia, and for those being considered for islet cell or pancreatic transplantation, or where transplantation is not available. This paper summarises current intraperitoneal insulin delivery technology, its potential risks and benefits, and an expert position statement. It is intended for use by diabetes specialist healthcare professionals, and as a reference for other healthcare professionals, commissioners, payors, people with diabetes, their carers, and advocates.

AIMS:Access to diabetes technology in the UK is significantly influenced by socio-economic status, ethnicity, and systemic healthcare inequities. This study investigates barriers faced by children and young people (CYP) from ethnic minority backgrounds and/or low socio-economic areas in accessing diabetes technologies, alongside strategies for equitable improvements. METHODS:Online semi-structured interviews were conducted across the UK with parents and caregivers of CYP (aged 2-17 years) with type 1 diabetes (T1DM) and young people (aged 14-17 years) from ethnic minority groups and low socio-economic areas. Participants were recruited via purposive sampling. Interviews were transcribed, coded, and analysed using a thematic reflexive analysis in QSR NVivo12. RESULTS:Thirty-two participants were included in the study. Of these, 27 triad interviews were completed involving parents and CYP, along with an additional five triad interviews led by young people. The majority of parents and CYP identified as being from Black African ethnic minority groups (72%), 13% were from Other Black ethnic groups, and a smaller proportion were from Asian minority groups, (8%) and Other ethnic minority groups (6%). Key themes included barriers to accessibility (e.g., financial, linguistic, and geographic challenges), variability in education and service provision, intersectional barriers (e.g., race and socio-economic status), and the need for improved communication and trust with healthcare professionals. The findings highlight the persistent inequities in diabetes technology access among underserved groups. CONCLUSION:Barriers to diabetes technology access for CYP from ethnic minority backgrounds and low socio-economic areas stem from an interplay of systemic inequities, cultural and linguistic challenges, and financial constraints. This study highlights the need for systemic reforms, including culturally tailored and standardised education programmes alongside equitable resource distribution, to address these barriers.

AIMS:This study aimed to explore barriers to diabetes technology access and co-create an educational animation to address them. METHODS:Guided by a community-based participatory research (CBPR) approach and the Generative Co-Design Framework for Healthcare Innovation, the study followed three stages: Pre-Design, Co-Design, and Post-Design. It built on prior qualitative research and was shaped by input from an advisory panel. Co-design workshops informed the animation's content and style. A total of 16 participants were involved: 6 (2 parents, 4 young people) contributed to advisory sessions, and 10 (5 parents, 5 children and young people) participated in co-design workshops. Data were analysed using reflexive thematic analysis. RESULTS:Key barriers included misconceptions about cost, limited awareness of NHS-funded technologies, and emotional and financial burdens. Participants emphasised the importance of diverse representation, accessible language, and engaging visuals to ensure the animation resonated with a wide audience, including healthcare professionals, families, educators, and policymakers. Post-design evaluation confirmed its usability. CONCLUSIONS:Guided by collaborative principles, the co-designed animation is a valuable tool for raising awareness and promoting equitable access to diabetes technology. Future research should explore broader implementation and standardisation of such educational tools across NHS services.

Introduction and Objective: A recent study comparing Freestyle Libre (FSL) 3, Dexcom (Dex) G7, and Medtronic (Med) Simplera CGM systems found discordant glycaemic metrics, with Med showing a significantly lower glucose management indicator (GMI) and a higher time-in-range. The purpose of this study was to assess concordance between laboratory HbA1c and GMI from three sensor families (Dex G6/G7; FSL L2/L2+/L3/L3+ and Med Guardian4/Simplera) under real-world conditions. Methods: Retrospective, observational, three-centre study of adults with type 1 diabetes (n=349, age 43±14, duration of diabetes 25±13) treated with a range of automated insulin delivery (AID) systems, comprising FSL (n=50), Dex (n=212), and Med sensors (n=87). We assessed glycaemic metrics for 90 days preceding the date of the lab A1c. Results: All three sensor families showed good overall GMI alignment with Lab A1c [%], with a glucose-variability (CV%) adjusted mean deviation of <0.2%. [GMI-Lab A1c; Mean, 95% CI; Dex +0.18% (+0.11, +0.26); FSL -0.02% (-0.17, +0.13); Med -0.16% (-0.28, -0.05), p < 0.001 with difference between Dex and the other two sensors, and no difference between Med and the FSL family. Bland-Altman plots for the three sensor families (Figure) show broadly similar patterns. Conclusion: We show good alignment between 90-day GMI and Lab A1c across all three sensor families under real-world conditions. We did not detect a clinically significant systematic bias towards lower GMI with Medtronic sensors. Disclosure L. Farouk: None. B. Bashir: None. R. Seese: None. P. Avari: Research Support; Current; Dexcom, Inc., Diabetes UK. M. Reddy: Research Support; Current; Dexcom, Inc., Medtronic, Roche Diabetes Care. Advisory Panel; Ended; Medtronic. N. Oliver: Research Support; Current; Dexcom, Inc., Roche Diabetes Care. Speaker's Bureau; Current; Sanofi. Speaker's Bureau; Ended; AstraZeneca. Research Support; Current; Medtronic. Speaker's Bureau; Ended; Dexcom, Inc. M. Evans: Other - Triallist, speaker, advisory board; Current; Abbott Diabetes. Other - Research support, speaker, advisory board; Current; Novo Nordisk A/S. Other - Triallist, advisory board, speaker; Current; Sanofi. Other - Triallist, speakers fees; Current; Eli Lilly and Company. Other - Triallist, advisory board; Current; Medtronic. Other - Advisory board; Current; Dexcom, Inc. Advisory Panel; Current; Zucara Therapeutics, vTv Therapeutics. Other - Advisory panel, triallist; Current; Pila Pharma. H. Thabit: Speaker's Bureau; Ended; Eli Lilly and Company. Speaker's Bureau; Current; Insulet Corporation. Research Support; Current; Dexcom, Inc. Advisory Panel; Current; Roche Diabetes Care. L. Leelarathna: Research Support; Current; Abbott Diabetes. Speaker's Bureau; Current; Abbott Diabetes, Insulet Corporation. Consultant; Ended; Insulet Corporation. Advisory Panel; Ended; Vertex Pharmaceuticals Incorporated.

Background: No randomised controlled trials have directly compared commercially available hybrid automated insulin delivery (AID) systems, and real-world comparative data remain limited. This study evaluated glycaemic outcomes across three hybrid AID systems in adults with type 1 diabetes (T1D). Methods: This was a retrospective, observational, single-centre study and included adults with T1D who transitioned from multiple daily injections (MDI) or non-automated insulin pump therapy to hybrid AID. Data were collected from routinely used clinical data-sharing platforms and electronic health records. Outcomes compared across systems included time in range (TIR; 3.9-10.0 mmol/L), time below range (TBR; <3.9 and <3.0 mmol/L), time above range (TAR; >10.0 and >13.9 mmol/L), glucose management indicator (GMI, %) and coefficient of variation (CV, %). Results: A total of 213 participants were included (Medtronic 780G n = 38; Tandem Control-IQ n = 81; Omnipod 5 n = 94). After adjustment for baseline TIR, diabetes duration, insulin modality and AID use duration 780G users achieved a higher TIR increase (21.1% [95% CI 18.4-23.7]) compared to Control-IQ (10.1% [3.2-17.3], p = 0.010) and Omnipod 5 (15.2% [12.9-17.5], p = 0.002), with corresponding reductions in TAR. Conclusion: All three hybrid AID systems were associated with improvements in glycaemic outcomes in real-world use, supporting the role of AID systems in the management of T1D. Medtronic 780G use was associated with higher TIR increase compared with the other systems; however, these findings are based on measurements from different continuous glucose monitors between AID groups and cannot be used to infer superiority in glycaemic attainment.

AIMS:To characterise differences in dietary intake, glucose variability, and activity in free-living healthcare shift workers with type 2 diabetes (T2D) across varying work conditions. METHODS:Healthcare shift workers with T2D were monitored over 10 days, covering night shifts, day shifts, and rest days. Data were collected using blinded continuous glucose monitoring, activity trackers, and diet/sleep diaries. Within-person comparisons were made for mean glucose (MG), coefficient of variation (CV), mean absolute glucose change (MAG), mean amplitude of glycaemic excursion (MAGE), continuous overlapping net glycaemic action (CONGA), dietary intake (food choices, nutrient intake), and activity/rest periods. RESULTS:The study sample (n = 37; 89.2% women) were mainly employed as nurses or midwives (62.2%). Energy intake was highest (2199 kcal SD 648) on a day when a night shift was worked. Percentage of energy intake from sweet snacks was higher on a night shift compared with a rest day after a night shift (13.4 SD 12.0% vs. 7.8 SD 11.8%, p = 0.013). Night shifts had the highest eating occasions (7.0 SD 2.2) and rest after night (RAN) the lowest (3.4 SD 1.6), p < 0.001. No differences were reported for MG, MAGE, or CV. MAG and CONGA were higher for night shift compared with RAN shift (p = 0.029). Step counts were higher on night shift days (13,775, SD 4270 p = 0.016), and participants were awake longer (22.2 h SD 2.4 h, p < 0.001) compared with other day types. CONCLUSIONS:Night shifts are associated with prolonged wakefulness, increased activity, and distinct dietary behaviours. Tailored interventions are needed to support night shift workers with T2D in managing their condition effectively.

Incorporating sex-specific factors in diabetes research and treatment is essential for advancing precision medicine. There are critical gaps in understanding and applying sex-related differences. Female-specific diabetes pathophysiology manifests in three major areas: life cycle phases (including puberty, pregnancy, and menopause), lifestyle factors (such as responses to nutrition and physical activity), and insulin pharmacology. These elements significantly affect insulin sensitivity and glycemic control in women, yet are frequently underrepresented or ignored in both research and clinical practice. Greater research and clinical focus across these domains is needed to better understand and address sex-based differences in diabetes. Identifying and filling evidence gaps will support more systematic and effective care.

Type 1 and type 2 diabetes are associated with increased severity and mortality from respiratory virus infections. Vaccination in the general population significantly reduces the risk of severe respiratory viral infection and triggers a strong, polyfunctional, and lasting T cell response in healthy individuals. However, vaccine effectiveness in people with type 1 diabetes is unclear. Here, we studied the magnitude and functional characteristics of vaccine-specific CD4(+) and CD8(+) T cell responses to vaccination in people with type 1 and type 2 diabetes and compared them to those of people living without diabetes, using the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine as a model. We found defects in both CD4(+) and CD8(+ )T cell memory maintenance and the functionality of the vaccine-specific T cells in people with diabetes compared with people without. In those individuals with type 1 and type 2 diabetes who harbored detectable vaccine-specific T cells, they displayed an unfocused, tolerogenic phenotype characterized by increased expression of IL-10 and IL-13 compared with people without diabetes. These results have implications for vaccination strategies for people with diabetes.

Type 1 and type 2 diabetes are associated with increased severity and mortality from respiratory virus infections. Vaccination in the general population significantly reduces the risk of severe respiratory viral infection and triggers a strong, polyfunctional, and lasting T cell response in healthy individuals. However, vaccine effectiveness in people with type 1 diabetes is unclear. Here, we studied the magnitude and functional characteristics of vaccine-specific CD4 + and CD8 + T cell responses to vaccination in people with type 1 and type 2 diabetes and compared them to those of people living without diabetes, using the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine as a model. We found defects in both CD4 + and CD8 + T cell memory maintenance and the functionality of the vaccine-specific T cells in people with diabetes compared with people without. In those individuals with type 1 and type 2 diabetes who harbored detectable vaccine-specific T cells, they displayed an unfocused, tolerogenic phenotype characterized by increased expression of IL-10 and IL-13 compared with people without diabetes. These results have implications for vaccination strategies for people with diabetes.

Neonatal hypoglycemia (NH) is potentially life-threatening and can lead to long-term neurological sequelae. We retrospectively assessed the association between maternal glycemia in women with type 1 diabetes (T1D) and NH. Continuous glucose monitoring data from 60 mothers, alongside routine capillary blood glucose measurements from their neonates, were analyzed. The analyses used two clinically recognized thresholds for NH (<2.2 mmol/L and <2.6 mmol/L). In total, there were 25 neonates (41.7%) with NH <2.6 mmol/L and 19 neonates (31.7%) with NH <2.2 mmol/L. Neonates with NH <2.2 mmol/L were born at a lower gestational age (37.0 [35.9, 37.7] vs. 37.6 [37.0, 38.4] weeks, P = 0.019), a higher proportion was exposed to antenatal corticosteroids (31.6% vs. 7.3%, P = 0.014), and a higher proportion required admission to the neonatal intensive care unit (42.1% vs.12.2%, P = 0.009). Similar associations were observed for NH <2.6 mmol/L, although admission rates to the neonatal intensive care unit did not reach statistical significance. Mixed-effects logistic regression analysis identified percentage time above range (odds ratio [OR] 1.047, 95% confidence interval [CI] 1.007-1.087, P = 0.01) and percentage time in range (OR 0.951, 95% CI 0.914-0.989, P = 0.01) as significantly associated with NH <2.2 mmol/L. Our data suggest that careful optimization of glycemia early in pregnancy, rather than in the final trimester alone, may help minimize the risk of NH in infants born to mothers with T1D.

Real-time continuous glucose monitoring (CGM), augmented with accurate glucose prediction, offers an effective strategy for maintaining blood glucose levels within a therapeutically appropriate range. This is particularly crucial for individuals with type 1 diabetes (T1D) who require long-term self-management. However, with extensive glycemic variability, developing a prediction algorithm applicable across diverse populations remains a significant challenge. Leveraging meta-learning for domain generalization, we propose GPFormer, a Transformer-based zero-shot learning method designed for multi-horizon glucose prediction. We developed GPFormer on the REPLACE-BG dataset, comprising 226 participants with T1D, and proceeded to evaluate its performance using three external clinical datasets with CGM data. These included the OhioT1DM dataset, a publicly available dataset including 12 T1D participants, as well as two proprietary datasets. The first proprietary dataset included 22 participants, while the second contained 45 participants, encompassing a diverse group with T1D, type 2 diabetes, and those without diabetes, including patients admitted to hospitals. These four datasets include both outpatient and inpatient settings, various intervention strategies, and demographic variability, which effectively reflect real-world scenarios of CGM usage. When compared with a group of machine learning baseline methods, GPFormer consistently demonstrated superior performance and achieved the lowest root mean square error for all the evaluated datasets up to a prediction horizon of two hours. These experimental results highlight the effectiveness and generalizability of the proposed model across a variety of populations, demonstrating its substantial potential to enhance glucose management in a wide range of practical clinical settings.

The accuracy of the latest generation Dexcom G7 sensors in individuals with diabetes undergoing hemodialysis has not previously been investigated. Participants with diabetes undergoing hemodialysis were recruited, with paired sensor glucose from Dexcom G7 recorded with plasma glucose analyzed in the laboratory, as well as the Freestyle Precision Pro glucometer and EKF Biosen C-Line analyzer. Ten adults (median age 64.0 [58.0-74.5] years) were recruited. Overall percentage (%) mean and median absolute relative differences were 10.4% and 8.5% for matched laboratory pairs, respectively (n = 720). Diabetes Technology Society error grid analysis showed 99.7%, 100%, and 99.9% of pairs within zones A and B for lab, glucometer, and EKF methods, respectively. This, the first Dexcom G7 accuracy study conducted in people on hemodialysis, demonstrates accuracy and safety when compared with lab reference readings. These data support the accessibility of continuous glucose monitoring (CGM) and hybrid closed-loop systems for people with diabetes on hemodialysis.

Type 1 and type 2 diabetes are associated with increased severity and mortality from respiratory virus infections, including SARS-CoV-2. Vaccination in the general population significantly reduces the risk of severe respiratory viral infection and triggers a strong, polyfunctional and lasting T cell response in healthy individuals. However, vaccine effectiveness in people with diabetes is unclear. Here we studied the magnitude and functional characteristics of vaccine-specific CD4+ and CD8+ T cell responses to the full vaccination protocol, and the recall response after a third booster dose of SARS-CoV-2 vaccine in people with type 1 and type 2 diabetes, and compared them to those of people without diabetes. We found defects in both CD4+ and CD8+ T cell memory maintenance and the functionality of the vaccine specific T cells in people with diabetes compared to people without. In those individuals with diabetes that harbored detectable vaccine-specific T cells, they displayed an unfocused, tolerogenic phenotype characterized by increased expression of IL-13 and IL-10 in T1D and T2D compared to people without diabetes. These results have implications for vaccination strategies for people with diabetes. ### Competing Interest Statement The authors have declared no competing interest.