Abstract Aims There is emerging evidence that maternal hyperglycaemia may be associated with adverse offspring neuro‐behavioural outcomes, which are foundational to educational success. We hypothesised that higher levels of maternal glucose would be associated with poorer educational attainment in early childhood. Methods The sample included 13,627 children from the UK's Born in Bradford cohort. Exposures included maternal fasting glucose, 2‐h post‐load glucose and a clinical diagnosis of gestational diabetes. The primary outcome was failure to achieve a ‘good level of development’ on the Early Years Foundation Stage Profile at age five. The association was tested using multivariable Poisson regression, accounting for sibling clusters and using multiple imputation for missing data. Results Higher maternal fasting glucose (at 26–28 weeks gestation) was associated with an increased risk of failing to achieve a good level of development (adjusted RR 1.04; 95% CI 1.00, 1.08; p = 0.034). This association appeared stronger in children of Pakistani ethnicity compared to White British ethnicity. No association was found for 2‐h post‐load glucose or gestational diabetes diagnosis. Conclusions These findings offer insights into the developmental origins of inequalities in child educational outcomes and highlight potential opportunities to optimise future health and learning through interventions during pregnancy.

AimsThe elevated risk of all‐cause and cardiovascular mortality in individuals with type 2 diabetes mellitus (T2DM) has led to growing efforts to develop prognostic models for early identification of high‐risk individuals. This systematic review synthesised existing models to inform future model development, enhance predictive performance and guide targeted prevention strategies in diverse clinical and population health settings.MethodsWe systematically searched Ovid MEDLINE, Scopus and Web of Science for studies published between January 1, 2015, and June 11, 2024, reporting prognostic models developed and/or validated to predict all‐cause or cardiovascular mortality in individuals T2DM. Data were extracted following the CHARMS checklist, and risk of bias assessed using the PROBAST tool.ResultsThe search yielded 18,126 records; 10,921 were screened after deduplication. Of 147 full texts assessed, 26 cohort studies met inclusion criteria, with sample sizes (median [IQR]: 20,554 [1931–59,180]). Models were developed in diverse regions, with the highest number from Taiwan (n = 5) and the USA (n = 5). Most studies focused on all‐cause mortality (n = 26); eight addressed cardiovascular mortality. Prediction horizons varied from 1 to 15 years, with 5‐year risk being the most common (n = 10). Discrimination had a median C‐statistic of 0.77 (IQR: 0.72–0.81). Calibration was reported in 20 studies, though methods varied. Cox regression was the most common statistical method (n = 16).ConclusionsPrediction models for mortality in T2DM show considerable heterogeneity in methodology, performance and validation. Limited external validation and inconsistent calibration reporting highlight the need for robust, generalisable and transparently reported models to improve clinical risk stratification in diabetes care.

AimsThe mental health impact of impaired awareness of hypoglycaemia (IAH) in people with type 2 diabetes (T2D) is not known. We explored this in people with insulin‐treated T2D and type 1 diabetes (T1D).MethodsHypo‐METRICS was a 10‐week cross‐sectional observation of hypoglycaemia experience, collecting data on glucose and activity. Participants (325 insulin‐treated T2D, 277 T1D) completed questionnaires scoring depression (PHQ‐9), anxiety (GAD‐7), diabetes distress (PAID) and fear of hypoglycaemia (HFS‐II [worry]) at baseline. IAH was defined as a Gold score ≥4. Relationships between IAH and mental health scores were explored using unadjusted and adjusted generalised linear regression analyses. Age, sex, race, diabetes duration, level of education, employment status, continuous glucose monitoring (CGM) use, hypoglycaemia, use of anti‐depressants and use of anti‐anxiety medications were covariates in the adjusted regression.ResultsIn unadjusted regression in insulin‐treated T2D, IAH was associated with higher PHQ‐9 (6.4% [1.5%–11.3%]; p = 0.011), GAD‐7 (7.6% [2.1%–13%]; p = 0.006) and HFS‐II (worry) (7.4% [2.8%–12%]; p = 0.002) scores, with no differences in PAID (p = 0.655). After adjustment, IAH was associated with higher HFS‐II (worry) (5.3% [0.3%–10.6%]; p = 0.048) only. In T1D, IAH was associated with higher PHQ‐9 (6.2% [1.3%–10.8%]; p = 0.012), GAD‐7 (6.1% [0.1%–12.2%]; p = 0.046) and HFS‐II (worry) (6.1% [0.06%–11.5%]; p = 0.029) scores, but not PAID (p = 0.654), all unadjusted. These relationships remained after adjustment, which also showed higher PAID (8.43% [2.62%–14.24%]; p = 0.005).ConclusionOur data demonstrated associations between IAH and a greater mental health burden in both insulin‐treated T2D and T1D. Addressing these mental health challenges should be an important part of the holistic care of people with IAH and insulin‐treated diabetes.

AimsPeople with diabetes who are admitted to hospital are at risk of adverse in‐hospital outcomes due to glycaemic dysregulation. Both the prevalence of diabetes and adverse outcomes are higher in rural and regional hospitals where infrastructure is more limited. Digital solutions may facilitate diabetes assessment on admission, so timely care coordination can be provided by inpatient diabetes teams. The aim of this systematic review was to identify and characterise the digital technologies and clinical decision support tools used to triage people with diabetes in the inpatient setting.MethodsSix electronic databases were searched for studies published between January 2014 and August 2024 on the use of digital technology or decision support tools to triage adult inpatients with diabetes during a hospital stay. Narrative synthesis was used to report results. The review followed PRISMA guidelines and was registered on PROSPERO (CRD 42021257655).ResultsNine studies met the inclusion criteria. Three developed or improved systems for referrals to an in‐hospital diabetes team. The remaining six reported on efforts to improve information to support referral and included risk prediction for iatrogenic hypoglycaemia, persistent adverse glycaemia and in‐hospital mortality among Intensive Care Unit patients with diabetes, and perioperative glycaemic management.ConclusionsDigital technologies and clinical decision support tools can improve inpatient triage of people with diabetes. A two‐tiered approach consisting of a simple admission risk screen tool followed by dynamic electronic health record surveillance focussed on immediate iatrogenic hypoglycaemia risk for ongoing prioritisation would balance sensitivity at admission with dynamic inpatient risk monitoring.

AimsTo explore UK key‐opinion leader perspectives on the future role of stem cell‐derived islets (sc‐islets) in islet transplantation for people with type 1 diabetes (T1D).MethodsFour UK‐based key‐opinion leaders evaluated current limitations of donor islet transplantation and reviewed emerging evidence, clinical pathways and logistical considerations for sc‐islet transplantation, including alternative delivery sites and implications for kidney transplantation strategies.ResultsConventional islet transplantation is constrained by donor scarcity, variable graft quality and lifelong immunosuppression, with associated risks of infection, malignancy and calcineurin inhibitor (CNI) nephrotoxicity. Stem cell‐derived islets, generated from human embryonic and induced pluripotent stem cells, provide a scalable and standardised alternative. Early investigational products, including Zimislecel (VX‐880), demonstrate potential for insulin independence and may offer an alternative to simultaneous pancreas–kidney (SPK) transplantation. Strategies to reduce or eliminate systemic immunosuppression particularly CNI immunosuppression through local immunomodulation, gene editing and encapsulation technologies may further broaden access. Ethics, infrastructural and economic considerations remain central to equitable implementation.ConclusionStem cell–derived islets may redefine islet transplantation for T1D by enabling more scalable, less invasive and sustainable therapeutic pathways while maintaining access to technological diabetes management options.