Adult-onset type 1 diabetes (T1D) is often misclassified as type 2 diabetes (T2D), resulting in delayed treatment, missed opportunities for referrals to specialists and increased risk of complications including diabetic ketoacidosis. An electronic medical record (EMR)-based algorithm—originally trained on a large national EMR dataset to identify likely misclassified adult-onset T1D cases—was tested and retrained on a health information exchange (HIE) dataset from HealthShare Exchange (HSX). Promising results were achieved on historical data, particularly when using the retrained algorithm. However, its prospective validation is essential to more reliably assess its clinical utility and real-world precision in flagging high-risk patients for clinician review.

This is a prospective, multicentre, non-interventional cohort study in two HSX-member healthcare organisations (HCOs) in southeastern Pennsylvania. At the onset of the study, all adult T2D patients are scored by the algorithm analysing HIE data on relevant predictors found in the 24-month lookback period. Patients meeting a prespecified score threshold estimated in retrospective testing to yield 10% recall will be presented to designated endocrinology or primary care providers for structured chart review, attribution confirmation and guideline-concordant follow-up (including autoantibody testing where appropriate). The primary endpoint is positive predictive value for confirmed adult-onset T1D among flagged patients. Secondary endpoints characterise operational cascade metrics (attribution, provider recommendation, test ordering/results and diagnosis updates) along with 95% CIs. Exploratory endpoints will assess provider adoption, interpretability and workflow integration via structured provider interviews.

This study was reviewed and approved by Advarra Institutional Review Board (protocol Pro00075945). The Institutional Review Board waived patient informed consent and granted a full waiver of HIPAA authorisation for patient records, while providers were required to provide written informed consent. HSX data were accessed and shared under its member-defined use cases. Findings will be disseminated via peer-reviewed publications and conference presentations. Reporting will follow Strengthening the Reporting of Observational Studies in Epidemiology guidance for cohort studies.

Type 2 diabetes (T2D) presents a global healthcare burden. Despite widespread use of non-insulin glucose lowering therapies, many individuals still require insulin to achieve recommended target glycated haemoglobin (HbA1c). Insulin injections improve HbA1c but can lead to problematic hypoglycaemia. The objective of this study is to determine whether fully closed-loop insulin delivery improves HbA1c at 26 weeks compared with standard insulin therapy with continuous glucose monitoring (CGM) in adults with T2D.

This study adopts an open-label, multinational, randomised, single-period parallel design and aims to randomise 224 adults with T2D to either standard insulin therapy with CGM (control group) or fully closed-loop insulin delivery (intervention group) for a period of 26 weeks. Participants will complete a run-in period of 2–3 weeks wearing a masked CGM followed by randomisation to either the control or intervention group. The primary endpoint is the between-group difference in HbA1c at 26 weeks. Key endpoints include time in target glucose range (3.9–10.0 mmol/L), mean sensor glucose, time above range (>10.0 mmol/L) and non-inferiority for time below target (

The study has received ethical approval from the East of England Cambridgeshire and Hertfordshire Research Ethics Committee (24/EE/0149) in the UK. Ethical approval for non-UK site has been obtained by local Research Ethics Committees.

Results will be disseminated by peer-reviewed publications and conference presentations, and findings will be shared with people living with diabetes, healthcare providers and relevant stakeholders.

NCT06579404.