Diabetes technology: an update.
Clinical Snapshot
PICO Framework
| P — Population | People with type 1 and type 2 diabetes mellitus, including those in early-stage type 1 diabetes (antibody-positive pre-symptomatic) and those at risk of diabetic ketoacidosis at disease onset |
| I — Intervention | Diabetes technologies including continuous glucose monitoring (CGM), automated insulin delivery (AID) systems, adjunctive pharmacologic therapies, and artificial intelligence-assisted diabetes management tools |
| C — Comparator | Conventional glucose monitoring and standard insulin delivery methods; historical glycaemic management benchmarks (e.g., DCCT-era intensive therapy) |
| O — Outcomes | Glycated haemoglobin (HbA1c), time in range (TIR; 70–180 mg/dL), rates of severe hypoglycaemia, diabetic ketoacidosis (DKA) incidence, disease progression monitoring in early-stage type 1 diabetes, and equity of access to diabetes technologies |
Bottom Line
This Stanford-authored narrative mini-review provides a clinically useful, expert-curated summary of recent advances in diabetes technology — particularly CGM and automated insulin delivery systems — and their associations with improved glycaemic outcomes in type 1 and type 2 diabetes. The review highlights emerging applications including CGM-guided monitoring in pre-symptomatic type 1 diabetes and DKA prevention at disease onset, alongside the potential of adjunctive pharmacotherapy and AI-assisted management. However, clinicians should interpret this as expert opinion and narrative synthesis rather than high-certainty systematic evidence. No formal search strategy, risk of bias assessment, or GRADE evaluation was performed, and no independent pooled effect sizes are generated. The review's most important contribution may be its explicit acknowledgement of health equity disparities in technology access — a dimension directly relevant to Australian practice, particularly for Indigenous communities and those in rural and remote settings. For evidence-based clinical decision-making, practitioners should consult the primary randomised controlled trials and systematic reviews cited within this paper, alongside RACGP, ADS, and NDSS guidance on CGM and AID system eligibility.
Key Findings
P Value: Not reported by this review.
Effect Size: Not pooled by this review; effect sizes are derived from cited primary studies. The review does not generate independent quantitative estimates.
Primary Outcome: CGM and AID systems are associated with significant improvements in HbA1c and time in range (70–180 mg/dL), and reductions in severe hypoglycaemia and DKA rates in people with both type 1 and type 2 diabetes. Recent data indicate benefit early in the course of type 1 diabetes.
Nnt Or Sensitivity: Not calculated by this review. NNT for DKA prevention, NNT for severe hypoglycaemia reduction, and diagnostic performance of CGM in pre-symptomatic type 1 diabetes monitoring are not synthesised.
Confidence Interval: Not reported by this review; confidence intervals are available only in the cited primary literature.
Clinical Application
CGM and AID systems are increasingly available in high-income countries. Feasibility is constrained by device cost, consumable burden, digital literacy requirements, healthcare system infrastructure, and ongoing supply chain considerations. The review appropriately flags that technological innovation must be paired with equitable access strategies. In Australia, CGM is subsidised through the National Diabetes Services Scheme (NDSS) for people with type 1 diabetes and select type 2 diabetes populations on insulin. The Freestyle Libre 2 and Dexcom G7 are TGA-approved and NDSS-listed. AID systems including the Omnipod 5 and MiniMed 780G are TGA-approved; PBS/NDSS subsidy for AID consumables has been progressively expanding. RACGP and the Australian Diabetes Society (ADS) guidelines support CGM use in type 1 diabetes and recommend consideration in insulin-treated type 2 diabetes. The equity concerns raised in this review are directly relevant to Aboriginal and Torres Strait Islander communities and rural/remote Australians, where access to diabetes technology and specialist endocrinology care remains significantly inequitable. The emerging use of CGM in pre-symptomatic type 1 diabetes monitoring aligns with Australian TrialNet screening programmes. Adults and children with type 1 diabetes; adults with type 2 diabetes on insulin or at risk of hypoglycaemia; individuals with multiple islet autoantibodies in pre-symptomatic stage 1–2 type 1 diabetes; populations with limited access to diabetes technologies in low-resource settings
Abstract
Diabetes is one of the most prevalent chronic diseases worldwide, with rates that continue to increase. More than 30 years ago, the Diabetes Control and Complications Trial demonstrated that intensive glucose management decreased long-term vascular complications. Unfortunately, many people with diabetes still struggle to meet glycemic goals. In this mini-review, we highlight advances in diabetes technology that are associated with improvements in glycemic management. Continuous glucose monitoring (CGM) and automated insulin delivery systems are associated with significant improvements in glycated hemoglobin (HbA1c), time in range (70-180 mg/dL), and decreases in severe hypoglycemia and diabetic ketoacidosis in people with both type 1 and type 2 diabetes. Recent data show that these technologies improve outcomes early in the course of type 1 diabetes. CGM is also being explored as a tool to monitor progression through early-stage type 1 diabetes (2 antibodies positive) to identify individuals who may benefit from disease-modifying therapies as well as to prevent the onset of diabetic ketoacidosis at onset of stage 3 (insulin-requiring) type 1 diabetes. Adjunctive pharmacologic therapies and artificial intelligence may further expand and improve therapies, offering potential synergistic benefits. However, there continue to be significant disparities in access to diabetes technologies and access to insulin worldwide. This mini-review summarizes recently published data, highlights emerging applications, and underscores the need to pair technological innovation with strategies that promote equitable access and support for diabetes care to improve outcomes for all people with diabetes.
References
- 1.Prahalad, P., Zaharieva, D., & Maahs, D. M. (2026). Diabetes technology: an update. The Journal of Clinical Endocrinology and Metabolism. Advance online publication. https://doi.org/10.1210/clinem/dgag164
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