Adaptive bolus calculators for people with type 1 diabetes: A systematic review

Unsworth, Rebecca; Avari, Parizad; Lett, Aaron M.; Oliver, Nick; Reddy, Monika

doi:10.1111/dom.15204

Cited by 3 publications

(1 citation statement)

References 60 publications

(213 reference statements)

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“…23 Two prior systematic reviews on a small number of studies, one of which included a meta-analysis, failed to show an effect of (adaptive) bolus advisors on glycaemic control in people with type 1 diabetes. 24,25 Our study builds upon these previous reports by incorporating a broader range of glycaemic endpoints and more diverse populations, including patients on MDI therapy, and with type 2 diabetes. In addition, new evidence on bolus advisors has emerged since the publication of the meta-analysis.…”

Section: Introductionmentioning

confidence: 90%

The effect of bolus advisors on glycaemic parameters in adults with diabetes on intensive insulin therapy: A systematic review with meta‐analysis

den Brok,

Svensson,

Panagiotou

et al. 2024

Diabetes Obesity Metabolism

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AimTo conduct a systematic review with meta‐analysis to provide a comprehensive synthesis of randomized controlled trials (RCTs) and prospective cohort studies investigating the effects of currently available bolus advisors on glycaemic parameters in adults with diabetes.Materials and MethodsAn electronic search of PubMed, Embase, CINAHL, Cochrane Library and ClinicalTrials.gov was conducted in December 2022. The risk of bias was assessed using the revised Cochrane Risk of Bias tool. (Standardized) mean difference (MD) was selected to determine the difference in continuous outcomes between the groups. A random‐effects model meta‐analysis and meta‐regression were performed. This systematic review was registered on PROSPERO (CRD42022374588).ResultsA total of 18 RCTs involving 1645 adults (50% females) with a median glycated haemoglobin (HbA1c) concentration of 8.45% (7.95%–9.30%) were included. The majority of participants had type 1 diabetes (N = 1510, 92%) and were on multiple daily injections (N = 1173, 71%). Twelve of the 18 trials had low risk of bias. The meta‐analysis of 10 studies with available data on HbA1c showed that the use of a bolus advisor modestly reduced HbA1c compared to standard treatment (MD −011%, 95% confidence interval −0.22 to −0.01; I2 = 0%). This effect was accompanied by small improvements in low blood glucose index and treatment satisfaction, but not with reductions in hypoglycaemic events or changes in other secondary outcomes.ConclusionUse of a bolus advisor is associated with slightly better glucose control and treatment satisfaction in people with diabetes on intensive insulin treatment. Future studies should investigate whether personalizing bolus advisors using artificial intelligence technology can enhance these effects.

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Section: Introductionmentioning

confidence: 90%

The effect of bolus advisors on glycaemic parameters in adults with diabetes on intensive insulin therapy: A systematic review with meta‐analysis

den Brok,

Svensson,

Panagiotou

et al. 2024

Diabetes Obesity Metabolism

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Attention Networks for Personalized Mealtime Insulin Dosing in People with Type 1 Diabetes

Fathi,

Pryor,

Breton

2024

IFAC-PapersOnLine

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The role of real‐time continuous glucose monitoring in diabetes management and how it should link to integrated personalized diabetes management

Reddy,

Oliver

2024

Diabetes Obesity Metabolism

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Diabetes is a complex metabolic condition that demands tailored, individualized approaches for effective management. Real‐time continuous glucose monitoring (rtCGM) systems have improved in terms of design, usability and accuracy over the years and play a pivotal role in the delivery of integrated personalized diabetes management (iPDM). iPDM is a comprehensive multidisciplinary approach that combines individualized care strategies utilizing technologies and interventions and encourages the active involvement of the person with diabetes in the care provided. The use of stand‐alone rtCGM and its integration with other diabetes technologies, such as hybrid automated insulin delivery, have enabled improved glycaemic and quality of life outcomes for people with diabetes. As the uptake of rtCGM and associated technologies is increasing and becoming the standard of care for people with diabetes, it is important that efforts are focused on associated goals such as reducing health inequalities in terms of access, aligning structured education with rtCGM usage, choosing the right technology based on needs and preferences, and minimizing burden while aiming for optimal glucose outcomes. Utilizing rtCGM in other settings than outpatients and in diabetes cohorts beyond type 1 and type 2 diabetes needs further exploration. This review aims to provide an overview of the role of rtCGM and how best to link rtCGM to iPDM, highlighting its role in enhancing personalized treatment strategies.

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Adaptive bolus calculators for people with type 1 diabetes: A systematic review

Cited by 3 publications

References 60 publications

The effect of bolus advisors on glycaemic parameters in adults with diabetes on intensive insulin therapy: A systematic review with meta‐analysis

The effect of bolus advisors on glycaemic parameters in adults with diabetes on intensive insulin therapy: A systematic review with meta‐analysis

Attention Networks for Personalized Mealtime Insulin Dosing in People with Type 1 Diabetes

The role of real‐time continuous glucose monitoring in diabetes management and how it should link to integrated personalized diabetes management

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