ArticleDiabetes technology & therapeutics2018
Insulin Sensitivity Index-Based Optimization of Insulin to Carbohydrate Ratio: In Silico Study Shows Efficacious Protection Against Hypoglycemic Events Caused by Suboptimal Therapy.
Article in Diabetes technology & therapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Quantitative estimation of disposition index from postprandial glucose data across the spectrum of glucose tolerance.American journal of physiology. Endocrinology and metabolism · 2025Article
- The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP.Scientific reports · 2023Article
- Mathematical Models of Meal Amount and Timing Variability With Implementation in the Type-1 Diabetes Patient Decision Simulator.Journal of diabetes science and technology · 2021Article
- Individualizing Time-in-Range Goals in Management of Diabetes Mellitus and Role of Insulin: Clinical Insights From a Multinational Panel.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2021Review
- Carbohydrate Requirement for Exercise in Type 1 Diabetes: Effects of Insulin Concentration.Journal of diabetes science and technology · 2020Article
- Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes-An In Silico Proof-of-Concept.Sensors (Basel, Switzerland) · 2019Article
- Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications.Journal of diabetes science and technology · 2018Article
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3 authors.
Funding
Abstract
BACKGROUND AND
aimThe insulin to carbohydrate ratio (CR) is a parameter used by patients with type 1 diabetes (T1D) to calculate the premeal insulin bolus. Usually, it is estimated by the physician based on patient diary, but modern diabetes technologies, such as subcutaneous glucose sensing (continuous glucose monitoring, CGM) and insulin delivery (continuous subcutaneous insulin infusion, CSII) systems, can provide important information for its optimization. In this study, a method for CR optimization based on CGM and CSII data is presented and its efficacy and robustness tested in several in silico scenarios, with the primary aim of increasing protection against hypoglycemia.
methodsThe method is based on a validated index of insulin sensitivity calculated from sensor and pump data (S
resultsThe optimized CR was efficacious in protecting against hypoglycemic events caused by suboptimal therapy. The method was also robust to possible error in carbohydrate count and suboptimal basal insulin infusion.
conclusionsA novel method for CR optimization in T1D, implementable in daily life using CGM and CSII data, is proposed. The method can be used both in open- and closed-loop insulin therapy.
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