ArticleJournal of process control2008
A Run-to-Run Control Strategy to Adjust Basal Insulin Infusion Rates in Type 1 Diabetes.
Article in Journal of process control, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01484457 (Controlled Insulin Delivery), which is not on this map. Cited by 35 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Controlled Insulin Delivery: Combining Technology With Treatment
Who cites it
35 citing papers in PubMed.
- Toward Personalized Decision Support Systems for Type 1 Diabetes: Integrating Psychobehavioral Factors and Glycemic Control.Journal of diabetes science and technology · 2025Trial
- Trial
- Analyzing the Potential of Advanced Insulin Dosing Strategies in Patients With Type 2 Diabetes: Results From a Hybrid In Silico Study.Journal of diabetes science and technology · 2018Trial
- Continuous Glucose Monitoring and Insulin Informed Advisory System with Automated Titration and Dosing of Insulin Reduces Glucose Variability in Type 1 Diabetes Mellitus.Diabetes technology & therapeutics · 2018Trial
- Twelve-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin ADiabetes care · 2017Trial
- Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia.Diabetes · 2012Trial
- Design andJournal of diabetes science and technology · 2024Article
- Multi-Timescale Rhythmicity of Blood Glucose and Insulin Delivery Reveals Key Advantages of Hybrid Closed Loop Therapy.Journal of diabetes science and technology · 2022Article
- Extended Kalman filter state estimation-based nonlinear explicit model predictive control design for blood glucose regulation of type 1 diabetic patient.Medical & biological engineering & computing · 2022Article
- Dynamic Insulin Basal Needs Estimation and Parameters Adjustment in Type 1 Diabetes.Sensors (Basel, Switzerland) · 2021Article
- Titration of Long-Acting Insulin Using Continuous Glucose Monitoring and Smart Insulin Pens in Type 1 Diabetes: A Model-Based Carbohydrate-Free Approach.Frontiers in endocrinology · 2021Article
- Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.Sensors (Basel, Switzerland) · 2020Review
- Application of Artificial Intelligence Techniques for the Estimation of Basal Insulin in Patients with Type I Diabetes.International journal of endocrinology · 2020Article
- Continuous Glucose Monitors and Activity Trackers to Inform Insulin Dosing in Type 1 Diabetes: The University of Virginia Contribution.Sensors (Basel, Switzerland) · 2019Article
- Controlling the AP Controller: Controller Performance Assessment and Modification.Journal of diabetes science and technology · 2019Article
- Adaptive Zone Model Predictive Control of Artificial Pancreas Based on Glucose- and Velocity-Dependent Control Penalties.IEEE transactions on bio-medical engineering · 2019Article
- Optimal regulation of blood glucose level in Type I diabetes using insulin and glucagon.PloS one · 2019Article
- Multivariate learning framework for long-term adaptation in the artificial pancreas.Bioengineering & translational medicine · 2019Article
- Extremum Seeking Control for Personalized Zone Adaptation in Model Predictive Control for Type 1 Diabetes.IEEE transactions on bio-medical engineering · 2018Article
- Automatic Adaptation of Basal Insulin Using Sensor-Augmented Pump Therapy.Journal of diabetes science and technology · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Maintaining good glycemic control is a daily challenge for people with type 1 diabetes. Insulin requirements are changing constantly due to many factors, such as levels of stress and physical activity. The basal insulin requirement also has a circadian rhythm, adding another level of complexity. Automating the adjustment of insulin dosing would result in improved glycemic control, as well as an improved quality of life by significantly reducing the burden on the patient. Building on our previous success of using run-to-run control for prandial insulin dosing (a strategy adapted from the chemical process industry), we show how this same framework can be used to adjust basal infusion profiles. We present a mathematical model of insulin-glucose dynamics which we augment in order to capture the circadian variation in insulin requirements. Using this model, we show that the run-to-run framework can also be successfully applied to adjust basal insulin dosing.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.