ArticleJournal of diabetes science and technology2011
Closed-loop insulin delivery utilizing pole placement to compensate for delays in subcutaneous insulin delivery.
Article in Journal of diabetes science and technology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02065895 (Effect of Gain on Closed-Loop Insulin), which is not on this map. Cited by 9 papers.
What it found
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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.
Effect of Gain on Closed-Loop Insulin
Who cites it
9 citing papers in PubMed.
- Effectiveness of early intensive therapy on β-cell preservation in type 1 diabetes.Diabetes care · 2013Trial
- The effects of inpatient hybrid closed-loop therapy initiated within 1 week of type 1 diabetes diagnosis.Diabetes technology & therapeutics · 2013Trial
- Closed-loop insulin therapy improves glycemic control in children aged <7 years: a randomized controlled trial.Diabetes care · 2013Trial
- Effect of insulin feedback on closed-loop glucose control: a crossover study.Journal of diabetes science and technology · 2012Trial
- A closed-loop microneedle-integrated physiological model for predictive glycemic management.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- The artificial pancreas: is it important to understand how the β cell controls blood glucose?Journal of diabetes science and technology · 2013Review
- Article
- Challenges and Recent Progress in the Development of a Closed-loop Artificial Pancreas.Annual reviews in control · 2012Article
- Use of a food and drug administration-approved type 1 diabetes mellitus simulator to evaluate and optimize a proportional-integral-derivative controller.Journal of diabetes science and technology · 2012Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundWe have previously used insulin feedback (IFB) as a component of a closed-loop algorithm emulating the β cell. This was based on the observation that insulin secretion is inhibited by insulin concentration. We show here that the effect of IFB is to make a closed-loop system behave as if delays in the insulin pharmacokinetic (PK)/pharmacodynamic (PD) response are reduced. We examine whether the mechanism can be used to compensate for delays in the subcutaneous PK/PD insulin response.
methodClosed-loop insulin delivery was performed in seven diabetic dogs using a proportional-integral-derivative model of the β cell modified by model-predicted IFB. The level of IFB was set using pole placement. Meal responses were obtained on three occasions: without IFB (NONE), reference IFB (REF), and 2xREF, with experiments performed in random order. The ability of the insulin model to predict insulin concentration was evaluated by correlation with the measured profile and results reported as R(2). The ability of IFB to improve the meal response was evaluated by comparing peak and nadir postprandial glucose and area under the curve (AUC; repeated measures analysis of variance with post hoc test for linear trend).
resultsInsulin concentration was well predicted by the model (median R(2) = 0.87, 0.79, and 0.90 for NONE, REF, and 2xREF, respectively). Peak postprandial glucose (294 ± 15, 243 ± 21, and 247 ± 16 mg/dl) and AUC (518.2 ± 36.13, 353.5 ± 45.04, and 280.3 ± 39.37 mg/dl · min) decreased with increasing IFB (p < .05, linear trend). Nadir glucose was not affected by IFB (76 ± 5.4, 68 ± 7.3, and 72 ± 4.3 mg/dl; p = .63).
conclusionsInsulin feedback provides an effective mechanism to compensate for delay in the insulin PK/PD profile.
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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.