ArticleJournal of diabetes science and technology2012
Use of a food and drug administration-approved type 1 diabetes mellitus simulator to evaluate and optimize a proportional-integral-derivative controller.
Article in Journal of diabetes science and technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Algorithms for a closed-loop artificial pancreas: the case for proportional-integral-derivative control.Journal of diabetes science and technology · 2013Pooled it
- Recent advances in the precision control strategy of artificial pancreas.Medical & biological engineering & computing · 2024Review
- The artificial pancreas: evaluating risk of hypoglycaemia following errors that can be expected with prolonged at-home use.Diabetic medicine : a journal of the British Diabetic Association · 2016Article
- Design and Evaluation of a Robust PID Controller for a Fully Implantable Artificial Pancreas.Industrial & engineering chemistry research · 2015Article
- The mathematician's control toolbox for management of type 1 diabetes.Interface focus · 2014Review
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClinical studies have shown that the Medtronic proportional-integral-derivative (PID) control with insulin feedback (IFB) provides stable 24 h glucose control, but with high postprandial glucose. We coupled this algorithm to a Food and Drug Administration-approved type 1 diabetes mellitus simulator to determine whether a proportional-derivative controller with preprogrammed basal rates (PDBASAL) would have better performance.
methodsWe performed simulation studies on 10 adult subjects to (1) obtain the basal profiles for the PDBASAL controller; (2) define the pharmacokinetic/pharmacodynamic profile used to effect IFB, (3) optimize the PID and PDBASAL control parameters, (4) evaluate improvements obtained with IFB, and (5) develop a method to simulate changes in insulin sensitivity and assess the ability of each algorithm to respond to such changes.
resultsPDBASAL control significantly reduced peak postprandial glucose [252 (standard error = 11) versus 279 (14) mg/dl; p < .001] and increased nadir glucose [102 (3) versus 92 (3) mg/dl; p < .001] compared with PID control (both implemented with IFB). However, with PDBASAL control, fasting glucose remained elevated following a 30% decrease in insulin sensitivity [156 (6) mg/dl; different from the target of 110 mg/dl; p < .001] and remained below target following a 30% increase in insulin sensitivity [84 (2) mg/dl; p < .001]. In both cases, PID control returned glucose levels to target.
conclusionsPDBASAL provides better postprandial glucose control than PID but is not appropriate for subjects whose basal requirements change with insulin sensitivity. Simulations used to compare different control strategies should assess this variability.
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Registered trials
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