ArticleJournal of diabetes science and technology2014
Novel insulin delivery profiles for mixed meals for sensor-augmented pump and closed-loop artificial pancreas therapy for type 1 diabetes mellitus.
Article in Journal of diabetes science and technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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Who cites it
7 citing papers in PubMed, 20 citations in OpenAlex.
- Randomized Crossover Comparison of Automated Insulin Delivery Versus Conventional Therapy Using an Unlocked Smartphone with Scheduled Pasta and Rice Meal Challenges in the Outpatient Setting.Diabetes technology & therapeutics · 2020Trial
- Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas.Diabetes care · 2016Trial
- Revolutionizing diabetes care: the role of artificial intelligence in prevention, diagnosis, and patient care.Journal of diabetes and metabolic disorders · 2025Review
- Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.Sensors (Basel, Switzerland) · 2020Review
- Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.Journal of medical Internet research · 2018Review
- Boluses in Insulin Therapy.Journal of diabetes science and technology · 2017Review
- An Adaptive Nonlinear Basal-Bolus Calculator for Patients With Type 1 Diabetes.Journal of diabetes science and technology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Maintaining euglycemia for people with type 1 diabetes is highly challenging, and variations in glucose absorption rates with meal composition require meal type specific insulin delivery profiles for optimal blood glucose control. Traditional basal/bolus therapy is not fully optimized for meals of varied fat contents. Thus, regimens for low- and high-fat meals were developed to improve current insulin pump therapy. Simulations of meals with varied fat content demonstrably replicated published data. Subsequently, an insulin profile library with optimized delivery regimens under open and closed loop for various meal compositions was constructed using particle swarm optimization. Calculations showed that the optimal basal bolus insulin profiles for low-fat meals comprise a normal bolus or a short wave. The preferred delivery for high-fat meals is typically biphasic, but can extend to multiple phases depending on meal characteristics. Results also revealed that patients that are highly sensitive to insulin could benefit from biphasic deliveries. Preliminary investigations of the optimal closed-loop regimens also display bi- or multiphasic patterns for high-fat meals. The novel insulin delivery profiles present new waveforms that provide better control of postprandial glucose excursions than existing schemes. Furthermore, the proposed novel regimens are also more or similarly robust to uncertainties in meal parameter estimates, with the closed-loop schemes demonstrating superior performance and robustness.
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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.