Evidence mapPaperPMID 36424765Full record

ArticleJournal of diabetes science and technology2024

Adjusting Therapy Profiles When Switching to Ultra-Rapid Lispro in an Advanced Hybrid Closed-Loop System: An in Silico Study.

Patricio Colmegna, Jenny L Diaz C, Jose Garcia-Tirado, Mark D DeBoer, Marc D Breton

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Article in Journal of diabetes science and technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. The Future of Automated Insulin Delivery Systems.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Patricio ColmegnaCenter for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.ORCID 0000-0001-9074-8634
Jenny L Diaz CCenter for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
Jose Garcia-TiradoCenter for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.ORCID 0000-0002-9970-2162
Mark D DeBoerCenter for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.ORCID 0000-0001-7645-2693
Marc D BretonCenter for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.

Funding

Advanced Artificial Pancreas Systems to Enable Fully Automated Glycemic Control in Type 1 Diabetes MellitusR01DK129553 · UNIVERSITY OF VIRGINIA · 2025 to 2025
$441k
NIDDK NIH HHS R01 DK129553
6 · The paper itself

Abstract

backgroundIt has been shown that insulin acceleration by itself might not be sufficient to see clear improvements in glycemic metrics, and insulin therapy may need to be adjusted to fully leverage the extra safety margin provided by faster pharmacokinetic (PK) and pharmacodynamic (PD) profiles. The objective of this work is to explore how to perform such adjustments on a commercially available automated insulin delivery (AID) system.

methodsUltra-rapid lispro (URLi) is modeled within the UVA/Padova simulation platform using data from previously published clamp studies. The Control-IQ AID algorithm is selected as it leverages carbohydrate-to-insulin ratio (CR in g/U), correction factor (CF in mg/dL/U), and basal rate (BR in U/h) daily profiles that are fully customizable. An experiment roadmap is proposed to understand how to safely modify these profiles when switching from lispro to URLi.

resultsSimulations show that a 7% decrease in CR (approximately an 8% increase in prandial insulin) and a 7.5% increase in BR lead to cumulative improvements in glucose control with URLi. Comparing with baseline metrics using lispro, a clinically significant increase in time in the range of 70 to 180 mg/dL (overall: 70.2%-75.2%,

conclusionProperly adjusting therapy parameters allows to fully leverage glucose control benefits provided by faster insulin analogues, opening opportunities to take another step forward into a next generation of more effective AID solutions.

Indexed as

Blood GlucoseComputer SimulationHypoglycemic AgentsInsulin Infusion SystemsInsulin LisproAlgorithmsDiabetes Mellitus, Type 1HumansInsulinBlood GlucoseHypoglycemic AgentsInsulinInsulin Lisproautomated insulin deliveryglucose controlinsulin therapy parameterstype 1 diabetesultra-rapid insulin analogues

Identifiers

PMID36424765
PMCPMC11089876

What Socratic holds

Textmetadata
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Registered trials

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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 Socratic graph.