Evidence map›Paper›PMID 32546001›Full record

ArticleJournal of diabetes science and technology2021

Impact of Accelerating Insulin on an Artificial Pancreas System Without Meal Announcement: An In Silico Examination.

Patricio Colmegna, Eda Cengiz, Jose Garcia-Tirado, Kristen Kraemer, Marc D Breton

Open access · bronzeAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2021. 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
1.3field-weighted citation impact, top 19% of its field
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, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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 at 4 institutions in 3 countries.

Patricio ColmegnaCenter for Diabetes Technology, University of Virginia, Charlottesville, USA.ORCID 0000-0001-9074-8634
Eda CengizDivision of Pediatric Endocrinology and Diabetes, Yale University School of Medicine, New Haven, CT, USA.
Jose Garcia-TiradoCenter for Diabetes Technology, University of Virginia, Charlottesville, USA.ORCID 0000-0002-9970-2162
Kristen KraemerDivision of Pediatric Endocrinology and Diabetes, Yale University School of Medicine, New Haven, CT, USA.
Marc D BretonCenter for Diabetes Technology, University of Virginia, Charlottesville, USA.
University of Virginia · USBahçeşehir University · TRConsejo Nacional de Investigaciones Científicas y Técnicas · ARYale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
YALE UNIVERSITY CLINICAL AND TRANSLATIONAL SCIENCE AWARD PROGRAMUL1RR024139 · NCRR · YALE UNIVERSITY · PI SHERWIN, ROBERT S · 2006 to 2011
$56.8M
Yale Diabetes Research CenterP30DK045735 · NIDDK · YALE UNIVERSITY · PI Kevan C Herold, GERALD I SHULMAN · 1993 to 2026
$44.0M
Models, signals, and distributed bio-behavioral control of exercise in diabetesDP3DK106826 · NIDDK · UNIVERSITY OF VIRGINIA · PI BRETON, MARC D · 2015 to 2015
$3.0M
NCATS NIH HHS UL1 TR001863NCRR NIH HHS UL1 RR024139NIDDK NIH HHS DP3 DK106826NIDDK NIH HHS P30 DK045735
6 · The paper itself

Abstract

backgroundControlling postprandial blood glucose without the benefit of an appropriately sized premeal insulin bolus has been challenging given the delays in absorption and action of subcutaneously injected insulin during conventional and artificial pancreas (AP) system diabetes treatment. We aim to understand the impact of accelerating insulin and increasing aggressiveness of the AP controller as potential solutions to address the postprandial hyperglycemia challenge posed by unannounced meals through a simulation study.

methodsAccelerated rapid-acting insulin analogue is modeled within the UVA/Padova simulation platform by uniformly reducing its pharmacokinetic time constants (α multiplier) and used with a model predictive control, where the controller's aggressiveness depends on α. Two sets of single-meal simulations were performed: (1) where we only tune the controller's aggressiveness and (2) where we also accelerate insulin absorption and action to assess postprandial glycemic control during each intervention.

resultsMean percent of time spent within the 70 to 180 mg/dL postprandial glycemic range is significantly higher in set (2) than in set (1): 79.9, 95% confidence interval [77.0, 82.7] vs 88.8 [86.8, 90.9] ([Note to typesetter: Set all unnecessary math in text format and insert appropriate spaces between operators.]

conclusionThese proof-of-concept simulations suggest that an AP without prandial insulin boluses combined with significantly faster insulin analogues could match the glycemic performance obtained with an optimal hybrid AP.

Indexed as

Diabetes Mellitus, Type 1Pancreas, ArtificialAlgorithmsBlood GlucoseComputer SimulationHumansHypoglycemic AgentsInsulinMealsPostprandial PeriodBlood GlucoseHypoglycemic AgentsInsulinartificial pancreasfast-acting insulin analoguesmodel predictive controltype 1 diabetesunannounced meals

Identifiers

PMID32546001
PMCPMC8258534
OpenAlexW3035154822

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.