Evidence map›Paper›PMID 31561714›Full record

ArticleJournal of diabetes science and technology2019

Controlling the AP Controller: Controller Performance Assessment and Modification.

Iman Hajizadeh, Nicole Hobbs, Sediqeh Samadi, Mert Sevil, Mudassir Rashid, Rachel Brandt, Mohammad Reza Askari, Zacharie Maloney, Ali Cinar

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes science and technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 1 institution in 1 country.

Iman HajizadehDepartment of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Nicole HobbsDepartment of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Sediqeh SamadiDepartment of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Mert SevilDepartment of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Mudassir RashidDepartment of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Rachel BrandtDepartment of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Mohammad Reza AskariDepartment of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Zacharie MaloneyDepartment of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Ali CinarDepartment of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.ORCID 0000-0002-1607-9943
Illinois Institute of Technology · US

Funding

Control Systems for Artificial Pancreas Use During and After ExerciseDP3DK101075 · NIDDK · ILLINOIS INSTITUTE OF TECHNOLOGY · PI CINAR, ALI · 2013 to 2013
$2.5M
Fault-tolerant Control Systems for Artificial PancreasDP3DK101077 · NIDDK · ILLINOIS INSTITUTE OF TECHNOLOGY · PI CINAR, ALI · 2013 to 2013
$2.0M
NIDDK NIH HHS DP3 DK101075NIDDK NIH HHS DP3 DK101077
6 · The paper itself

Abstract

backgroundDespite recent advances in closed-loop control of blood glucose concentration (BGC) in people with type 1 diabetes (T1D), online performance assessment and modification of artificial pancreas (AP) control systems remain a challenge as the metabolic characteristics of users change over time.

methodsA controller performance assessment and modification system (CPAMS) analyzes the glucose concentration variations and controller behavior, and modifies the parameters of the control system used in the multivariable AP system. Various indices are defined to quantitatively evaluate the controller performance in real time. Controller performance assessment and modification system also incorporates online learning from historical data to anticipate impending disturbances and proactively counteract their effects.

resultsUsing a multivariable simulation platform for T1D, the CPAMS is used to enhance the BGC regulation in people with T1D by means of automated insulin delivery with an adaptive learning predictive controller. Controller performance assessment and modification system increases the percentage of time in the target range (70-180) mg/dL by 52.3% without causing any hypoglycemia and hyperglycemia events.

conclusionsThe results demonstrate a significant improvement in the multivariable AP controller performance by using CPAMS.

Indexed as

Pancreas, ArtificialAlgorithmsBlood GlucoseDiabetes Mellitus, Type 1HumansHypoglycemic AgentsInsulinInsulin Infusion SystemsBlood GlucoseHypoglycemic AgentsInsulinartificial pancreasbiomedical systemcontroller performance assessment and modification

Identifiers

PMID31561714
PMCPMC6835190
OpenAlexW2976127560

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.