Evidence map›Paper›PMID 23193210›Full record

Trial reportDiabetes care2013

Clinical evaluation of a personalized artificial pancreas.

Eyal Dassau, Howard Zisser, Rebecca A Harvey, Matthew W Percival, Benyamin Grosman, Wendy Bevier, Eran Atlas, Shahar Miller, Revital Nimri, Lois Jovanovic and 1 more

Open access · hybridAbstract readClinical Trial
In one paragraph

Trial report in Diabetes care, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
9.5field-weighted citation impact, top 1% 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

50 citing papers in PubMed, 119 citations in OpenAlex.

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  11. Artificial Pancreas: The First 20 Years.Journal of diabetes science and technology · 2025
    Article
  12. Early Stages of Automated Insulin Delivery.Journal of diabetes science and technology · 2025
    Review
  13. Review
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  15. Early Stages of Automated Insulin Delivery.Diabetes technology & therapeutics · 2025
    Review
  16. Review
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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

11 authors at 3 institutions in 2 countries.

Eyal DassauDepartment of Chemical Engineering, University of California, Santa Barbara, California, USA.
Howard Zisser
Rebecca A Harvey
Matthew W Percival
Benyamin Grosman
Wendy Bevier
Eran Atlas
Shahar Miller
Revital Nimri
Lois Jovanovic
Francis J Doyle
Sansum Diabetes Research Institute · USSchneider Children's Medical Center · ILUniversity of California, Santa Barbara · US

Funding

Closed-loop Artificial Pancreas: Algorithm Engineering and Clinical EvaluationR01DK085628 · NIDDK · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI DOYLE, FRANCIS J, JOVANOVIC, LOIS · 2009 to 2013
$3.4M
NIDDK NIH HHS DK-085628-01NIDDK NIH HHS R01 DK085628
6 · The paper itself

Abstract

objectiveAn artificial pancreas (AP) that automatically regulates blood glucose would greatly improve the lives of individuals with diabetes. Such a device would prevent hypo- and hyperglycemia along with associated long- and short-term complications as well as ease some of the day-to-day burden of frequent blood glucose measurements and insulin administration. RESEARCH DESIGN AND

methodsWe conducted a pilot clinical trial evaluating an individualized, fully automated AP using commercial devices. Two trials (n = 22, n(subjects) = 17) were conducted using a multiparametric formulation of model predictive control and an insulin-on-board algorithm such that the control algorithm, or "brain," can be embedded on a chip as part of a future mobile device. The protocol evaluated the control algorithm for three main challenges: 1) normalizing glycemia from various initial glucose levels, 2) maintaining euglycemia, and 3) overcoming an unannounced meal of 30 ± 5 g carbohydrates.

resultsInitial glucose values ranged from 84-251 mg/dL. Blood glucose was kept in the near-normal range (80-180 mg/dL) for an average of 70% of the trial time. The low and high blood glucose indices were 0.34 and 5.1, respectively.

conclusionsThese encouraging short-term results reveal the ability of a control algorithm tailored to an individual's glucose characteristics to successfully regulate glycemia, even when faced with unannounced meals or initial hyperglycemia. To our knowledge, this represents the first truly fully automated multiparametric model predictive control algorithm with insulin-on-board that does not rely on user intervention to regulate blood glucose in individuals with type 1 diabetes.

Indexed as

Pancreas, ArtificialAlgorithmsBlood GlucoseDiabetes Mellitus, Type 1HumansInsulin Infusion SystemsBlood Glucose

Identifiers

PMID23193210
PMCPMC3609541
OpenAlexW2154410696

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.