Evidence map›Paper›PMID 33931977›Full record

ArticleClinical and translational medicine2021

Full closed loop open-source algorithm performance comparison in pigs with diabetes.

Rayhan A Lal, Caitlin L Maikawa, Dana Lewis, Sam W Baker, Anton A A Smith, Gillie A Roth, Emily C Gale, Lyndsay M Stapleton, Joseph L Mann, Anthony C Yu and 9 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical and translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. A Systematic Review of Commercial Hybrid Closed-Loop Automated Insulin Delivery Systems.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2023 · on this map
    Review
  9. Article
  10. Article
  11. Review
  12. Automated insulin dosing systems: Advances after a century of insulin.Diabetic medicine : a journal of the British Diabetic Association · 2021
    Review
  13. Article
  14. 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

19 authors.

Rayhan A LalDivision of Endocrinology, Department of Medicine, Stanford University, Stanford, California, USA.
Caitlin L MaikawaDepartment of Bioengineering, Stanford University, Stanford, California, USA.
Dana LewisOpenAPS, Seattle, Washington, USA.
Sam W BakerDepartment of Comparative Medicine, Stanford University, Stanford, California, USA.
Anton A A SmithDepartment of Materials Science & Engineering, Stanford University, Stanford, California, USA.
Gillie A RothDepartment of Bioengineering, Stanford University, Stanford, California, USA.
Emily C GaleDepartment of Biochemistry, Stanford University, Stanford, California, USA.
Lyndsay M StapletonDepartment of Bioengineering, Stanford University, Stanford, California, USA.
Joseph L MannDepartment of Materials Science & Engineering, Stanford University, Stanford, California, USA.
Anthony C YuDepartment of Materials Science & Engineering, Stanford University, Stanford, California, USA.
Santiago CorreaDepartment of Materials Science & Engineering, Stanford University, Stanford, California, USA.
Abigail K GrosskopfDepartment of Chemical Engineering, Stanford University, Stanford, California, USA.
Celine S LiongDepartment of Bioengineering, Stanford University, Stanford, California, USA.
Catherine M MeisDepartment of Materials Science & Engineering, Stanford University, Stanford, California, USA.
Doreen ChanDepartment of Chemistry, Stanford University, Stanford, California, USA.ORCID 0000-0001-9301-6789
Joseph P GarnerDepartment of Comparative Medicine, Stanford University, Stanford, California, USA.
David M MaahsDivision of Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA.
Bruce A BuckinghamDivision of Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA.
Eric A AppelDivision of Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA.ORCID 0000-0002-2301-7126

Funding

Stanford Islet Research CoreP30DK116074 · NIDDK · STANFORD UNIVERSITY · PI FREDRIC B. KRAEMER · 2017 to 2026
$19.5M
Network Control of Diabetes: Aligning Artificial Pancreas Design with PhysiologyDP3DK101055 · NIDDK · UNIVERSITY OF VIRGINIA · PI KOVATCHEV, BORIS P · 2013 to 2013
$3.4M
Co-Formulations of Amylin Analogues with Insulin Analogues for Treatment of DiabetesR01DK119254 · NIDDK · STANFORD UNIVERSITY · PI APPEL, ERIC ANDREW · 2019 to 2023
$2.9M
Using a Closed-Loop System Plus Behavioral Supports in Preschoolers with DiabetesDP3DK104059 · NIDDK · STANFORD UNIVERSITY · PI BUCKINGHAM, BRUCE A, DIMEGLIO, LINDA A · 2014 to 2014
$2.1M
Training Research Leaders in Type 1 DiabetesK12DK122550 · NIDDK · STANFORD UNIVERSITY · PI MAAHS, DAVID MATTHEW · 2019 to 2023
$2.1M
The Optimal Pathway to Implanted Autonomous Insulin DeliveryK23DK122017 · NIDDK · STANFORD UNIVERSITY · PI LAL, RAYHAN · 2020 to 2024
$958k
NIDDK NIH HHS DP3 DK101055NIDDK NIH HHS DP3 DK104059NIDDK NIH HHS K12 DK122550NIDDK NIH HHS K23 DK122017NIDDK NIH HHS P30 DK116074NIDDK NIH HHS R01 DK119254
6 · The paper itself

Abstract

Understanding how automated insulin delivery (AID) algorithm features impact glucose control under full closed loop delivery represents a critical step toward reducing patient burden by eliminating the need for carbohydrate entries at mealtimes. Here, we use a pig model of diabetes to compare AndroidAPS and Loop open-source AID systems without meal announcements. Overall time-in-range (70-180 mg/dl) for AndroidAPS was 58% ± 5%, while time-in-range for Loop was 35% ± 5%. The effect of the algorithms on time-in-range differed between meals and overnight. During the overnight monitoring period, pigs had an average time-in-range of 90% ± 7% when on AndroidAPS compared to 22% ± 8% on Loop. Time-in-hypoglycemia also differed significantly during the lunch meal, whereby pigs running AndroidAPS spent an average of 1.4% (+0.4/-0.8)% in hypoglycemia compared to 10% (+3/-6)% for those using Loop. As algorithm design for closed loop systems continues to develop, the strategies employed in the OpenAPS algorithm (known as oref1) as implemented in AndroidAPS for unannounced meals may result in a better overall control for full closed loop systems.

Indexed as

Insulin Infusion SystemsAlgorithmsAnimalsBlood GlucoseDiabetes Mellitus, ExperimentalDisease Models, AnimalFemaleGlycemic ControlInsulinSwineBlood GlucoseInsulinautomated insulin deliverydiabetesopen-source closed loop

Identifiers

PMID33931977
PMCPMC8087942

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.