Evidence map›Paper›PMID 30188192›Full record

ArticleDiabetes technology & therapeutics2018

Multivariable Artificial Pancreas for Various Exercise Types and Intensities.

Kamuran Turksoy, Iman Hajizadeh, Nicole Hobbs, Jennifer Kilkus, Elizabeth Littlejohn, Sediqeh Samadi, Jianyuan Feng, Mert Sevil, Caterina Lazaro, Julia Ritthaler and 4 more

Registry-linked trialAbstract read
In one paragraph

Article in Diabetes technology & therapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05145374 (Multivariable Artificial Pancreas to Detect and Mitigate the Effects of Unannounced Physical Activities and Acute Psychological Stress), which is not on this map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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.

NCT05145374 recruitingnot on this mapstarted 2022, after this paper: background citation

Multivariable Artificial Pancreas to Detect and Mitigate the Effects of Unannounced Physical Activities and Acute Psychological Stress

TypeobservationalSponsorUniversity of Illinois at ChicagoRan2022 to 2025Enrolled20ConditionsType 1 Diabetes
3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Trial
  2. Metabolic Models, in Silico Trials, and Algorithms.Diabetes technology & therapeutics · 2025
    Review
  3. Metabolic Models, in Silico Trials, and Algorithms.Journal of diabetes science and technology · 2025
    Review
  4. Dosing Algorithms for Insulin Pumps.Diabetes spectrum : a publication of the American Diabetes Association · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Recent advances in the precision control strategy of artificial pancreas.Medical & biological engineering & computing · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Review
  20. 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

14 authors.

Kamuran Turksoy1 Department of Biomedical Engineering and Illinois Institute of Technology , Chicago, Illinois.
Iman Hajizadeh2 Department of Chemical and Biological Engineering, Illinois Institute of Technology , Chicago, Illinois.
Nicole Hobbs1 Department of Biomedical Engineering and Illinois Institute of Technology , Chicago, Illinois.
Jennifer Kilkus3 Section of Endocrinology, Department of Pediatrics and Medicine, Kovler Diabetes Center, University of Chicago , Chicago, Illinois.
Elizabeth Littlejohn3 Section of Endocrinology, Department of Pediatrics and Medicine, Kovler Diabetes Center, University of Chicago , Chicago, Illinois.
Sediqeh Samadi2 Department of Chemical and Biological Engineering, Illinois Institute of Technology , Chicago, Illinois.
Jianyuan Feng2 Department of Chemical and Biological Engineering, Illinois Institute of Technology , Chicago, Illinois.
Mert Sevil1 Department of Biomedical Engineering and Illinois Institute of Technology , Chicago, Illinois.
Caterina Lazaro5 Department of Electrical and Computer Engineering, Illinois Institute of Technology , Chicago, Illinois.
Julia Ritthaler6 Division of Biological Sciences, University of Chicago , Chicago, Illinois.
Brooks Hibner6 Division of Biological Sciences, University of Chicago , Chicago, Illinois.
Nancy Devine3 Section of Endocrinology, Department of Pediatrics and Medicine, Kovler Diabetes Center, University of Chicago , Chicago, Illinois.
Laurie Quinn7 College of Nursing, University of Illinois at Chicago , Chicago, Illinois.
Ali Cinar1 Department of Biomedical Engineering and Illinois Institute of Technology , Chicago, Illinois.

Funding

Research Design, Data, and Analytics CoreP30DK092949 · NIDDK · UNIVERSITY OF CHICAGO · PI MILDA Renne SAUNDERS · 2011 to 2026
$10.0M
NIDDK NIH HHS P30 DK092949
6 · The paper itself

Abstract

backgroundExercise challenges people with type 1 diabetes in controlling their glucose concentration (GC). A multivariable adaptive artificial pancreas (MAAP) may lessen the burden.

methodsThe MAAP operates without any user input and computes insulin based on continuous glucose monitor and physical activity signals. To analyze performance, 18 60-h closed-loop experiments with 96 exercise sessions with three different protocols were completed. Each day, the subjects completed one resistance and one treadmill exercise (moderate continuous training [MCT] or high-intensity interval training [HIIT]). The primary outcome is time spent in each glycemic range during the exercise + recovery period. Secondary measures include average GC and average change in GC during each exercise modality.

resultsThe GC during exercise + recovery periods were within the euglycemic range (70-180 mg/dL) for 69.9% of the time and within a safe glycemic range for exercise (70-250 mg/dL) for 93.0% of the time. The exercise sessions are defined to begin 30 min before the start of exercise and end 2 h after start of exercise. The GC were within the severe hypoglycemia (<55 mg/dL), moderate hypoglycemia (55-70 mg/dL), moderate hyperglycemia (180-250 mg/dL), and severe hyperglycemia (>250 mg/dL) for 0.9%, 1.3%, 23.1%, and 4.8% of the time, respectively. The average GC decline during exercise differed with exercise type (P = 0.0097) with a significant difference between the MCT and resistance (P = 0.0075). To prevent large GC decreases leading to hypoglycemia, MAAP recommended carbohydrates in 59% of MCT, 50% of HIIT, and 39% of resistance sessions.

conclusionsA consistent GC decline occurred in exercise and recovery periods, which differed with exercise type. The average GC at the start of exercise was above target (185.5 ± 56.6 mg/dL for MCT, 166.9 ± 61.9 mg/dL for resistance training, and 171.7 ± 41.4 mg/dL HIIT), making a small decrease desirable. Hypoglycemic events occurred in 14.6% of exercise sessions and represented only 2.22% of the exercise and recovery period.

Indexed as

Pancreas, ArtificialAdultBlood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 1ExerciseFemaleHumansHypoglycemiaHypoglycemic AgentsInfusion PumpsInsulinMaleResistance TrainingTreatment OutcomeYoung AdultBlood GlucoseHypoglycemic AgentsInsulinArtificial pancreasExerciseType 1 diabetes.

Identifiers

PMID30188192
PMCPMC6161329

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Registered trials

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.