Evidence map›Paper›PMID 30922295›Full record

ReviewBiomedical engineering online2019

Combining continuous glucose monitoring and insulin pumps to automatically tune the basal insulin infusion in diabetes therapy: a review.

Martina Vettoretti, Andrea Facchinetti

Open access · goldAbstract readReview
In one paragraph

Review in Biomedical engineering online, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 5% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Case Studies in Continuous Glucose Monitoring.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2024
    Article
  8. Review
  9. Article
  10. Article
  11. [Research progress on minimally invasive and non-invasive blood glucose detection methods].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023
    Article
  12. Article
  13. Review
  14. Article
  15. Artificial intelligence perspective in the future of endocrine diseases.Journal of diabetes and metabolic disorders · 2022
    Review
  16. Article
  17. Article
  18. Article
  19. Glycemic Status Assessment by the Latest Glucose Monitoring Technologies.International journal of molecular sciences · 2020
    Review
  20. Review
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

2 authors at 1 institution in 1 country.

Martina VettorettiDepartment of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy.
Andrea FacchinettiDepartment of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy. facchine@dei.unipd.it.ORCID http://orcid.org/0000-0001-8041-2280
University of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For individuals affected by Type 1 diabetes (T1D), a chronic disease in which the pancreas does not produce any insulin, maintaining the blood glucose (BG) concentration as much as possible within the safety range (70-180 mg/dl) allows avoiding short- and long-term complications. The tuning of exogenous insulin infusion can be difficult, especially because of the inter- and intra-day variability of physiological and behavioral factors. Continuous glucose monitoring (CGM) sensors, which monitor glucose concentration in the subcutaneous tissue almost continuously, allowed improving the detection of critical hypo- and hyper-glycemic episodes. Moreover, their integration with insulin pumps for continuous subcutaneous insulin infusion allowed developing algorithms that automatically tune insulin dosing based on CGM measurements in order to mitigate the incidence of critical episodes. In this work, we aim at reviewing the literature on methods for CGM-based automatic attenuation or suspension of basal insulin with a focus on algorithms, their implementation in commercial devices and clinical evidence of their effectiveness and safety.

Indexed as

Insulin Infusion SystemsAdipose TissueAutomationDiabetes Mellitus, Type 1GlucoseHumansMonitoring, PhysiologicGlucoseGlucose predictionGlucose sensorsHypoglycemiaInsulin pumpKalman filterType 1 diabetes

Identifiers

PMID30922295
PMCPMC6440103
OpenAlexW2939880135

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.