Evidence map›Paper›PMID 30817171›Full record

ArticleDiabetes technology & therapeutics2019

Factory-Calibrated Continuous Glucose Monitoring: How and Why It Works, and the Dangers of Reuse Beyond Approved Duration of Wear.

Gregory P Forlenza, Taisa Kushner, Laurel H Messer, R Paul Wadwa, Sriram Sankaranarayanan

Abstract read
In one paragraph

Article in Diabetes technology & therapeutics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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.

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

25 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. A Passive Perspiration Inspired Wearable Platform for Continuous Glucose Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  13. Review
  14. Review
  15. Article
  16. Noninvasive Glucose Sensing In Vivo.Sensors (Basel, Switzerland) · 2023
    Review
  17. Article
  18. Review
  19. Article
  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

5 authors.

Gregory P Forlenza1 Department of Pediatric Endocrinology, Barbara Davis Center, University of Colorado Denver, Aurora, Colorado.
Taisa Kushner2 Department of Computer Science, University of Colorado, Boulder, Colorado.
Laurel H Messer1 Department of Pediatric Endocrinology, Barbara Davis Center, University of Colorado Denver, Aurora, Colorado.
R Paul Wadwa1 Department of Pediatric Endocrinology, Barbara Davis Center, University of Colorado Denver, Aurora, Colorado.
Sriram Sankaranarayanan2 Department of Computer Science, University of Colorado, Boulder, Colorado.

Funding

K12 Career DevelopmentK12DK094712 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI STECK, ANDREA · 2011 to 2021
$4.5M
NIDDK NIH HHS K12 DK094712
6 · The paper itself

Abstract

Continuous glucose monitors (CGM) display real-time glucose values enabling greater glycemic awareness with reduced management burden. Factory-calibrated CGM systems allow for glycemic assessment without the pain and inconvenience of fingerstick glucose testing. Advances in sensor chemistry and CGM algorithms have enabled factory-calibrated systems to have greater accuracy than previous generations of CGM technology. Despite these advances many patients and providers are hesitant about the idea of removing fingerstick testing from their diabetes care. In this commentary, we aim to review the clinical trials on factory-calibrated CGM systems, present the algorithms which facilitate factory-calibrated CGMs to improve accuracy, discuss clinical use of factory-calibrated CGMs, and finally present two cases demonstrating the dangers of utilizing exploits in commercial systems to prolong sensor life.

Indexed as

Blood Glucose Self-MonitoringBlood GlucoseCalibrationDiabetes Mellitus, Type 1HumansBlood GlucoseContinuous glucose monitoringFactory calibrationType 1 diabetes

Identifiers

PMID30817171
PMCPMC6477582

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.