Evidence map›Paper›PMID 38721109›Full record

ArticleJournal of the Endocrine Society2024

Concordance of Blood Glucose and CGM During a Pilot Trial of Automated Insulin Delivery in Type 1 Diabetes Pregnancies.

Ravinder Jeet Kaur, Carol J Levy, Kristin Castorino, Christina M Wood-Wentz, Shafaq R Rizvi, Basak Ozaslan, Grenye O'Malley, Mari Charisse Trinidad, Camilla Levister, Mei Mei Church and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the Endocrine Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

18 authors.

Ravinder Jeet KaurMayo Clinic, Rochester, MN 55902, USA.
Carol J LevyDepartment of Endocrine, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Kristin CastorinoSansum Diabetes Research Institute, Santa Barbara, CA 93105, USA.
Christina M Wood-WentzMayo Clinic, Rochester, MN 55902, USA.
Shafaq R RizviMayo Clinic, Rochester, MN 55902, USA.
Basak OzaslanHarvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02134, USA.
Grenye O'MalleyDepartment of Endocrine, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Mari Charisse TrinidadMayo Clinic, Rochester, MN 55902, USA.
Camilla LevisterDepartment of Endocrine, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Mei Mei ChurchSansum Diabetes Research Institute, Santa Barbara, CA 93105, USA.
Donna DesjardinsMayo Clinic, Rochester, MN 55902, USA.
Selassie OgyaaduDepartment of Endocrine, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Corey ReidMayo Clinic, Rochester, MN 55902, USA.
Kent R BaileyMayo Clinic, Rochester, MN 55902, USA.
Francis J DoyleHarvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02134, USA.
Jordan E PinskerSansum Diabetes Research Institute, Santa Barbara, CA 93105, USA.
Eyal DassauSansum Diabetes Research Institute, Santa Barbara, CA 93105, USA.
Yogish C KudvaMayo Clinic, Rochester, MN 55902, USA.ORCID https://orcid.org/0000-0003-0285-6622

Funding

Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement - Dr. Timothy Curry)UL1TR002377 · NCATS · MAYO CLINIC ROCHESTER · PI VESNA D GAROVIC · 2017 to 2026
$78.4M
Automated Glucose Regulation to improve Diabetes Control and Outcomes for Pregnant Women with Type 1 Diabetes and FetusR01DK120358 · NIDDK · HARVARD UNIVERSITY · PI DASSAU, EYAL, KUDVA, YOGISH C. · 2018 to 2020
$2.3M
NCATS NIH HHS UL1 TR002377NIDDK NIH HHS R01 DK120358
6 · The paper itself

Abstract

Background: Customized and standard automated insulin delivery (AID) systems for use in pregnancies of women with preexisting type 1 diabetes (T1D) are being developed and tested to achieve pregnancy appropriate continuous glucose monitoring (CGM) targets. Guidance on the use of CGM for treatment decisions during pregnancy in the United States is limited. Methods: Ten pregnant women with preexisting T1D participated in a trial evaluating at-home use of a pregnancy-specific AID system. Seven-point self-monitoring of blood glucose (SMBG) was compared to the closest sensor glucose (Dexcom G6 CGM) value biweekly to assess safety and reliability based on the 20%/20 mg/dL criteria. Results: All participants completed the study with 7 participants satisfying the safety and reliability criteria with a mean absolute relative difference of 10.3%. Three participants did not fulfill the criteria, mainly because the frequency of SMBG did not meet the requirements. Conclusion: Dexcom G6 CGM is safe and accurate in the real-world setting for use in pregnant women with preexisting T1D with reduced SMBG testing as part of a pregnancy-specific AID system.

Indexed as

automated insulin deliverycontinuous glucose monitoringoutpatientpregnancyself-monitoring blood glucosetype 1 diabetes

Identifiers

PMID38721109
PMCPMC11077602

What OpenQuestion holds

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Registered trials

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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.