Evidence mapPaperPMID 37551339Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023

Racial Disparities in Diabetes Technology Adoption and Their Association with HbA1c and Diabetic Ketoacidosis.

Rebecca Baqiyyah Conway, Andrea Gerard Gonzalez, Viral N Shah, Cristy Geno Rasmussen, Halis Kaan Akturk, Laura Pyle, Gregory Forlenza, Guy Todd Alonso, Janet Snell-Bergeon

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.4field-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

15 citing papers in PubMed, 22 citations in OpenAlex.

  1. Trial
  2. Review
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  7. Article
  8. Racial Disparities in the Use of Automated Insulin Delivery Systems in Youth With Type 1 Diabetes.Diabetes spectrum : a publication of the American Diabetes Association · 2025
    Article
  9. Article
  10. Article
  11. Review
  12. Advances in diabetes technology within the digital diabetes ecosystem.Journal of managed care & specialty pharmacy · 2024
    Review
  13. Review
  14. Article
  15. 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

9 authors at 2 institutions in 1 country.

Rebecca Baqiyyah ConwayDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Andrea Gerard GonzalezSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.ORCID 0000-0001-9871-0294
Viral N ShahSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Cristy Geno RasmussenSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Halis Kaan AkturkSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Laura PyleSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Gregory ForlenzaSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.ORCID 0000-0003-3607-9788
Guy Todd AlonsoSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Janet Snell-BergeonSchool of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
University of Colorado Anschutz Medical Campus · USColorado School of Public Health · US

Funding

University of Colorado Anschutz Medical Campus DRCP30DK116073 · UNIVERSITY OF COLORADO DENVER · 2025 to 2025
$1.3M
NIDDK NIH HHS P30 DK116073
6 · The paper itself

Abstract

Aim: Poorer glycemic control and higher diabetic ketoacidosis (DKA) rates are seen in racial/ethnic minorities with type 1 diabetes (T1D). Use of diabetes technologies such as continuous glucose monitors (CGM), continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems has been shown to improve glycemic control and reduce DKA risk. We examined race/ethnicity differences in diabetes technology use and their relationship with HbA1c and DKA. Methods: Data from patients aged ≥12 years with T1D for ≥1 year, receiving care from a single diabetes center, were examined. Patients were classified as Non-Hispanic White (n=3945), Non-Hispanic Black (Black, n=161), Hispanic (n=719), and Multiracial/Other (n=714). General linear models and logistic regression were used. Results: Black (OR=0.22, 0.15-0.32) and Hispanic (OR=0.37, 0.30-0.45) patients were less likely to use diabetes technology. This disparity was greater in the pediatric population (p-interaction=0.06). Technology use associated with lower HbA1c in each race/ethnic group. Among technology users, AID use associated with lower HbA1c compared to CGM and/or CSII (HbA1c of 8.4% vs 9.2%, respectively), with the greatest difference observed for Black adult AID users. CSII use associated with a lower odds of DKA in the past year (OR=0.73, 0.54-0.99), a relationship that did not vary by race (p-interaction =0.69); this inverse association with DKA was not observed for CGM or AID. Conclusion: Disparities in diabetes technology use, DKA, and glycemic control were apparent among Black and Hispanic patients with T1D. Differences in technology use ameliorated but did not fully account for disparities in HbA1c or DKA.

Indexed as

automated insulin delivery systemscontinuous glucose monitoringcontinuous subcutaneous insulin infusiondiabetic ketoacidosisracial disparities

Identifiers

PMID37551339
PMCPMC10404403
OpenAlexW4385495772

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.