Evidence map›Paper›PMID 37264642›Full record

Observational studyJournal of diabetes science and technology2025

An Observational Crossover Study of People Using Real-Time Continuous Glucose Monitors Versus Self-Monitoring of Blood Glucose: Real-World Evidence Using Electronic Medical Record Data From More Than 12,000 People With Type 1 Diabetes.

Nudrat Noor, Gregory Norman, Rona Sonabend, Lily Chao, Manmohan Kamboj, Lauren Golden, M Tracy Bekx, Susan Hseih, Carol Levy, Janine Sanchez and 2 more

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in Journal of diabetes science and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. 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

12 authors at 10 institutions in 1 country.

Nudrat NoorT1D Exchange, Boston, MA, USA.ORCID 0000-0003-0400-7835
Gregory NormanDexcom, San Diego, CA, USA.ORCID 0000-0001-7989-9597
Rona SonabendTexas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.
Lily ChaoChildren's Hospital of Los Angeles, Los Angeles, CA, USA.
Manmohan KambojNationwide Children's Hospital, Columbia, OH, USA.
Lauren GoldenNYU Langone Health, New York City, NY, USA.
M Tracy BekxUW Health, University of Wisconsin, Madison, WI, USA.
Susan HseihCook Children's Hospital, Fort Worth, TX, USA.
Carol LevyIcahn School of Medicine, New York City, NY, USA.ORCID 0000-0002-3492-2578
Janine SanchezMiller School of Medicine, University of Miami, Miami, FL, USA.
Robert RapaportIcahn School of Medicine, New York City, NY, USA.
Osagie EbekozienT1D Exchange, Boston, MA, USA.ORCID 0000-0002-8473-249X
Icahn School of Medicine at Mount Sinai · USBaylor College of Medicine · USChildren's Hospital of Los Angeles · USCook Children's Medical Center · USDexcom (United States) · USNationwide Children's Hospital · UST1D Exchange · USUniversity of Miami · USUniversity of Mississippi · USUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe used real-world electronic health record (EHR) data to examine HbA1c levels among children and adults with type 1 diabetes (T1D) who are classified as continuous glucose monitor (CGM) users after T1D diagnosis and switch to self-monitoring of blood glucose (SMBG) during follow-up, versus people who opt for SMBG after T1D diagnosis and switch to CGM during follow-up visits.

methodsWe conducted an observational, case-crossover study using electronic medical record (EMR) data from the T1D Exchange Quality Improvement Collaborative. The primary outcome in this study was HbA1c. Baseline HbA1c levels were taken at the index date, corresponding to initial device classification, and compared with HbA1c value recorded at the clinic visit following device switch.

resultsOf all patients classified in the SMBG group, 7,706 switched to CGM use within the 5-year study time frame, and 5,123 of all initial CGM users switched to SMBG within the study time frame and were included in this analysis. At baseline, median (interquartile range [IQR]) HbA1c for SMBG use was 8.1 (2.4), whereas postcrossover to CGM use, there was a decline in median (IQR) levels to 7.7 (1.9) (

conclusionWe found that people who switched to CGM use had significantly improved HbA1c levels compared to those who switched to glucose monitoring with SMBG.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringCross-Over StudiesDiabetes Mellitus, Type 1Electronic Health RecordsGlycated HemoglobinAdolescentAdultChildFemaleHumansMaleMiddle AgedYoung AdultBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanCGMcrossover studyHbA1cSMBGT1D

Identifiers

PMID37264642
PMCPMC11688696
OpenAlexW4379094329

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.