Evidence mapPaperPMID 38629784Full record

ReviewJournal of diabetes science and technology2024

Continuous Glucose Monitoring for Prediabetes: What Are the Best Metrics?

Salwa J Zahalka, Rodolfo J Galindo, Viral N Shah, Cecilia C Low Wang

Registry-linked trialOpen access · greenAbstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07452159 (Diabetes in Asians at Risk in Youth), which is not on this map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
10.4field-weighted citation impact, top 1% 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.

NCT07452159 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Diabetes in Asians at Risk in Youth

TypeobservationalSponsorSingapore General HospitalRan2026 to 2029Enrolled3,000ConditionsYoung Onset Asian Diabetes (Under 40 Years)ArmsOral glucose tolerance test and HbA1c, Anthropometric measurements, Body impedance Analysis, Handgrip measurement, Continuous glucose monitoring
3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 29 citations in OpenAlex.

  1. Review
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Use of technology in prediabetes and precision prevention.Journal of diabetes investigation · 2025
    Review
  14. Article
  15. Article
  16. Article
  17. 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

4 authors at 3 institutions in 1 country.

Salwa J ZahalkaDivision of Endocrinology, Metabolism and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Rodolfo J GalindoMiller School of Medicine, University of Miami, Miami, FL, USA.ORCID 0000-0002-9295-3225
Viral N ShahDivision of Endocrinology and Metabolism, Indiana University, Indianapolis, IN, USA.ORCID 0000-0002-3827-7107
Cecilia C Low WangDivision of Endocrinology, Metabolism and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.ORCID 0000-0001-8557-5417
University of Colorado Anschutz Medical Campus · USIndiana University – Purdue University Indianapolis · USUniversity of Miami · US

Funding

Technologies Advancing Translation - Regional CoreP30DK111024 · EMORY UNIVERSITY · 2025 to 2025
$775k
Use of Continuous Glucose Monitoring (CGM) in End-Stage Renal Disease(ESRD) Patients with Type 2 DiabetesK23DK123384 · NIDDK · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Rodolfo Galindo · 2022 to 2024
$369k
Pharmaco-epidemiology of diabetes in patients with end-stage kidney diseaseR03DK138255 · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · 2025 to 2025
$115k
NIDDK NIH HHS K23 DK123384NIDDK NIH HHS P30 DK111024NIDDK NIH HHS R03 DK138255
6 · The paper itself

Abstract

backgroundContinuous glucose monitoring (CGM) has transformed the care of type 1 and type 2 diabetes, and there is potential for CGM to also become influential in prediabetes identification and management. However, to date, we do not have any consensus guidelines or high-quality evidence to guide CGM goals and metrics for use in prediabetes.

methodsWe searched PubMed for all English-language articles on CGM use in nonpregnant adults with prediabetes published by November 1, 2023. We excluded any articles that included subjects with type 1 diabetes or who were known to be at risk for type 1 diabetes due to positive islet autoantibodies.

resultsBased on the limited data available, we suggest possible CGM metrics to be used for individuals with prediabetes. We also explore the role that glycemic variability (GV) plays in the transition from normoglycemia to prediabetes.

conclusionsGlycemic variability indices beyond the standard deviation and coefficient of variation are emerging as prominent identifiers of early dysglycemia. One GV index in particular, the mean amplitude of glycemic excursion (MAGE), may play a key future role in CGM metrics for prediabetes and is highlighted in this review.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringPrediabetic StateContinuous Glucose MonitoringHumansBlood Glucosecontinuous glucose monitoringglucose intoleranceglycemic variabilityimpaired glucosemetricsprediabetes

Identifiers

PMID38629784
PMCPMC11307227
OpenAlexW4394873101

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

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.