Evidence mapPaperPMID 38295402Full record

ReviewDiabetes care2024

The Glucose Management Indicator: Time to Change Course?

Elizabeth Selvin

Open access · greenAbstract readReview
In one paragraph

Review in Diabetes care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
14.7field-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.

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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.

  1. Pooled it
  2. Guideline
  3. Health-related quality of life in racial and ethnic minority adults with type 2 diabetes: validity and responsiveness of the EQ-5D-3L.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Trial
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Association of HbADiabetologia · 2026
    Article
  11. Observational
  12. Review
  13. Article
  14. Article
  15. Article
  16. Managing discordance between HbADiabetic medicine : a journal of the British Diabetic Association · 2025
    Review
  17. Article
  18. Article
  19. Observational
  20. Observational
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

1 author at 1 institution in 1 country.

Elizabeth SelvinDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.ORCID 0000-0001-6923-7151
Johns Hopkins University · US

Funding

Glucose patterns and cardiac arrhythmias in older adults with diabetesR01HL158022 · JOHNS HOPKINS UNIVERSITY · 2025 to 2025
$683k
Effects of the DASH diet on glucose patterns in adults with type 2 diabetesR01DK128900 · JOHNS HOPKINS UNIVERSITY · 2025 to 2025
$553k
NHLBI NIH HHS K24 HL152440NHLBI NIH HHS R01 HL158022NIA NIH HHS RF1 AG074044NIDDK NIH HHS R01 DK128837NIDDK NIH HHS R01 DK128900
6 · The paper itself

Abstract

Laboratory measurement of hemoglobin A1c (HbA1c) has, for decades, been the standard approach to monitoring glucose control in people with diabetes. Continuous glucose monitoring (CGM) is a revolutionary technology that can also aid in the monitoring of glucose control. However, there is uncertainty in how best to use CGM technology and its resulting data to improve control of glucose and prevent complications of diabetes. The glucose management indicator, or GMI, is an equation used to estimate HbA1c based on CGM mean glucose. GMI was originally proposed to simplify and aid in the interpretation of CGM data and is now provided on all standard summary reports (i.e., average glucose profiles) produced by different CGM manufacturers. This Perspective demonstrates that GMI performs poorly as an estimate of HbA1c and suggests that GMI is a concept that has outlived its usefulness, and it argues that it is preferable to use CGM mean glucose rather than converting glucose to GMI or an estimate of HbA1c. Leaving mean glucose in its raw form is simple and reinforces that glucose and HbA1c are distinct. To reduce patient and provider confusion and optimize glycemic management, mean CGM glucose, not GMI, should be used as a complement to laboratory HbA1c testing in patients using CGM systems.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringGlycated HemoglobinDiabetes MellitusGlycemic ControlHumansBlood GlucoseGlycated Hemoglobin

Identifiers

PMID38295402
PMCPMC11116920
OpenAlexW4391378727

What Socratic 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 Socratic graph.