Evidence map›Paper›PMID 22768904›Full record

ReviewJournal of diabetes science and technology2012

The challenges of measuring glycemic variability.

David Rodbard

Abstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
–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

41 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. To What Extent Is HbJournal of clinical medicine · 2024
    Article
  6. Article
  7. A New Analysis Tool for Continuous Glucose Monitor Data.Journal of diabetes science and technology · 2022
    Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Glycemic Variability: Risk Factors, Assessment, and Control.Journal of diabetes science and technology · 2019
    Review
  20. 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

1 author.

David RodbardBiomedical Informatics Consultants LLC, Potomac, Maryland 20854-4721, USA. drodbard@comcast.net

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This commentary reviews several of the challenges encountered when attempting to quantify glycemic variability and correlate it with risk of diabetes complications. These challenges include (1) immaturity of the field, including problems of data accuracy, precision, reliability, cost, and availability; (2) larger relative error in the estimates of glycemic variability than in the estimates of the mean glucose; (3) high correlation between glycemic variability and mean glucose level; (4) multiplicity of measures; (5) correlation of the multiple measures; (6) duplication or reinvention of methods; (7) confusion of measures of glycemic variability with measures of quality of glycemic control; (8) the problem of multiple comparisons when assessing relationships among multiple measures of variability and multiple clinical end points; and (9) differing needs for routine clinical practice and clinical research applications.

Indexed as

Analysis of VarianceBiomarkersBlood GlucoseData Interpretation, StatisticalDiabetes MellitusDisease ProgressionGlycated HemoglobinHumansPredictive Value of TestsPrognosisReproducibility of ResultsRisk FactorsTime FactorsUncertaintyBiomarkersBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID22768904
PMCPMC3440043

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.