Evidence map›Paper›PMID 41217525›Full record

ArticleDiabetologia2026

Association of HbA

Viral N Shah, Yongjin Xu, Yaghoub Dabiri, Hemanth P Mohanadas, Alan Cheng, Timothy C Dunn

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetologia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Viral N Shah *Division of Endocrinology & Metabolism, Indiana University School of Medicine, Indianapolis, IN, USA. shahvi@iu.edu.ORCID http://orcid.org/0000-0002-3827-7107
Yongjin Xu *Abbott Diabetes Care, Alameda, CA, USA.ORCID http://orcid.org/0000-0001-9446-8402
Yaghoub DabiriAbbott Diabetes Care, Alameda, CA, USA.ORCID http://orcid.org/0000-0003-4778-7501
Hemanth P MohanadasAbbott Diabetes Care, Alameda, CA, USA.ORCID http://orcid.org/0000-0001-8932-7816
Alan ChengAbbott Diabetes Care, Alameda, CA, USA.ORCID http://orcid.org/0000-0001-7897-4751
Timothy C DunnAbbott Diabetes Care, Alameda, CA, USA.ORCID http://orcid.org/0000-0003-3487-2504

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisThis study aimed to compare the predictive performance of HbA

methodsWe used the data from a previously published longitudinal case-control study that collected CGM data for up to 7 years prior to diagnosis of incident diabetic retinopathy or no retinopathy (control participants) among adults with type 1 diabetes. Mutual information scores (MIS), receiver operating characteristics (ROC) curves and machine learning models were used to assess the associations of diabetic retinopathy with HbA

resultsThe uGMI demonstrated a stronger association with incident diabetic retinopathy (MIS 0.148) compared with HbA CONCLUSIONS/

interpretationThe uGMI is a slightly stronger predictor of diabetic retinopathy risk compared with HbA

Indexed as

Blood GlucoseDiabetes Mellitus, Type 1Diabetic RetinopathyGlycated HemoglobinAdultBlood Glucose Self-MonitoringCase-Control StudiesFemaleHumansLongitudinal StudiesMachine LearningMaleMiddle AgedROC CurveBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanCGMDiabetic retinopathyHbA1cType 1 diabetesUpdated GMI

Identifiers

PMID41217525
PMCPMC12881093

What Socratic holds

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LicenceCC BY
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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.