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Record W4410113123 · doi:10.1136/bmjdrc-2024-004713

Relationship between time-varying achieved HbA<sub>1c</sub> and risk of coronary artery disease events among common haptoglobin phenotype groups with type 2 diabetes: the ADVANCE study

2025· article· en· W4410113123 on OpenAlexafffund
Leah E. Cahill, Rachel A Warren, Samantha K Lavallée, Andrew P. Levy, Allie S. Carew, John L. Sapp, Michelle Samuel, Elizabeth Selvin, Neil R Poulter, Michel Marre, Stephen Harrap, Giuseppe Mancia, Katie Harris, John Chalmers, Mark Woodward, Eric B. Rimm

Bibliographic record

VenueBMJ Open Diabetes Research & Care · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHemoglobin structure and function
Canadian institutionsNova Scotia Health AuthorityDalhousie University
FundersNational Heart, Lung, and Blood InstituteNational Health and Medical Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchNational Institutes of HealthResearch Nova Scotia
KeywordsMedicineInternal medicineHaptoglobinType 2 diabetesCoronary artery diseaseGlycated hemoglobinDiabetes mellitusGastroenterologyHazard ratioCohortCohort studyEndocrinologyConfidence interval

Abstract

fetched live from OpenAlex

Introduction This study sought to determine whether the association between attaining specific glycated hemoglobin (HbA1c) targets (<7.0% (<53 mmol/mol) and ≥8.0% (≥64 mmol/mol) compared with 7.0%–7.9%) over time and risk of incident coronary artery disease (CAD) was dependent on haptoglobin (Hp) phenotype in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) study. Research design and methods Prospectively collected HbA1c data from the ADVANCE biomarker case-cohort study, updated at 6 months and every 12 months thereafter over a median of 5.0 (IQR 4.5–5.3) years, were analyzed in relation to incident CAD in the Hp2-2 (n=1323) and non-Hp2-2 (n=2069) phenotypes separately using weighted multivariable-adjusted Cox regression models. Additional a priori stratifications by sex, race, previous cardiovascular disease (CVD), and type 2 diabetes duration were performed. Results Mean HbA1c was similar in each phenotype group throughout the study. Compared with HbA1c of 7.0%–7.9%, HbA1c <7.0% was not associated with CAD risk for any phenotype group or subgroup. HbA1c ≥8.0% compared with 7.0%–7.9% over time was associated with higher CAD risk for the Hp2-2 phenotype only (HR 1.53, 95% CI 1.01 to 2.32; no significant association in the non-Hp2-2 type: 1.26, 0.89 to 1.77, p-interaction=0.71); this was pronounced when those with previous CVD at baseline were excluded (Hp2-2: 2.80, 1.41 to 5.53, p-interaction=0.03). Compared with HbA1c of <8.0%, having HbA1c ≥8.0% was associated with a 59% higher CAD risk among participants with the Hp2-2 phenotype (1.59, 1.12 to 2.26) and a 39% higher CAD risk among participants without the Hp2-2 phenotype (1.39, 1.03 to 1.88, p-interaction=0.97). Conclusions The present ADVANCE analysis suggests that not having HbA1c ≥8.0%, rather than achieving HbA1c <7.0%, was found to be particularly important for CAD prevention among people with type 2 diabetes and the common Hp2-2 phenotype. While the subgroup analyses were likely underpowered, their inclusion is hypothesis generating and can be used in future meta-analyses to improve power and generalizability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.339
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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