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Record W4399677154 · doi:10.1093/eurjpc/zwae175.326

Does the relationship between time-varying achieved HbA1c and risk of coronary events depend on haptoglobin phenotype within the Action for Health in Diabetes (Look AHEAD) study?

2024· article· en· W4399677154 on OpenAlexaff
Anthony Carew, R A Warren, Michael P. Bancks, Mark A. Espeland, Judy Bahnson, Cara L. Lewis, Andrew P. Levy, John L. Sapp, Robin Urquhart, J L Wang, Eric B. Rimm, Leah E. Cahill

Bibliographic record

VenueEuropean Journal of Preventive Cardiology · 2024
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineHaptoglobinGlycemicType 2 diabetesDiabetes mellitusCoronary artery diseaseInternal medicineBiomarkerType 2 Diabetes MellitusCohortProportional hazards modelDiseaseCohort studyHazard ratioEndocrinologyConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background Our previous research has identified the haptoglobin (Hp) phenotype as a potential biomarker that could be used to personalize glycemic control in type 2 diabetes mellitus (T2DM) to prevent coronary artery disease (CAD), the most common cardiovascular disease (CVD). We observed that attaining HbA1c ≥8.0% compared with 7.0–7.9% was consistently associated with incident CAD risk among participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study with the Hp2-2 type(1). No similar association was observed among participants without the Hp2-2 type. However, most ACCORD participants were middle-aged and older males who were at high risk of CVD. Therefore, the optimal glycemic target for CAD prevention for the Hp types remains unclear among women, younger adults, and those at lower risk of CVD. Objective To explore the relationship between achieving specific clinically relevant HbA1c targets and risk of incident CAD in separate Hp types in a diverse cohort of individuals living with T2DM (the Action for Health in Diabetes (Look AHEAD) study(2)). Methods Hp type was measured in 4,539 blood samples from the Look AHEAD study using a validated assay. Cox regression models with time-varying covariables were used to quantify the association between time-varying achieved HbA1c (<6.5%, 6.5-6.9% and ≥8.0% compared to 7.0-7.9%), updated at years 1-4 and biennially thereafter, and incident CAD in the Hp2-2 (n=1,590) and non-Hp2-2 (n=2,949) types separately. Further pre-specified subgroup analyses by age, sex, and history of CVD were performed in each Hp type group separately. Results During 16 years of follow-up, 744 incident CAD cases were documented. Compared with HbA1c 7.0-7.9%, having HbA1c <6.5% was associated with a 29% lower CAD risk among participants with the non-Hp2-2 type (adjusted HR 0.71, 95% CI 0.55-0.90). In subgroup analyses, this association was present in participants with the non-Hp2-2 type who were male (0.58, 0.42-0.80), who did not have a history of CVD (0.67, 0.49-0.93), and who were aged ≥65 years at baseline (0.64, 0.43-0.95). HbA1c ≥8.0% was associated with CAD risk among participants with the Hp2-2 type who had a history of CVD (1.81, 1.02-3.21). No associations were observed between the other HbA1c targets and CAD risk when Hp2-2 participants were combined or partitioned into subgroups. Conclusion Achieving HbA1c <6.5% compared with 7.0–7.9% reduced the risk of CAD events in Look AHEAD participants with the non-Hp2-2 type, but not in participants with the Hp2-2 type. HbA1c ≥8.0% was associated with higher CAD risk among participants who had the Hp2-2 type and a history of CVD.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.231

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.318
Teacher spread0.276 · 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 teacher head, 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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Citations2
Published2024
Admission routes1
Has abstractyes

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