Early insulin resistance in normoglycemic low-risk individuals is associated with subclinical atherosclerosis
Bibliographic record
Abstract
BACKGROUND: Elevated glycated hemoglobin (HbA1c) is associated with a higher burden of subclinical atherosclerosis (SA). However, the association with SA of earlier insulin resistance markers is poorly understood. The study assessed the association between the homeostatic model assessment of insulin resistance index (HOMA-IR) and SA in addition to the effect of cardiovascular risk factors (CVRFs) in individuals with normal HbA1c. METHODS: A cohort of 3,741 middle-aged individuals from the Progression of Early Subclinical Atherosclerosis (PESA) study with basal HbA1c < 6.0% (< 42 mmol/mol) and no known CV disease underwent extensive imaging (multiterritorial vascular ultrasound and coronary artery calcium score, CACS) to assess the presence, burden, and extent of SA. RESULTS: Individuals with higher HOMA-IR values had higher rates of CVRFs. HOMA-IR showed a direct association with the multiterritorial extent of SA and CACS (p < 0.001) and with global plaque volume measured by 3-dimensional vascular ultrasound (p < 0.001). After adjusting for key CVRFs and HbA1c, HOMA-IR values ≥ 3 were associated with both the multiterritorial extent of SA (odds ratio 1.41; 95%CI: 1.01 to 1.95, p = 0.041) and CACS > 0 (odds ratio 1.74; 95%CI: 1.20 to 2.54, p = 0.004), as compared with the HOMA-IR < 2 (the reference HOMA-IR category). In a stratified analysis, this association remained significant in individuals with a low-to-moderate SCORE2 risk estimate (75.6% of the cohort) but not in high-risk individuals. CONCLUSIONS: The use of HOMA-IR identified low-risk individuals with a higher burden of SA, after adjusting for the effects of key traditional CVRFs and HbA1c. HOMA-IR is a simple measure that could facilitate earlier implementation of primary CV prevention strategies in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".