Maximum carotid artery wall thickness and risk factors in a young primary prevention population
Bibliographic record
Abstract
Maximum carotid artery wall thickness was utilized in a primary prevention population and compared with baseline risk factors. Carotid wall thickness was measured between the blood-intima and media-adventitia interfaces by B-mode ultrasonography using software calipers at points of protrusion. Long-axis measures were confirmed by short-axis assessment. The maximum carotid wall thickness for each subject was divided by age in years to yield an annual accretion rate (called carotid intima-media thickness accretion rate [CIMTAR]). The entire study population was then divided by median CIMTAR to investigate the association with baseline variables used in standard risk assessments with the bifurcated groups. Traditional risk factors such as age, diabetes, smoking, hyperlipidemia, and obesity were not associated with greater than median CIMTAR. Only male gender (P = 0.02) and systolic blood pressure (P = 0.002) in baseline variables were associated with an elevated CIMTAR for the entire population. Among those not taking lipid-lowering therapy at baseline, only systolic blood pressure remained significant (P = 0.0002). Correlations between low-density lipoprotein (LDL) cholesterol level and maximum carotid wall thickness/CIMTAR were weak for the entire population (r = -0.17/r = -0.12, respectively). Measure of maximum carotid wall thickness may select patients earlier for treatment than traditional risk factors. The addition of CIMTAR to risk algorithms may permit a single-point assignation of subsequent vascular risk that is more efficacious than traditional risk factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".