Measurement of Intima-Media Thickness vs. Carotid Plaque: Uses in Patient Care, Genetic Research and Evaluation of New Therapies
Bibliographic record
Abstract
Intima-media thickness (IMT) has been measured for over 20 years, and is widely regarded as a surrogate for atherosclerosis. However, in the carotid arteries atherosclerosis is focal, manifesting as plaques. IMT is often measured deliberately where no plaque exists, or multiple measurements may be averaged, including only one or two that intersect plaque. IMT and plaque are biologically and genetically distinct, so they can be expected to respond differentially to therapies for atherosclerosis. Furthermore, because plaques grow along the carotid arteries 2.4 times faster than they thicken, progression or regression of total plaque area is more sensitive to effects of therapy than IMT. Because plaques also grow and regress circumferentially, three-dimensional (3-D) plaque volume is two orders of magnitude more sensitive to effects of therapy than is IMT. While 3-D ultrasound requires special equipment, total plaque area can be measured using the same equipment as IMT. Because plaque and IMT are biologically and genetically distinct entities, representing different phenotypes of atherosclerosis, both should be measured in any situation where IMT is measured, with the exception of studies in children too young for the occurrence of plaque. IMT should not be called 'atherosclerosis': the phenotype being assessed should be specified.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".