Abstract 18292: Storm Preparations: Use of Carotid Ultrasound for Assessment of Atherosclerotic Disease
Bibliographic record
Abstract
Background: A call of warning was raised by scientists at the 2010 American Heart Association meeting: “Cardiovascular Disease in the Elderly is the Coming Tsunami.” Accordingly, the need to develop imaging modalities to detect coronary artery disease (CAD) early was identified. Carotid intimal medial thickening (CIMT) may serve as a systemic barometer of atherosclerosis throughout the arterial tree. Plaque is also often observed in the carotid arteries of patients however its association with CAD is unclear. Our objective was to determine the sensitivity and negative predictive value of CIMT and carotid plaque in consecutive outpatients referred for angiography. Methods: Carotid scans were conducted immediately following the angiogram in 242 consecutive outpatients. An ultrasonography device (General Electric Vivid 7; USA) equipped with a 10 MHz linear probe was used to record images from both the right and left carotid arteries. CIMT in the distal common carotid artery and the maximal two-dimensional thickness of carotid bulb plaque was measured. The angiogram was scored as 0 (no coronary lesions), 1 (mild coronary atherosclerosis), 2 (at least 50% narrowing in one vessel), and 3 (at least 50% narrowing in two or more vessels). Sensitivity and negative predictive value of CIMT < 1mm and of plaque < 1.5 mm was determined for an angiogram score of 0 or 1. Results: The prevalence of significant CAD in this population was 71%. The average CIMT for men was 0.94 +/− 0.22 mm and for women was 0.88 +/− 0.19 mm. The mean maximum plaque value was 2.31 +/− 0.95 mm for men, and 2.03 +/− 1.01 mm for women. Plaque thickness but not CIMT was greater in patients with CAD (p< 0.001). The negative predictive value of CIMT was poor (< 50%) however the sensitivity and negative predictive value of plaque was 94 and 75 % respectively. Conclusion: A complete carotid ultrasound that includes plaque assessment may serve as an inexpensive and low-risk test to help rule out CAD in outpatients.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".