Abstract 4142959: Carotid 3D Plaque Composition after Carnitine Supplementation in Patients with Metabolic Syndrome
Bibliographic record
Abstract
Background: L-Carnitine (L-C) is a widely used nutritional supplement, but its effect on cardiovascular disease (CVD) is controversial. L-C has been shown to have benefits for CVD but is also believed to be associated with pro-atherogenic mechanisms. We have previously shown that L-C does not cause plaque progression (no effect) in metabolic syndrome patients supplemented with L-C but indicated an increase in stenosis. Carotid plaque ultrasound pixel distribution analysis (PDA) can identify plaque tissue types (soft vs calcified) indicating if a plaque is prone to rupture and to cause cardiovascular events. Beyond plaque volume (quantity), a change in plaque composition may have a role in causing cardiovascular events (increased lipid core). Research Questions/Hypothesis: Is there a change in 3D plaque composition from baseline to 6-month when taking an L-C supplement in metabolic syndrome patients? If L-C is associated with pro-atherogenic mechanisms, perhaps plaque composition may change (increased fat), increasing risk for events. Methods: Patients were selected from cardiology and stroke clinics who met the diagnostic criteria for metabolic syndrome. Participants (n=157) were randomized to 6-month L-C (2g/day, n=76) or placebo (n=81). Participants received a 3D carotid ultrasound at baseline and 6-months. Carotid plaques were analyzed using a novel 3D carotid arterial plaque composition analysis software (Carotid Model, Figure) that uses deep learning artery and plaque classifications with grayscale PDA (Philips Healthcare). 3D percent change in plaque volume, blood, fat, muscle, fibrous, and calcium due to L-C supplementation was assessed by pairwise t-test. Results: We found no difference in baseline characteristics between placebo and L-C arms. There was no change in percent total plaque volume (L-C=4.18% vs Placebo=17.0%; P=0.24). Each plaque composition component remained similar from baseline to 6-month within arms and between arms (Table). There was a slight increase in grayscale median value in the placebo arm. Conclusion(s): We did not observe a change in carotid 3D plaque volume or plaque composition following 6-month treatment with L-C. Our findings support the theory that L-C may not be directly involved in a pro-atherogenic mechanism. Although L-C supplementation did not influence plaque composition in this population, the software has great potential in determining changes in plaque vulnerability over time in response to drug therapy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".