Echogenicity of the carotid intima–media complex and cardiovascular risk factors
Bibliographic record
Abstract
INTRODUCTION: Increased carotid intima-media thickness (IMT) has been associated with increased risk of myocardial infarction (MI) and stroke. A measure of echogenicity, the grey scale median (GSM), has been shown to be inversely correlated with cardiovascular risk factors and to be predictive of mortality in a community-based cohort. We assessed the factors associated with carotid IM-GSM in younger, non-diabetic patients with a recent MI. METHODS AND RESULTS: A total of 122 patients (women, 25%) aged 31-80 years (61) were recruited 2-3 days after an acute MI. Ultrasound examinations of the carotid arteries were performed 1-12 months after the MI. IMT was 0·78 (SD 0·17) mm on the right side and 0·81 (0·20) mm on the left side (P = 0·05). GSM was 88·60 (range 46-132, SD 18·32) on the right side and 82·10 (40-126, 17·89) on the left side (P = 0·002). Triglycerides (TG) correlated with GSM on both sides (right, r = -0·27, P = 0·003; left, r = -0·18, P = 0·05). On the right side, GSM was 92·15 and 82·26 (P = 0·05) in patients with TG < and ≥1·7, and on the left side, it was 84·04 and 74·55 (P = 0·02) in patients with TG < and ≥2·3. On multivariate analysis, TG were significantly associated with GSM, both on the right side (P = 0·01) and on the left side (P = 0·009). CONCLUSION: We found a negative association between TG and carotid IM-GSM on both sides in patients with a recent MI. Our results also suggest that atherosclerosis progression may be faster on the left side in patients with coronary heart disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".