Abstract 18: The Effect of Lipid Modification on Peripheral Arterial Disease after Endovascular Intervention Trial (ELIMIT)
Bibliographic record
Abstract
BACKGROUND The Effect of Lipid Modification on Peripheral Arterial Disease after Endovascular Intervention Trial (ELIMIT), a prospective double-blind randomized study, was designed to determine over 24-months, the effects of triple drug lipid modification therapy versus mono therapy on the progression of atherosclerotic lesions in the distal superficial femoral artery (SFA), as assessed by 3.0T magnetic resonance imaging (MRI). METHODS A total of 95 patients were randomized to either mono therapy with simvastatin (40mg) or triple therapy with simvastatin (40mg), extended-release niacin (1.5g), and ezetimibe (10mg). MR imaging was performed at baseline, 6-, 12-, and 24-months. SFA wall, lumen, and total vessel volumes were quantified using inter-visit co-registered proton-density-weighted turbo spin echo MRI sequences. MRI derived SFA parameters and lipids were analyzed with multi-level models and non-parametric tests, respectively. RESULTS Baseline characteristics did not differ between mono and triple therapy groups, except for ethnicity (Table). There was no difference in adverse cardiovascular events between groups (p=0.99). SFA wall, lumen, and vessel volumes increased non-significantly for both groups between baseline and 24-months. Non-high-density lipoprotein cholesterol showed a larger reduction in triple therapy compared with mono therapy at 12-months (p=0.01). CONCLUSION Despite improved atherogenic lipid profiles, there was no significant difference between mono therapy with simvastatin and triple therapy with simvastatin, extended-release niacin, and ezetimibe for the 24-month changes in total SFA wall, lumen, and vessel volumes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".