Effects of plaque composition on vascular remodelling after angioplasty in the MultiVitamins and Probucol (MVP) trial.
Bibliographic record
Abstract
BACKGROUND: The antioxidant probucol reduced coronary restenosis in the MultiVitamins and Probucol (MVP) trial by improving vascular remodelling. Whether calcification limits the extent of adaptive vessel enlargement is not known. OBJECTIVE: To determine whether plaque composition at the dilated site affects probucol-induced vascular remodelling after angioplasty. PATIENTS AND METHODS: Beginning 30 days before percutaneous transluminal coronary angioplasty (PTCA), 317 patients received either probucol, vitamins, probucol and vitamins, or placebo. Patients were then treated for six months after PTCA. Intravascular ultrasound (IVUS) was performed post-PTCA and at follow-up in 94 patients (111 segments). The cross-section for serial analysis was the one at the angioplasty site with the smallest lumen area at follow-up. Quantitative analysis consisted of measurements of lumen area and external elastic membrane (EEM) area. The selected cross-section was also divided into five regions according to the type of plaque present (calcific, fibrotic, hypoechoic, fibrohypoechoic or normal). Plaque characterization scores (PCS) (PCS for arc, area, inner perimeter and outer perimeter) were calculated using weighting factors. RESULTS: There were no interactions between potential PCS covariates and probucol main effect on changes in lumenal, EEM and wall area. There were no significant PCS covariates in the model for change in EEM as they were all removed using a backward stepwise procedure. The last potential covariate (area PCS) had a significance level of P=0.48. In contrast, probucol significantly influenced the change in EEM over time (P=0.003). CONCLUSION: Plaque composition at the dilated site does not appear to influence probucol-induced vascular remodelling after angioplasty.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".