Plaque morphology (the PLAC Scale) on CT angiography: predicting long-term anatomical success of primary carotid stenting
Bibliographic record
Abstract
OBJECT: Carotid angioplasty and stenting has emerged as an alternative to carotid endarterectomy for the treatment of atherosclerotic carotid stenosis. Primary carotid stenting, performed using self-expanding stents alone without deliberate use of embolic protection devices and balloon angioplasty, has been shown to be effective and faster, cheaper, and potentially safer than conventional techniques. However, the long-term morphological results of this technique have not been established. The aim of this study was to determine whether preprocedural carotid plaque imaging at the site of maximal stenosis by using CT angiography (CTA) could predict the long-term morphological outcome of primary carotid stenting. METHODS: One hundred eighty-one patients were treated over an 11-year period. Preprocedural CTA was performed in 102 of these. A morphological scale (the Predicting Long-term outcome with Angioplasty of the Carotid artery [PLAC] Scale), with grades from 0 to 4 and A or B, was used to evaluate the circumferential degree of plaque calcification, and the presence or absence of soft plaque. All patients were followed using duplex carotid ultrasound and plain radiographs. Satisfactory morphological outcome was defined as a peak systolic velocity < 120 cm/s and internal carotid artery/common carotid artery ratio < 1.4. RESULTS: The average follow-up duration was 29.7 months (median 24.5 months, range 0.3-87 months). Univariate logistic regression demonstrated that a low calcification grade (p < 0.001), less thick calcification (p < 0.001), and moderate amounts of soft plaque (p < 0.001) are factors that are highly associated with good long-term outcome. Multivariate analyses confirmed that these factors are independent of each other in predicting outcome. CONCLUSIONS: The long-term morphological outcome of primary carotid stenting was predicted with considerable accuracy by using a straightforward CTA carotid plaque grading scale.
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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 | 0.004 |
| 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 | 0.000 | 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".