Safety Evaluation of Primary Carotid Stenting: Transcranial Doppler and MRI
Bibliographic record
Abstract
ABSTRACT: Background and Purpose: Cerebral emboli are generated by every step of standard carotid angioplasty and stenting. Primary carotid stenting (PCS) is a technique in which the use of balloon angioplasty (BA) is minimized to decrease the embolic load. The primary aim of this study is to establish the number of emboli generated by each step of primary stenting and determine the relationship to new diffusion (DWI) lesions on subsequent magnetic resonance imaging (MRI). Methods: Eighty-five patients with severe, symptomatic carotid stenosis were prospectively recruited and underwent carotid stenting. Intraoperative transcranial Doppler was performed in 77 patients. The number and size of microemboli for each of seven procedural steps were recorded. Correlation was made with the number and location of new DWI lesions. Results: PCS was performed in 73 patients. BA was required in 12 patients. The mean number of microemboli was 114, and most microemboli were generated by stent deployment, followed by BA. Balloon techniques generated significantly more emboli than primary stenting (p = 0.017). There was a significant relationship between total microemboli and new DWI lesions (p = 0.009), and between new DWI lesions in multiple territories and the severity of pretreatment stenosis (p = 0.002). Conclusions: During PCS, more emboli are generated by stent deployment than during any other stage of the procedure. When BA is necessary, more malignant emboli are generated but total emboli are unchanged and there is no difference in new diffusion lesions on MRI. PCS is safe and is not inferior to historical controls for the generation of new DWI lesions.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".