Predictors of Acute and Persisting Ischemic Brain Lesions in Patients Randomized to Carotid Stenting or Endarterectomy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We investigated predictors for acute and persisting periprocedural ischemic brain lesions among patients with symptomatic carotid stenosis randomized to stenting or endarterectomy in the International Carotid Stenting Study. METHODS: We assessed acute lesions on diffusion-weighted imaging 1 to 3 days after treatment in 124 stenting and 107 endarterectomy patients and lesions persisting on fluid-attenuated inversion recovery after 1 month in 86 and 75 patients, respectively. RESULTS: Stenting patients had more acute (relative risk, 8.8; 95% confidence interval, 4.4-17.5; P<0.001) and persisting lesions (relative risk, 4.2; 95% confidence interval, 1.6-11.1; P=0.005) than endarterectomy patients. Acute lesion count was associated with age (by trend), male sex, and stroke as the qualifying event in stenting; high systolic blood pressure in endarterectomy; and white matter disease in both groups. The rate of conversion from acute to persisting lesions was lower in the stenting group (relative risk, 0.4; 95% confidence interval, 0.2-0.8; P=0.007), and was only predicted by acute lesion volume. CONCLUSIONS: Stenting caused more acute and persisting ischemic brain lesions than endarterectomy. However, the rate of conversion from acute to persisting lesions was lower in the stenting group, most likely attributable to lower acute lesion volumes. Clinical Trial Registration -URL: www.isrctn.org. Unique identifier: ISRCTN25337470.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".