Abstract P563: Prognosis Driven Definition of Carotid Near-Occlusion With Full Collapse
Bibliographic record
Abstract
Introduction: Carotid near-occlusion is a severe carotid stenosis causing distal artery collapse of varying degree. Near-occlusion is often divided into a “full collapse” group with a threadlike distal lumen, and the often overlooked “without full collapse” group with a normal-appearing, albeit small, distal lumen. By this division by appearance, symptomatic near-occlusion with full collapse has been reported to have worse short-term prognosis than those without full collapse, no other division has been assessed for prognosis. The aim of this study was to assess if a measurement based definition of full collapse might improve prognostic discrimination. Methods: 99 consecutive patients with symptomatic near-occlusion diagnosed on CT-angiography were included. The risk of preoperative recurrent ipsilateral ischemic stroke within 28 days of presenting event was assessed with Kaplan-Meier analysis, censoring at revascularization. We assessed residual stenosis diameter, distal ICA diameter, ICA-ratio (side-to-side), and ICA-ECA ratio as risk markers. Results: By appearance, the 28-day risk of stroke tended to be higher for full collapse (27%, 11/42) than without full collapse (11%, 6/57), p=0.054 (figure). The best new definition of full collapse was distal ICA diameter ≤2.0 mm and/or ICA ratio ≤0.47. 10 patients were reclassified by this new definition compared to appearance definition, 5 in each direction. By the new definition, 28-day risk of stroke was higher in full collapse (34%, 14/42) than without full collapse (5%, 3/57), p<0.001 (fig 1B). Conclusions: Compared to the appearance based definition, our new definition of separating near-occlusions into with and without full collapse yields similar groups sizes but better prognostic discrimination. This new definition could be used as inclusion criteria in future treatment trials.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".