High risk of early recurrent stroke in patients with near-occlusion with full collapse of the internal carotid artery
Bibliographic record
Abstract
We aimed to validate the prognostic ability and assess interrater reliability of a recently suggested measurement-based definition of near-occlusion with full collapse (distal ICA diameter ≤ 2.0 mm and/or ICA ratio ≤ 0.42). 118 consecutive patients with symptomatic near-occlusion were prospectively included and assessed on computed tomography angiography by 2 blinded observers, 26 (22%) had full collapse. At 2 days after presenting event, the risk of preoperative stroke was 3% for without full collapse and 16% for with full collapse (p = 0.01). At 28 days, this risk was 16% for without full collapse and 22% for with full collapse (p = 0.22). Interrater reliability was perfect (kappa 1.0). Thus, near-occlusion with full collapse should be defined as distal ICA ≤ 2.0 mm and/or ICA ratio ≤ 0.42 in order to detect cases with very high risk of early stroke recurrence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".