NCCT and CTA-based imaging protocol for endovascular treatment selection in late presenting or wake-up strokes
Bibliographic record
Abstract
INTRODUCTION: Recently, the benefit of selecting patients for endovascular treatment (EVT) beyond the 6-hour time window using a tissue-based approach was demonstrated in two randomized trials. The optimal imaging protocol for selecting patients is under debate, and it is still unknown if a simpler and faster protocol may adequately select patients with wake-up stroke (WUS) and late-presenting stroke (LPS) for EVT. OBJECTIVE: To compare outcomes of patients submitted to EVT presenting within 6 hours of symptom onset or 6-24 hours after last seen well, selected using non-contrast computed tomography (NCCT) and CT angiography (CTA). METHODS: An observational study was performed, which included consecutive patients with anterior circulation ischemic stroke with large vessel occlusion treated with EVT. Patients presenting within 6 hours were treated if their NIH Stroke Scale (NIHSS) score was ≥6 and Alberta Stroke Program Early CT score (ASPECTS) was ≥6, while patients presenting with WUS or 6-24 hours after last seen well (WUS/LPS) were treated if their NIHSSscore was ≥12 and ASPECTS was ≥7. RESULTS: 249 patients were included, 63 of whom were in the WUS/LPS group. Baseline characteristics were similar between groups, except for longer symptom-recanalization time, lower admission NIHSS (16 vs 17, P=0.038), more frequent tandem occlusions (25.4% vs 11.8%, P=0.010), and large artery atherosclerosis etiology (22.2% vs 11.8%, P=0.043) in the WUS/LPS group. No differences in symptomatic intracranial hemorrhage, peri-procedural complications or mortality were found between groups. Three-month functional independence was similar in both groups (65.1% in WUS/LPS vs 57.0% in ≤6 hours, P=0.259) and no differences were found after adjustment for confounders. CONCLUSIONS: This real-world observational study suggests that EVT may be safe and effective in patients with WUS and LPS selected using clinical-core mismatch (high NIHSS/high ASPECTS in NCCT).
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".