Supplementary Material for: Multiparametric Neuroimaging and Its Association with Non-Contrast Computed Tomography in Late-Window Large Vessel Occlusion Acute Stroke
Bibliographic record
Abstract
Introduction: Endovascular treatment (EVT) for acute ischemic stroke (AIS) between 6 and 24 h is established as a standard of care among patients selected by multiparametric neuroimaging. We aimed to explore neuroimaging parameters in late-window large vessel occlusion (LVO) patients and its association with non-contrast computed tomography (NCCT) findings. Methods: We included consecutive AIS patients within 6–24 h from the symptoms onset with LVO. We described multiparametric imaging findings, the rate of patients who fulfilled imaging perfusion criteria according to the DAWN and DEFUSE-3 trials that define the computed tomography perfusion mismatch (CTP-MM) group and its association with NCCT focused on Alberta Stroke Program Early CT Score (ASPECTS). We also analyzed the association between neuroimaging parameters and the clinical outcome determined by the 90-day modified Rankin scale (mRS). Results: We included 206 patients, of them, 176 (85.4%) presented CTP-MM and 184 (89.3%) presented an ASPECTS ≥6 on admission. The rate of CTP-MM was 90.8% in patients with ASPECTS ≥6, compared with 40.9% in those with low ASPECTS. ASPECTS was moderately correlated with ischemic core determined by cerebral blood flow <30% volume (rS = −0.557, p < 0.001). In EVT-treated patients (185, 89.8%), after adjusting for identifiable confounders, the presence of CTP-MM was a predictor of 90-day functional independence (OR: 3.38; 95% CI: 1.01–11.29; p = 0.048). We did not find an association between CTP-MM and 90-day functional disability (ordinal mRS shift, aOR: 1.39; 95% CI: 0.58–3.34; p = 0.459). Conclusions: A great majority of patients who presented a LVO in the late window fulfilled guidelines imaging criteria to undergo EVT, especially those with high ASPECTS (≥6). Our data suggest that NCCT with CT angiography could be a reasonable approach for AIS treatment selection also in the late window.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.789 | 0.181 |
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".