Abstract P11: Clinical Utility of Aspects in Late Window Stroke Thrombectomy Patients: Insights From Star
Bibliographic record
Abstract
Introduction: Recent trials have proven safety and efficacy of mechanical thrombectomy for patients presenting with emergent large vessel occlusion beyond 6 hours of symptom onset. While evidence supports using baseline CT scan to evaluate the candidacy for mechanical thrombectomy for patients presenting in the early window, late window trials have used advanced imaging such as CT and MR perfusion. We aim to assess outcomes of MT stratified by admission Alberta Stroke Program Early CT Score (ASPECTS). Methods: We used data from the prospectively maintained registries of 28 stroke centers in the Stroke Thrombectomy and Aneurysm (STAR) collaboration. Demographics, comorbidities, LVO site, ASPECTS, MT technique, radiographic and clinical outcome data were collected. Patients with M1 or ICA occlusion were included in these analyses. Multivariable analysis was performed using a generalized linear model with logit link to assess for variables associated with favorable outcomes. Results: 3356 patients in the STAR database were reviewed and 347 (10.3%) of those underwent MT in the late window (table). Median age was 69, 189 (54.5%) were female, and 181 (52.2%) were white. 295 patients ASPECTS ≥6. In this group, 200 (68.8%) had M1 occlusion, and the remaining had ICA occlusion. Aspiration thrombectomy was used in 139 (47.1%) of patients. Successful reperfusion was achieved (mTICI≥2b) in 264 (76.1%). sICH was observed in 15 (5.1%). Excellent functional outcome (mRS 0-2) was observed in 124 (42%) patients. ASPECTS score was independently associated with favorable outcomes (aOR 1.2, 95% CI 1.1-1.4, P=0.006). Conclusion: Excellent outcomes are observed in patients with good ASPECT score presenting in the late window irrespective of perfusion criteria. Admission CT scan could be used to triage patients presenting with emergent large vessel occlusion beyond 6 hours of symptom onset.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".