Abstract 146: Endovascular Treatment May Still Benefit Patients With Low Baseline Alberta Stroke Program Early CT Score
Bibliographic record
Abstract
Introduction: We aimed to investigate the outcome of endovascular treatment (EVT) for acute ischemic stroke in patients with low Alberta Stroke Program Early CT Score (ASPECTS). Methods: This study reports on MR CLEAN Registry patients with available baseline ASPECTS (N=1423). ASPECTS was trichotomized in 0-4, 5, and 6-10 in order to create low ASPECTS groups of similar size. Primary outcome was modified Rankin Scale score (mRS) at 90 days. Secondary outcomes were symptomatic intracranial hemorrhage (sICH) and mortality. Benefit of reperfusion (defined as extended thrombolysis in cerebral infarction [eTICI] score 2B-3) was assessed by multivariable ordinal logistic regression analysis, including an interaction term of reperfusion and ASPECTS, and it was expressed as an adjusted common odds ratio (acOR). A comparison with the MR CLEAN trial control arm was made to assess benefit of EVT. Results: Higher trichotomized ASPECTS was associated with improved mRS (acOR 1.4, 95%CI 1.2-1.7). For ASPECTS 0-4 (n=93) successful reperfusion was not associated with improved mRS (acOR 1.4, 95%CI 0.6-2.9). ASPECTS 5 (n=63) and ASPECTS 6-10 subgroups (n=1267) however, did show significant benefit of reperfusion (acOR 3.9, 95%CI 1.3-11.8; acOR 2.7, 95%CI 2.2-3.3, respectively)(Fig1). Interaction between trichotomized ASPECTS and reperfusion was not significant ( p =0.13). Comparison with the MR CLEAN trial control group showed that trichotomized ASPECTS did not modify the effect of EVT ( p =0.14). Patients with lower trichotomized ASPECTS had a higher risk of mortality (aOR 0.9, 95%CI 0.9-1.0), but not of sICH (aOR 1.0, 95%CI 0.9-1.1). Conclusion: ASPECTS does not modify effect of reperfusion or EVT on functional outcome after acute ischemic stroke. Patients with ASPECTS 5 or higher seem to benefit from successful reperfusion.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".