Endovascular Treatment May Benefit Patients With Low Baseline Alberta Stroke Program Early CT Score: Results From the MR CLEAN Registry
Bibliographic record
Abstract
Background: Current American guidelines are uncertain regarding endovascular treatment (EVT) for patients with acute ischemic stroke with an Alberta Stroke Program Early Computed Tomography Score (ASPECTS) <6. Dutch guidelines do not specify ASPECTS-based exclusion criteria for EVT. In this retrospective observational cohort study, we investigated outcomes of EVT in patients with low ASPECTS in the MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in The Netherlands) registry. Methods: ASPECTS was trichotomized into 0 to 2, 3 to 5, and 6 to 10, according to the grouping used in the ongoing trials. The effect of ASPECTS (granular and trichotomized) on 90-day functional outcome (modified Rankin Scale score) and symptomatic intracranial hemorrhage was assessed with multivariable logistic regression. We included multiplicative interaction terms to evaluate treatment interaction between ASPECTS and reperfusion (extended thrombolysis in cerebral infarction score 2B-3) as a proxy for EVT. Results: =0.76 for trichotomized ASPECTS). All ASPECTS subgroups showed benefit of reperfusion (0-2 [n = 39]: acOR, 7.40; 95% CI, 1.41-18.68; 3-5 [n = 214]: acOR, 1.95; 95% CI, 1.13-3.34; 6-10 [n = 2822]: acOR, 2.41; 95% CI, 2.08-2.80). ASPECTS was not associated with symptomatic intracranial hemorrhage (granular: acOR, 1.00; 95% CI, 0.92-1.10, trichotomized: acOR, 0.92; 95% CI, 0.60-1.41). Conclusion: Benefit of reperfusion was not modified by baseline ASPECTS. Patients in all ASPECTS subgroups showed benefit of reperfusion. These findings do not support withholding EVT on the basis of low ASPECTS only.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".