Combined Effect of Age and Baseline Alberta Stroke Program Early Computed Tomography Score on Post-Thrombectomy Clinical Outcomes in the MR CLEAN Registry
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Ischemic brain tissue damage in patients with acute ischemic stroke, as measured by the Alberta Stroke Program Early CT Score (ASPECTS) may be more impactful in older than in younger patients, although this has not been studied. We aimed to investigate a possible interaction effect between age and ASPECTS on functional outcome in acute ischemic stroke patients undergoing endovascular treatment, and compared reperfusion benefit across age and ASPECTS subgroups. METHODS: Patients with ischemic stroke from the MR CLEAN Registry (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands; March 2014-November 2017) were included. Multivariable ordinal logistic regression was performed to obtain effect size estimates (adjusted common odds ratio) on functional outcome (modified Rankin Scale score) for continuous age and granular ASPECTS, with a 2-way multiplicative interaction term (age×ASPECTS). Outcomes in four patient subgroups based on age (< versus ≥ median age [71.8 years]) and baseline ASPECTS (6-10 versus 0-5) were assessed. RESULTS: =0.299). CONCLUSIONS: Although the proportion of poor outcomes following endovascular treatment was highest in older patients with low baseline ASPECTS, outcomes did not significantly differ from the main effect. These results do not support withholding endovascular treatment based n a combination of high age and low ASPECTS.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".