Influence of ASPECTS and endovascular thrombectomy in acute ischemic stroke: a meta-analysis
Bibliographic record
Abstract
Background Prompt revascularization of the ischemic penumbra following an acute ischemic event (AIS) has established benefit within the literature. However, use of the semi-quantitative Alberta Stroke Program Early CT Score (ASPECTS) to evaluate patient suitability for revascularization has been inconsistent in patient risk stratification and selection. Objective To conduct a meta-analysis to evaluate the available evidence for a clinically valid ASPECTS threshold in assessment of suitability for revascularization following AIS. Methods Two independent reviewers searched Medline (Ovid) and Cochrane Central Register of Systematic Reviews databases for studies appraising outcomes of endovascular thrombectomy (EVT) in relation to a variably-defined preoperative ASPECTS. Results A total of 13 articles were included. The pooled good outcome proportion after EVT was 41.4% (95% CI 36.4% to 46.6%; p<0.001), with subjective study-specific definitions of favorable and unfavorable subgroup outcomes of 49.7% (95% CI 44.2% to 55.3%; I2=76.5%; p<0.001) and 33.2% (95% CI 28.5% to 38.3%; I2=33.16%), respectively. Objective trichotomization into low (0–4), intermediate (5–7), and high (8–10) subgroups yielded pooled good outcome proportions of 17.1% (95% CI 6.8% to 36.8%; I2=64.24%; p=0.039), 35.7% (95% CI 30.5% to 41.3%; I2=23.11%; p=0.245), and 49.7% (95% CI 44.2% to 55.3%; I2=76.5%; p<0.001) for low, intermediate, and high ASPECTS, respectively. Conclusions A subjectively favorable ASPECTS is associated with significantly better outcomes after EVT than an unfavorable ASPECTS, regardless of the cut-off used. EVT is unlikely to be useful in patients with an objectively low ASPECTS and is likely to be useful for those with high ASPECTS; findings in patients with intermediate ASPECTS were equivocal.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.062 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".