Impact of Pretreatment Noncontrast CT Alberta Stroke Program Early CT Score on Clinical Outcome After Intra-Arterial Stroke Therapy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The efficacy of intra-arterial treatment remains uncertain. Because most centers performing IAT use noncontrast CT (NCCT) imaging, it is critical to understand the impact of NCCT findings on treatment outcomes. This study aimed to compare functional independence and safety among patients undergoing intra-arterial treatment stratified by the extent of ischemic change on pretreatment NCCT. METHODS: The study cohort was derived from multicenter trials of the Penumbra System. Inclusion criteria were anterior circulation proximal occlusion, evaluable pretreatment NCCT, and known time to reperfusion. Ischemic change was quantified using the Alberta Stroke Program Early CT Score (ASPECTS) and stratified into 3 prespecified groups for comparison: 0 to 4 (most ischemic change) versus 5 to 7 versus 8 to 10 (least ischemic change). RESULTS: A total of 249 patients were analyzed: 40 with ASPECTS 0 to 4, 83 with ASPECTS 5 to 7, and 126 with ASPECTS 8 to 10. For ASPECTS 0 to 4, 5 to 7, and 8 to 10, respectively, good outcome (modified Rankin Scale score, 0-2) rates were 5%, 38.6%, and 46% (P<0.0001), and mortality rates were 55%, 28.9%, and 19% (P=0.0001). The only significant pairwise differences were between ASPECTS 0 to 4 and other groups. Symptomatic hemorrhage was more common with lower ASPECTS (P=0.02). Shorter time to reperfusion was significantly associated with better outcomes among patients with ASPECTS 8 to 10 (P=0.01). A similar relationship was seen for ASPECTS 5 to 7 but was not statistically significant. No such relationship was seen for ASPECTS 0 to 4. CONCLUSIONS: NCCT seems useful for excluding patients with the greatest burden of ischemic damage from futile intra-arterial treatment, which is unlikely to result in patient functional independence and increases the risk of hemorrhage.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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".