Relationship Between Baseline Infarct and Clinical Outcome in Pediatric Large‐Vessel Occlusion Ischemic Stroke
Bibliographic record
Abstract
Background In adults with large‐vessel occlusion stroke, the extent of the baseline infarct measured using the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) predicts outcome and is used during patient selection for mechanical thrombectomy. The relationship between ASPECTS and clinical outcome is unknown in pediatric large‐vessel occlusion stroke. Methods Secondary analysis of a retrospective multicenter case–control study assessing mechanical thrombectomy versus medical management alone for pediatric large‐vessel occlusion stroke across 5 centers in Australia and Canada from 2011 to 2022. ASPECTS was measured on baseline computed tomography or magnetic resonance imaging–diffusion‐weighted imaging while blinded to clinical outcome and treatment status. The relationship between ASPECTS and pediatric modified Rankin scale scores at 3 months following stroke was assessed using ordinal logistic regression. Results In total, n = 24 thrombectomy patients (F = 10, mean age, 11.3 years [SD, 4.36]) and n = 24 control patients (F = 10, mean age, 10.2 years [SD, 4.32) were included. Mean ASPECTS was 6.3 (SD, 2.37) in the thrombectomy group and 6.1 (SD, 2.64) in the control group. In patients undergoing thrombectomy, baseline ASPECTS significantly correlated with pediatric modified Rankin scale scores at 3 months (odds ratio, 1.58 [95% CI, 1.10–2.27]; P = 0.013). In control patients, there was no significant correlation (odds ratio, 1.17 [95% CI, 0.87–1.55]; P = 0.298). Six of 7 thrombectomy patients with a large baseline infarct (ASPECTS <6) had a pediatric modified Rankin scale score of 0 to 2 at final follow‐up. Conclusion Baseline ASPECTS was significantly associated with clinical outcome in pediatric patients with large‐vessel occlusion stroke who received mechanical thrombectomy. Thrombectomy patients with low ASPECTS demonstrated favorable long‐term outcomes, suggesting ASPECTS alone should not be used to exclude pediatric patients from receiving thrombectomy.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".