CTP-Defined Large Core Is a Better Predictor of Poor Outcome for Endovascular Treatment Than ASPECTS-Defined Large Core
Bibliographic record
Abstract
BACKGROUND: Recent trials confirmed the effectiveness of endovascular therapy in patients with large ischemic cores. Yet the optimal neuroimaging modalities to define large core remains unclear. We tried to address this question by comparing the functional outcomes in patients receiving thrombectomy selected by either noncontrast computed tomography Alberta Stroke Program Early Computed Tomography Score (ASPECTS) or computed tomography perfusion (CTP). METHODS: This study retrospectively selected patients enrolled in the International Stroke Perfusion Registry between August 2011 and April 2022. Patients with acute stroke with large vessel occlusion in anterior circulation treated with endovascular therapy were included. All received both CTP and noncontrast computed tomography. The primary outcome was defined as poor functional outcome represented by a modified Rankin Scale score of 5 to 6 at 3 months. Large cores were defined in terms of either (1) noncontrast computed tomography ASPECTS ≤5 or (2) core volume ≥70 mL on CTP. RESULTS: A total of 1115 patients were included in the analysis, of which 90 patients had ASPECTS ≤5 (8.1%) and 97 patients CTP core ≥70 mL (8.7%). A fair agreement between ASPECTS and CTP with a κ value of 0.31 (0.21–0.40) was found. Compared with patients with neither CTP nor ASPECTS large cores, those with only ASPECTS-defined large cores (ie, ASPECTS ≤5; n=56) did not have a higher adjusted odds of poor outcome (29%; odds ratio, 1.84 [0.91–3.73]; P =0.089). However, patients with CTP large core but not ASPECTS-defined large core (n=63) had a higher adjusted odds of poor outcome (60%; odds ratio, 3.91 [2.01–7.60]; P <0.001). In time-stratified subgroup analysis (>6 versus ≤6 hours), ASPECTS showed no discriminative difference between ≤5 and >5 in poor outcome for patients receiving endovascular therapy within 6 hours. CONCLUSIONS: CTP core ≥70 mL-defined large cores are more predictive of poor outcome than ASPECTS ≤5-defined core in endovascular therapy patients, particularly within 6 hours after stroke onset.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".