Delayed phase computed tomography angiography ASPECTS predicts clinical outcome and final infarct volume
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Non-contrast computed tomography (NCCT) Alberta Stroke Program Early CT Score (ASPECTS) and assessment of collateral flow with multiphase computed tomography angiography (CTA) have been investigated as predictors of clinical outcome in patients with acute ischemic stroke. This study assessed the value of multiphase CTA ASPECTS in predicting final infarction core and clinical outcome in patients undergoing endovascular treatment of acute ischemic stroke. METHODS: We retrospectively studied consecutive patients who underwent multiphase CTA prior to endovascular treatment of acute stroke due to anterior circulation large artery occlusion. Multiphase CTA and final diffusion-weighted imaging (DWI) scans were evaluated by two independent observers for NCCT ASPECTS, acute phase CTA (CTA-AP) ASPECTS, delayed phase CTA (CTA-DP) ASPECTS, and final DWI ASPECTS. Modified Rankin Scale score ≤2 at 3 months was considered a favorable outcome. RESULTS: A total of 74 patients were analyzed. We found that CTA-DP ASPECTS (r = 0.82; 95% CI, 0.73-0.91; p < 0.001) correlated with final DWI ASPECTS better than NCCT ASPECTS (r = 0.49; 95% CI, 0.39-0.59) and CTA-AP ASPECTS (r = 0.71; 95% CI, 0.64-0.78). Interobserver agreement was higher for CTA-DP ASPECTS (k = 0.84). Good CTA-DP ASPECTS was an independent predictor of favorable outcome (odds ratio, 8.71; 95% CI, 3.71-17.3; p < 0.001). CONCLUSION: CTA-DP ASPECTS is a reliable predictor of final infarction core and neurological outcome.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".