Predicting final infarct size and clinical outcomes in patients with acute ischemic stroke after endovascular thrombectomy using the Alberta Stroke Program early CT score on venous-phase CT
Bibliographic record
Abstract
Background The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a semi-quantitative tool for evaluating the extent and distribution of early ischemic changes. Purpose To assess the value of ASPECTS on non-contrast CT (NCCT), arterial-phase CT (APCT), or venous-phase CT (VPCT) in predicting the final infarct core (IC) on follow-up diffusion-weighted imaging (DWI) and the clinical outcomes of patients with acute ischemic stroke (AIS) after endovascular thrombectomy (EVT). Material and Methods In total, 120 patients with AIS who underwent EVT in our center were retrospectively enrolled. Correlations between CT-ASPECTS and follow-up DWI-ASPECTS were analyzed using Spearman's rank correlation coefficient. Mean differences and limit of agreement (LoA) between CT-ASPECTS and follow-up DWI-ASPECTS were assessed using the Bland–Altman plots. Multivariate logistic regression and receiver operating characteristic curve analyses were used to identify independent factors and evaluate their performances in predicting the clinical outcomes. Results VPCT-ASPECTS exhibited the highest correlation with follow-up DWI-ASPECTS (r = 0.846, P < 0.001), followed by APCT-ASPECTS (r = 0.613, P < 0.001) and NCCT-ASPECTS (r = 0.557, P < 0.001). The mean difference between VPCT-ASPECTS and follow-up DWI-ASPECTS was 0.0 (limit of agreement = −2.1 to 2.1). National Institute of Health Stroke Scale (NIHSS) scores at admission (NIHSS pre ) (odds ratio [OR]=1.162, 95% confidence interval [CI]=1.063–1.270; P = 0.001) and VPCT-ASPECTS (OR=0.728, 95% CI=0.535–0.991; P = 0.044) were the independent factors associated with clinical outcomes. The combined model integrating NIHSS pre and VPCT-ASPECTS exhibited an excellent performance in predicting good clinical outcomes (area under curve [AUC]=0.807; sensitivity=75.0%; specificity=72.3%). Conclusion VPCT-ASPECTS may be a promising imaging biomarker to predict the final IC and the clinical outcome of the patients with AIS after EVT.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".