Predictive value of CT angiography source image ASPECTS in patients with anterior circulation acute ischemic stroke after endovascular treatment: ultimate infarct size and clinical outcome
Bibliographic record
Abstract
Background and purpose The objective of this study was to investigate the predictive value of computed tomographic angiography (CTA) source image Alberta Stroke Program Early CT Score (ASPECTS) on clinical outcome and final infarction extent after endovascular treatment (EVT) in patients with acute ischemic stroke (AIS). M ethods All eligible patients from January 2014 to March 2018 undergoing EVT due to anterior circulation AIS were retrospectively reviewed. The baseline ASPECTS on initial noncontrast CT (NCCT) and the CTA source image were compared with the follow-up MR diffusion-weighted imaging (DWI) ASPECTS. Receiver operating characteristic (ROC) curve analysis was used to assess the predictive value of CTA ASPECTS for prediction of final infarct extent and good clinical outcome. Results Our sample included a total of 122 eligible patients (64 males, mean age 70 years) with a median baseline National Institute of Health Stroke Scale (NIHSS) score of 12. Baseline ASPECTS on the CTA source image correlated with follow-up MR DWI ASPECTS better than NCCT ASPECTS (P<0.001). ROC curve analysis revealed baseline CTA ASPECTS (area under the curve [AUC] =0.74, 95% CI: 0.65 to 0.83, P<0.001) can better predict favorable functional outcome than NCCT ASPECTS (AUC=0.64, 95% CI: 0.54 to 0.74, P=0.008). Baseline NIHSS score <15, CTA ASPECTS≥8, and successful recanalization were independent predictors of good clinical outcomes. Conclusion The ASPECTS on the CTA source image provides more information in the prediction of good clinical outcome and final infarction size than NCCT in patients with AIS treated with 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".