Lower DWI-ASPECTS Score in Cortical Regions Predicts Unfavorable Outcome after Successful Thrombectomy
Bibliographic record
Abstract
Abstract Background Mechanical thrombectomy has been established as an effective treatment for acute ischemic stroke (AIS) caused by large vessel occlusion (LVO). However, the factors predicting poor outcomes despite successful reperfusion after thrombectomy remain unclear. Methods This study included 50 patients who achieved successful reperfusion after mechanical thrombectomy between January 2014 and March 2021. The diffusion-weighted imaging (DWI) Alberta Stroke Program Early Computed Tomography Score (ASPECTS) was stratified into deep (dDWI-ASPECTS) and cortical (cDWI-ASPECTS) components. Baseline clinical characteristics and procedural factors were statistically analyzed to identify variables associated with unfavorable outcomes, defined as a modified Rankin scale score of 3 to 6. Results Seventeen patients (34%) achieved favorable outcomes, while 33 (66%) had unfavorable outcomes. The cDWI-ASPECTS were significantly higher in the favorable outcome group compared with the unfavorable outcome group (p = 0.01), whereas no significant differences were observed in the dDWI-ASPECTS. Multivariate analysis identified older age (p < 0.01; odds ratio [OR]: 1.15; 95% confidence interval [CI]: 1.04–1.27), lower baseline cDWI-ASPECTS (p < 0.01; OR: 2.71; 95% CI: 1.30–5.56), and higher baseline National Institutes of Health Stroke Scale (NIHSS) scores (p = 0.03; OR: 1.21; 95% CI: 1.02–1.44) as independent predictors of unfavorable outcomes. Conclusion A lower baseline cDWI-ASPECTS score serves as a predictive factor for unfavorable outcomes following successful thrombectomy, particularly in older AIS-LVO patients with higher baseline NIHSS scores.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".