Novel Risk Score to Predict Poor Outcome After Endovascular Treatment in Anterior Circulation Occlusive Acute Ischemic Stroke
Bibliographic record
Abstract
Background We aimed to develop and validate a prognostic score to predict outcomes after endovascular treatment in acute ischemic stroke. Methods The prognostic score was developed based on the ACTUAL (Endovascular Treatment for Acute Anterior Circulation Ischemic Stroke) registry. The validation cohort was derived from the Captor trial. Independent predictors of poor outcome after endovascular treatment were obtained from the least absolute shrinkage and selection operator regression and multivariable logistic regression. Corresponding regression coefficients were used to generate point scoring system. The area under the receiver operating characteristic curve and the Hosmer–Lemeshow goodness‐of‐fit test were used to assess model discrimination and calibration. The predictive properties of the developed prognostic score were validated and the discriminative power was compared with other validated tools. Results A 17‐point Age, Collateral Status, Blood glucose, Alberta Stroke Program Early Computed Tomography Score, and National Institutes of Health Stroke Scale score scale was developed from the set of independent predictors, including age, admission National Institutes of Health Stroke Scale score, Alberta Stroke Program Early Computed Tomography Score on initial computed tomography scan, blood glucose, and collateral status. The scale showed good discrimination in the derivation cohort (area under the receiver operating characteristic curve, 0.79 [95% CI, 0.75–0.82]) and validation cohorts (area under the receiver operating characteristic curve, 0.77 [95% CI, 0.70–0.84]). The scale was well calibrated (Hosmer–Lemeshow test) in the derivation cohort ( P =0.57) and validation cohort ( P =0.75). Conclusions The Age, Collateral Status, Blood glucose, Alberta Stroke Program Early Computed Tomography score, and National Institutes of Health Stroke Scale score scale is a valid tool for predicting outcomes and may be useful for endovascular stroke treatment in anterior circulation large vessel occlusions.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".