Optimal thresholds to predict long-term outcome after complete endovascular recanalization in acute anterior ischemic stroke
Bibliographic record
Abstract
BACKGROUND: Despite complete endovascular recanalization, a significant percentage of patients with acute anterior stroke do not achieve a good clinical outcome. We analyzed optimal thresholds of relevant parameters to discern functional independence after successful endovascular recanalization and test their predictive performance. METHODS: Patients with acute anterior ischemic stroke undergoing endovascular treatment between April 2015 and November 2019 were retrospectively analyzed. Only patients with premorbid modified Rankin Scale (mRS) score <3 and complete recanalization (modified Thrombolysis In Cerebral Infarction 2c/3) were included. Optimal thresholds of the most important variables predicting functional independence (mRS 0-2 after 90 days) were calculated using receiver operating characteristic curves and their predictive performance was tested in an independent dataset using machine learning algorithms. RESULTS: Overall, 371 patients met the inclusion criteria. Optimal thresholds for the overall most important variables to predict functional independence were (1) National Institutes of Health Stroke Scale (NIHSS) score ≤5 after 24 hours (area under the curve (AUC) 0.88 (95% CI 0.84 to 0.92)); (2) Alberta Stroke Program Early CT Score (ASPECTS) ≥7 on follow-up CT (AUC 0.72 (95% CI 0.68 to 0.77)); and (3) change in NIHSS score ≥8 after 24 hours (AUC 0.70 (95% CI 0.65 to 0.74)). The performance of these thresholds to predict a good outcome using machine learning in the independent dataset was evaluated for (1) NIHSS score ≤5 after 24 hours (AUC 0.76 (95% CI 0.71 to 0.81)); (2) follow-up ASPECTS ≥7 (AUC 0.64 (95% CI 0.58 to 0.70)); (3) change in NIHSS score ≥8 after 24 hours (AUC 0.61 (95% CI 0.55 to 0.67)); and (4) the combination of all three parameters (AUC 0.84 (95% CI 0.80 to 0.88)). CONCLUSIONS: After complete recanalization in acute anterior circulation ischemic stroke, a good long-term outcome could be accurately predicted reaching NIHSS score ≤5 after 24 hours.
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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) | 0.001 | 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 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".