Neurological improvement predicts clinical outcome after acute basilar artery stroke thrombectomy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Mechanical thrombectomy (MT) is the standard of care for patients with anterior circulation large vessel occlusion. Early neurological improvement (ENI), defined as a reduction of ≥ 8 on the National Institutes of Health Stroke Scale (NIHSS) compared with baseline score, or an NIHSS score of 0 or 1 at 24 h after MT, is a strong predictor of 3-month favorable outcome in such patients. The impact of ENI after MT in stroke patients with basilar artery occlusion (BAO) on 3-month outcome is not clear. We aimed to study the effects of ENI in patients with BAO. METHODS: We performed a retrospective analysis of a multicenter prospective cohort of all consecutive stroke patients with BAO who underwent MT. We compared clinical outcomes between BAO patient groups according to ENI status. Multivariate analyses were performed to determine the impact of ENI on favorable 90-day outcome (modified Rankin scale score 0-3) and to report factors contributing to ENI. RESULTS: A total of 237 patients were included. ENI was observed in 70 patients (30%). Outcomes were significantly better in ENI-positive patients, with 84% achieving favorable outcome (mRS score 0-3) at 3 months versus 30% for ENI-negative patients (P < 0.0001). In multivariate analysis, ENI was an independent predictive factor associated with higher rates of favorable outcome {odds ratio (OR) 18.12 [95% confidence interval (CI) 3.95-83.10]; P = 0.0001}. Higher number of passes [OR 0.62 (95% CI 0.43-0.89); P = 0.010] and need for stenting [OR 0.27 (95% CI 0.07-0.95); P = 0.041] were negatively associated with ENI. CONCLUSION: Early neurological improvement on day 1 following MT for BAO is a strong independent predictor of a favorable 3-month clinical outcome.
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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 | 0.000 | 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 | 0.002 |
| 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".