Endovascular treatment versus medical management for basilar artery occlusion with low-to-moderate symptoms (National Institutes of Health Stroke Scale < 10)
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background: Patients with acute basilar artery occlusion (BAO) and low-to-moderate symptoms (National Institutes of Health Stroke Scale [NIHSS] < 10) are poorly represented in thrombectomy trials. Our objective is to compare thrombectomy and best medical management (BMT) in this population. Methods: We compared data of all consecutive patients presenting with an initial NIHSS < 10 and acute symptomatic BAO included in two registries. The main outcome was the proportion of patients achieving a 3-months favorable outcome (mRS 0-2 or equal to the pre-stroke value). Secondary outcomes included the proportion of patients with an excellent outcome (mRS 0-1 or equal to pre-stroke value), overall mRs distribution (shift analysis) and mortality. Effect sizes for thrombectomy versus BMT alone were calculated using binary or ordinal logistic regression model before after considering confounders using the inverse probability of treatment weighting (IPTW) propensity score method. Results: One hundred twenty-seven patients were included: sixty-four patients treated with thrombectomy (mean ± SD age: 63.4 ± 16.1) and sixty-three with BMT (mean ± SD age: 69.0 ± 14.3). There was no significant difference between groups for the rate of 3 month-favorable outcome or mortality. After propensity-score adjustment, thrombectomy was associated with a significantly higher chance of excellent outcome at 3 months (mRS 0-1 or equal to pre-stroke value; adjusted OR, 2.68; 95%CI, 1.04–6.90; p = 0.041). Conclusion: Our study suggests that thrombectomy in patients with low-to-moderate symptoms (NIHSS < 10) due to BAO does not improve the rate of favorable outcome but could lead to a higher chance of excellent outcome at 3 months. Trial Registration: ETIS Registry. http://www.clinicaltrials.govNCT03776877
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 it