Locked-in syndrome responding to endovascular treatment
Bibliographic record
Abstract
BACKGROUND: Locked-in syndrome (LiS) is a rare and devastating condition in patients with acute basilar artery occlusion. However, the benefits of endovascular treatment (EVT) for LiS remain unclear. OBJECTIVE: To assess the outcomes associated with EVT and identify the factors associated with outcomes of LiS. METHODS: We used the data of the Endovascular Treatment for Acute Basilar Artery Occlusion Study Registry (BASILAR) from 47 tertiary stroke centers in China. The included patients had LiS and received EVT or standard medical treatment (SMT) alone. The primary outcome was improvement in the modified Rankin Scale (mRS) score at 90 days. RESULTS: Among the 120 patients with LiS, 92 (76.7%) received EVT and 28 (23.3%) received SMT. Compared with SMT, EVT was associated with improved mRS score (common OR (cOR)=2.68 (95% CI 1.16 to 6.20); p=0.02) and decreased mortality (aOR=0.35 (95% CI 0.13 to 0.90); p=0.03). Moreover, the benefit of EVT for LiS was sustained for at least 1 year (p=0.008). Higher baseline posterior circulation Alberta Stroke Prognosis Early CT Score (pc-ASPECTS, aOR=2.04 (95% CI 1.34 to 3.10); p<0.001) and absence of pneumonia (aOR=0.26 (95% CI 0.08 to 0.90); p=0.03) were significantly associated with favorable functional outcome at 90 days in patients who received EVT, while lower pc-ASPECTS (aOR=0.52 (95% CI 0.36 to 0.76); p<0.001) was associated with increased 90-day mortality. CONCLUSIONS: This study found that EVT was associated with favorable functional outcomes and decreased mortality among patients with LiS. Baseline pc-ASPECTS and pneumonia were independent predictors of outcomes.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".