Temporal progression of functional independence after mechanical thrombectomy in acute vertebrobasilar artery occlusions
Bibliographic record
Abstract
BACKGROUND: Neurological recovery after endovascular treatment (EVT) for large vessel occlusion stroke often has diverse timelines. Understanding the temporal progression of functional independence after EVT, especially delayed functional independence (DFI) and highly delayed functional independence (HDFI), in patients who do not improve early is essential for prognostication and rehabilitation. We aimed to analyze the prevalence and predictors of DFI and HDFI after EVT in acute vertebrobasilar artery occlusions (VBAO). METHODS: Patients with VBAO who received EVT in China were retrospectively enrolled. Early functional independence (EFI) was defined as a modified Rankin Scale (mRS) score of 0-2 at discharge. The incidence and predictors of DFI (mRS score 0-2 at 90 days in non-EFI patients) and HDFI (mRS score 0-2 at 1 year in non-DFI patients) were analyzed. RESULTS: 2422 patients met the study criteria. EFI was observed in 20% (483) of patients. Among non-EFI patients, DFI was observed in 21% (395/1880). HDFI was observed in 13% (191/1439) of non-DFI patients. Younger age (P=0.006), lower pre-EVT National Institutes of Health Stroke Scale (NIHSS) score (P<0.001), higher posterior circulation-Alberta Stroke Program Early CT Score (PC-ASPECTS) (P=0.012), and absence of symptomatic intracranial hemorrhage (sICH) (P<0.001) were predictors of DFI. Predictors of HDFI were younger age (P<0.001) and lower pre-EVT NIHSS score (P<0.001). CONCLUSION: A considerable proportion of patients have DFI and HDFI. The independent predictors of DFI were younger age, lower pre-EVT NIHSS score, higher PC-ASPECTS, and absence of sICH. Predictors of HDFI included younger age and lower pre-EVT NIHSS score.
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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 | 0.001 |
| 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) | 0.001 | 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".