Delayed functional independence after thrombectomy: temporal characteristics and predictors
Bibliographic record
Abstract
BACKGROUND: Variability in early neurological improvement after endovascular thrombectomy (EVT) for large vessel occlusion (LVO) stroke is well documented. Understanding the temporal progression of functional independence after EVT, especially delayed functional independence in patients who do not experience early improvement, is essential for prognostication and rehabilitation. OBJECTIVE: To determine the incidence of early and delayed functional independence and identify associated predictors after EVT. METHODS: A retrospective analysis of prospectively collected data on patients undergoing EVT in the setting of anterior circulation LVO was performed. Demographic, clinical, radiological, treatment, and procedural information were analyzed. Incidence and predictors of early functional independence (EFI, modified Rankin Scale (mRS) score 0-2 at discharge) and delayed functional independence (DFI, mRS score 0-2 at 90 days in non-EFI patients) were analyzed. RESULTS: Three hundred and fifty-five patients met the study criteria. 55% were women and mean age was 71±15. Mean National Institutes of Health Stroke Scale (NIHSS) score was 17±6 and median Alberta Stroke Program Early CT Score was 9 (8-10). EFI was observed in 21% (73) of patients. Among non-EFI patients (282), DFI was observed in 30% (85) of patients. Shorter time to treatment (p=0.03), lower 24 hours NIHSS score (p<0.001), and smaller follow-up infarct volume (p=0.003) were independent predictors of EFI. Younger age (p=0.011), lower 24 hours NIHSS score (p=0.001), and absence of parenchymal hemorrhage (PH2; p=0.039) were independent predictors of DFI. CONCLUSION: Approximately one-fifth of patients experience EFI and one-third of non-early improvers experience DFI. Younger age, lower 24 hours NIHSS score, and absence of parenchymal hemorrhage were independent predictors of DFI among non-early improvers. Further studies are required to improve our understanding of DFI.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".