Outcomes of Endovascular Therapy in Patients With Prestroke Mobility Impairment
Bibliographic record
Abstract
Background and Purpose: Patients with prestroke mobility impairment (PSMI) were excluded from endovascular clinical trials. There are limited data regarding safety and outcomes of endovascular thrombectomy in this population. We used a large, national data set (Get With The Guidelines–Stroke) to evaluate the safety and outcomes of endovascular thrombectomy in patients with PSMI. Methods: We included patients who underwent endovascular thrombectomy in the Get With The Guidelines–Stroke registry between 2015 and 2019. PSMI was defined as the inability to ambulate independently. Generalized estimating equations for logistic regression models were used to evaluate the association between PSMI and outcomes. Results: Of 56 762 patients treated with endovascular thrombectomy, 2919 (5.14%) had PSMI. PSMI was not associated with symptomatic intracranial hemorrhage (6.0% versus 5.4%; P=0.979). In-hospital death or discharge to hospice occurred in 32.3% of patients with PSMI versus 17.5% without PSMI (adjusted odds ratio, 1.45 [1.32–1.58]). Conclusions: While procedural adverse outcomes were no higher in patients with PSMI, further study is necessary to determine clinical benefit in this population.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".