Abstract P521: Effect of Endovascular Thrombectomy on Health-Related Quality of Life Among Patients With Acute Ischemic Stroke and Large Vessel Occlusion in the Escape Trial
Bibliographic record
Abstract
Background: Endovascular thrombectomy (EVT) improves 90-day disability in patients following acute ischemic stroke due to large vessel occlusion. However, the effect of EVT on health-related quality of life and specific functional domains, and whether this effect differs by age or sex is less studied. Methods: We used data from the ESCAPE randomized controlled trial to obtain EuroQol-5D-3L (EQ-5D) at 90 days after acute stroke in patients randomized to EVT or standard care. Death was assigned an index value of 0 for EQ-5D. We used quantile regression to evaluate the association between EVT and EQ-5D index scores, and logistic regression for the association between EVT and symptom-free status among 90-day survivors for each EQ-5D dimension (self-care, usual activities, mobility, pain/discomfort, and anxiety/depression), assessing for modification by age or sex and adjusting for baseline factors including stroke severity, affected hemisphere, and receipt of alteplase. Results: There were 165 patients randomized to EVT and 150 patients randomized to control. Median EQ-5D was significantly higher for those who received EVT (0.80 versus 0.60; p<0.001). There was evidence of modification by age with older age associated with greater improvements in EQ-5D with EVT (Figure). Those receiving EVT had higher odds of symptom-free status in self-care, usual activities, mobility for those aged 60-79, and pain/discomfort for women, with no association with anxiety/depression (Table). Conclusions: EVT substantially improves health-related quality of life, with relatively greater impact in older individuals and observed benefit across multiple dimensions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".