Abstract 75: Association Between Speed From Hospital Arrival To Endovascular Thrombectomy And Health-Related Quality Of Life In Patients With Acute Ischemic Stroke
Bibliographic record
Abstract
Background: Faster treatment with endovascular thrombectomy (EVT) in patients with acute ischemic stroke is associated with better functional outcome at 90 days on the modified Rankin Scale. Whether speed of treatment is associated with improvements in patient-reported outcomes such as health-related quality of life is not well known. Methods: We used data from the ESCAPE-NA1 randomized trial which tested the effect of nerinetide in patients with large vessel occlusion undergoing EVT. We calculated EuroQol 5-dimension 5-level (EQ-5D-5L) index scores at 90 days using country-specific value sets. Using quantile regression, we evaluated the association between time from hospital arrival to EVT groin puncture (door-to-puncture) and EQ-5D-5L index score and visual analogue scale (EQ-VAS), adjusting for age, sex, stroke severity, ASPECTS, alteplase treatment, and nerinetide treatment. Using logistic regression, we determined the association between door-to-puncture time and reporting no/slight symptoms in each domain (mobility, self-care, usual activities, pain, and anxiety/depression) or all domains concurrently. Results: There were 1045 patients receiving EVT with EQ-5D values at 90 days. Median door-to-puncture time was 59 minutes (interquartile range 42-84). There was a strong association between faster door-to-puncture time and higher EQ-5D index score and EQ-VAS (Figure A-C). Faster time was also associated with higher probability of no/slight problems in each of five domains and all domains concurrently, with approximately 10% increase in probability for each hour of faster treatment (Figure D-I). Conclusion: Faster door-to-puncture EVT time is strongly associated with greater health-related quality of life across all domains in patients with large vessel occlusion. These results support the beneficial impact of speed of EVT on patient-reported outcomes and encourage efforts to improve quality of life in patients by optimizing workflows.
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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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".