Sex differences in endovascular thrombectomy: A comparative analysis of baseline characteristics, time metrics, interventional radiology techniques, and clinical outcomes
Bibliographic record
Abstract
PURPOSE: To investigate differences in the baseline risk factors, stroke characteristics, procedural techniques, workflow processing times, and clinical outcomes between male and female endovascular thrombectomy (EVT) patients. MATERIALS AND METHODS: This retrospective cohort study analyzed medical records of adult patients with acute ischemic stroke treated with EVT at a comprehensive stroke center from February 1, 2015, to May 31, 2022. The primary outcome was functional neurological disability, scored using the modified Rankin Scale (mRS) at 90 days. Secondary outcomes included procedural workflow time delays, successful reperfusion rate, and other EVT technical aspects. Categorical data was evaluated through Fisher's exact test and continuous data through Mann-Whitney U tests. RESULTS: A total of 943 patients consisting of 480 male and 463 female patients were included. Female patients were more likely to be older (p < 0.0001), and present with atrial fibrillation (p = 0.0089), and cardioembolic strokes (p < 0.0001). Male patients demonstrated higher rates of smoking (p = 0.030), coronary artery disease (p = 0.0004), large artery atherosclerotic strokes (p < 0.0001), and posterior circulation occlusion (p = 0.03). Median mRS scores at 90 days were similar between groups (mRS 1, p = 0.15). There were no differences in EVT technique and workflow time metrics between groups, however, female patients were more likely to present during business versus on-call hours (44.1% vs 37.3%, p = 0.040). CONCLUSIONS: Female patients undergoing EVT demonstrated no difference in EVT outcomes, and were more likely to present during business hours. Female patients were older, and were more likely to present with atrial fibrillation, and cardioembolic strokes.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".