The impact of postoperative aspirin in patients undergoing Woven EndoBridge: a multicenter, institutional, propensity score-matched analysis
Bibliographic record
Abstract
BACKGROUND: The Woven EndoBridge (WEB) device is frequently used for the treatment of intracranial aneurysms. Postoperative management, including the use of aspirin, varies among clinicians and institutions, but its impact on the outcomes of the WEB has not been thoroughly investigated. METHODS: This was a retrospective, multicenter study involving 30 academic institutions in North America, South America, and Europe. Data from 1492 patients treated with the WEB device were included. Patients were categorized into two groups based on their postoperative use of aspirin (aspirin group: n=1124, non-aspirin group: n=368). Data points included patient demographics, aneurysm characteristics, procedural details, complications, and angiographic and functional outcomes. Propensity score matching (PSM) was applied to balance variables between the two groups. RESULTS: Prior to PSM, the aspirin group exhibited significantly higher rates of modified Rankin scale (mRS) mRS 0-1 and mRS 0-2 (89.8% vs 73.4% and 94.1% vs 79.8%, p<0.001), lower rates of mortality (1.6% vs 8.6%, p<0.001), and higher major compaction rates (13.4% vs 7%, p<0.001). Post-PSM, the aspirin group showed significantly higher rates of retreatment (p=0.026) and major compaction (p=0.037) while maintaining its higher rates of good functional outcomes and lower mortality rates. In the multivariable regression, aspirin was associated with higher rates of mRS 0-1 (OR 2.166; 95% CI 1.16 to 4, p=0.016) and mRS 0-2 (OR 2.817; 95% CI 1.36 to 5.88, p=0.005) and lower rates of mortality (OR 0.228; 95% CI 0.06 to 0.83, p=0.025). However, it was associated with higher rates of retreatment (OR 2.471; 95% CI 1.11 to 5.51, p=0.027). CONCLUSIONS: Aspirin use post-WEB treatment may lead to better functional outcomes and lower mortality but with higher retreatment rates. These insights are crucial for postoperative management after WEB procedures, but further studies are necessary for validation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".