Incidence and predictors of Woven EndoBridge (WEB) shape modification following treatment of intracranial aneurysms in a large multicenter study
Bibliographic record
Abstract
The Woven EndoBridge (WEB) device is FDA-approved for the treatment of bifurcation aneurysms. Despite its wide popularity, it has been under scrutiny for its association with potential aneurysm recanalization and retreatment due to device shape modification. This study aims to analyze the shape modification rate of WEB devices and identify factors associated with this phenomenon, as well as its correlation with aneurysm retreatment. We conducted a retrospective review of the WorldWide WEB Consortium database, including adult patients treated for intracranial aneurysms with the WEB device. We assessed aneurysm occlusion using the WEB Occlusion Scale and defined WEB shape modification as a percentage reduction in the distance between two WEB markers. Logistic regression and Cox proportional hazards models were utilized to evaluate predictors of shape modification and retreatment. Kaplan-Meier curves were used to estimate the time-dependent probability of no or minor shape modification. A total of 405 patients were analyzed, with minor and major shape modification occurring in 31.4% and 10.1% of cases, respectively. Major shape modification was associated with lower rates of adequate occlusion (70.7%) compared to no or minor shape modification (86.6%) and a higher rate of retreatment (26.8% vs. 8.1%). Predictors of major shape modification included the presence of daughter sac, bifurcation aneurysms, absence of immediate flow stagnation, and a WEB width minus aneurysm width ratio ≤ 0.5. The probability of no or minor shape modification declined within the first 25 months and stabilized thereafter. WEB device shape modification is a significant predictor of aneurysm occlusion efficacy and retreatment. Recognizing the factors influencing shape modification can guide treatment decisions and follow-up protocols to improve patient outcomes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".