Abstract 007: Device‐related Technical Complications with Flow Diversion of Intracranial Aneurysms: A Systematic Review and Meta‐analysis
Bibliographic record
Abstract
Introduction Flow diverters (FD) have become a revolutionary approach in the endovascular treatment of intracranial aneurysms (IAs), supplanting traditional methods (1). Despite their demonstrated efficacy and safety, unforeseeable device‐related technical complications, such as fish‐mouthing, device braid narrowing, deformation, ovalization, and collapsing have been reported during implantation and follow‐up (2,3,4). However, the definitions and reporting of these complications remain inconsistent. We conducted a systematic review and meta‐analysis to assess overall device‐related technical complication rates associated with flow diversion and provide an overview of the current reported definitions. Methods We searched six databases up to April 4th, 2023, and included studies that reported device‐related technical complications related to FD treatment for IAs. We considered five main outcome measures as device‐related technical complications: (1) fish‐mouthing, (2) device braid collapsing, (3) device braid narrowing, (4) device braid deformation, and (5) device braid ovalization. The data from these studies were pooled using a random‐effects model. Results We included 48 studies involving 3,572 patients and 3,939 aneurysms. Among them, 14 studies (39%) provided definitions for fish‐mouthing. However, none of the included studies offered specific definitions for device braid collapsing, narrowing, or deformation, despite reporting rates for these complications in five, six, and three studies, respectively. The pooled rates for device‐related technical complications were as follows: 3% (95% CI 2 – 4%; I2 = 27%) for fish‐mouthing, 1% (95% CI 0 – 3%; I2 = 0%) for collapsing, 7% (95% CI 2 – 20%; I2 = 85%) for narrowing, and 1% (95% CI 1 – 4%; I2 = 0%) for deformation. Device braid ovalization data were not available. Conclusion The findings of this study suggest that FD treatment for IAs generally exhibits low rates of fish‐mouthing, device braid narrowing, collapsing, and deformation. However, the lack of standardized definitions hinders the ability to objectively compare device outcomes, emphasizing the need for uniform device‐related complication definitions in future prospective studies on FD.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".