Overview of Different Flow Diverters and Flow Dynamics
Bibliographic record
Abstract
Over the past decade, flow diverter technology for endocranial aneurysms has seen rapid evolution, with the development of new devices quickly outpacing the clinical evidence base. However, flow diversion has not yet been directly compared to surgical aneurysm clipping or other endovascular procedures. The oldest and most well-studied device is the Pipeline Embolization Device (PED; Medtronic), recently transitioned to the Pipeline Flex (Medtronic), which still has sparse data regarding outcomes. To date, other flow diverting devices have not been shown to outperform the PED, although information comes primarily from retrospective studies with short follow-up, which are not always comparable. Because of this lack of high-quality outcome data, no reliable recommendations can be made for choosing among flow diversion devices yet. Moreover, the decision to proceed with flow diversion should be individualized to each patient. In this work, we wish to provide a comprehensive overview of the technical specifications of all flow diverter devices currently available, accompanied by a succinct description of the evidence base surrounding each device.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".