Safety and efficacy of aneurysms treated with endovascular devices (The SEATED Study)
Bibliographic record
Abstract
OBJECTIVES: To create a nationwide consortium to gather all the data related to advanced devices used for aneurysm treatment and conduct pragmatic real-world studies despite the variations among all centres. The strength of this study will be in pooling data of the less commonly used recent devices where there is less evidence. The study will be prospective and retrospective where the initial recruitment figure is expected to be around 5000 patients. METHODS: To assess how endovascular techniques vary among different UK centres, we illustrate the results of initial surveys that were sent to those centres across the United Kingdom using a single device, the pipeline embolization device with vantage technology (PEDV). RESULTS: Although the centres were using the same device, the antiplatelet protocol varied from one centre to another as well as follow-up protocols according to the local experience, patient clinical status or even according to the adjuncts uses (e.g., adjunct coiling). CONCLUSIONS: The illustrated results show that although the centres were using the same device, the antiplatelet protocol varied from one centre to another. Also, follow-up protocols vary from one centre to another according to the local experience, patient clinical status or even according to the adjuncts used (e.g., adjunct coiling). This exemplar serves to illustrate that a nationwide consortium can pool and analyse data of any recent endovascular device. ADVANCES IN KNOWLEDGE: Obtaining nationwide data regarding safety, efficacy as well as risk factors for aneurysm recurrence when using recent devices. This study will add valuable data regarding the less commonly used recent devices where there is less evidence.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".