Impact of WASID and Wingspan on the frequency of intracranial angioplasty and stenting at a high volume tertiary care hospital
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The impact of the Warfarin and Aspirin for Symptomatic Intracranial Disease (WASID) data is described in combination with the commercial release of the Wingspan stenting system on the frequency of neurointervention for the treatment of symptomatic intracranial atherosclerotic disease (ICAD) in a tertiary care center. METHODS: Endovascular case logs were reviewed from April 2004 to July 2007. The total number of intracranial neurointerventions and the number of neurointerventions (percutaneous transluminal angioplasty alone (PTA) or with stenting (PTAS)) performed for symptomatic ICAD were calculated. The time period evaluated was divided into two equal 19.5-month epochs representing the time periods before and after the availability of the Wingspan system. RESULTS: The frequency of neurointerventions for ICAD increased by 763%, from seven of 354 total cases (2%) to 56 of 367 total cases (15.3%) (p<0.001) after the Wingspan system became available. The increase in intracranial PTAS volume occurred immediately and was stable throughout the "Wingspan era". CONCLUSIONS: The publication of the WASID trial results combined with the availability of the Wingspan stent system led to a marked increase in the frequency of neurointervention for symptomatic ICAD at our institution. The adoption of this technology occurred without direct evidence that PTAS with Wingspan is superior to traditional medical therapy. These findings underscore the need for a randomized trial of stenting and medical therapy for the treatment of this disease process.
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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".