A Simplified One-Size-Fits-All Approach to Carotid Stenting
Bibliographic record
Abstract
BACKGROUND: Carotid artery stenosis causes up to 20% of ischemic strokes. Stenting is used as an alternative to endarterectomy in symptomatic patients. Each commercially available stent offers numerous stent diameters/lengths. Most centers thus carefully match each individual stenosis to a specific stent length/diameter stent size. However, this process can be time-consuming and costly while the relative benefit of a custom stent sizing versus one-size-fits-all approach has not been well evaluated yet. We hypothesized that a 'one-size-fits-all' default approach to carotid stenting results in comparable results to a customized approach. METHODS: We conducted a descriptive retrospective cohort study on 154 patients who presented to our academic carotid revascularization clinic with symptomatic carotid artery stenosis who underwent carotid artery stenting for peri- and postprocedural carotid artery stenting complications. The primary outcomes were periprocedural (within 24 hours of the procedure) or postprocedural (within 30 days of the procedure) TIA, stroke, or death. The secondary outcome was the estimated degree of stenosis on follow-up ultrasound performed within 6 months of the procedure. RESULTS: The complication rate within the first 24 hours was 4.5% while that during the first 30 days postprocedure was 6.5%. Age over 80 and degree of stenosis on postprocedural cerebral angiogram were associated with an increased risk of complications. Severe restenosis was reported in 16.8% of patients within 6 months postprocedure. CONCLUSION: Our study suggests that using a simplified, one-size-fits-all, approach to carotid stenting results in safe and effective outcomes, suggesting an alternative to simplify a complex medical procedure.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".