Abstract 289: Cognitive Outcomes in Symptomatic Intracranial Stenosis: A Post‐hoc SAMMPRIS Analysis of Stenting versus Aggressive Medical Management
Bibliographic record
Abstract
Introduction The impact of treatment modality on cognitive function is not well established. In this post‐hoc analysis of the SAMMPRIS trial, we compare cognitive outcomes in patients with symptomatic ICAD managed with percutaneous transluminal angiographic stenting to those treated with aggressive medical management. Methods Using the SAMMPRIS trial sample of 451 patients, we included patients who underwent successful symptomatic intracranial atherosclerotic stenosis (i.e. no periprocedural complications or stenting challenges) along with those those treated with aggressive medical management. Cognitive outcomes between the stenting and aggressive medical management arms were then assessed using the Montreal Cognitive Assessment (MoCA) at 30 days, 4 months, 12 months, and final follow‐up. Multivariate linear and logistic regression models were used to adjust for baseline MoCA score, age, sex, and vascular risk factors. Results Following exclusion for non‐successful stenting, we analyzed 270 patients (stenting: 122, aggressive medical management: 152). The stenting group exhibited significantly reduced odds of achieving MoCA ≥ 26 compared to the medical management group (OR 0.54, 95% CI 0.29 to 1.00, p=0.050), representing a 54% higher likelihood of reaching sub‐normal cognitive outcome. Despite higher baseline cognitive function in the stenting group (median MoCA 26 vs 25, p=0.019), no significant difference was observed in continuous MoCA scores between patients receiving stenting and medical management (OR ‐0.63, 95% CI ‐1.60 to 0.34, p=0.205). Conclusion Stenting was associated with decreased long‐term cognitive outcomes relative to symptomatic ICAD treated with aggressive medical therapy. By raising concern about potential cognitive harm from interventional management, these findings highlight the importance of including cognitive outcomes as a factor in treatment selection.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".