Abstract WP127: Effects of EDAS Revascularization and Intensive Medical Management on the Cognitive Function of Patients With Intracranial Atherosclerosis
Bibliographic record
Abstract
Introduction: Cognitive decline after transient ischemic attacks (TIA) or stroke is common. Evaluation with the Montreal Cognitive Assessment (MoCA) tool has shown a decrease in cognitive scores in more than 30% of patients at 1 year. We hypothesize that indirect revascularization with EDAS plus intensive medical management (IMM) would decrease the rate of decline. Methods: This is a prospective study of EDAS plus IMM in symptomatic patients with intracranial arterial stenosis of more than 70%. Patients had MoCA evaluations at baseline, 1 month, 6 months, and 12 months after EDAS. Differences in MoCA at baseline and follow-up were compared using mixed model repeated measures ANOVA. Results: Thirty-one patients with no aphasia or neglect were included. Mean age was 48.3 +/- 16.6 years. Twenty-one were females (70%). The mean MoCA scores at baseline and 12-months were 23.6 +/- 4.3 and 25.5 +/- 4.1, respectively. MoCA ≥ 1 improvement was seen in 78.9% at 12 months. However, differences in MoCA scores at these time points did not reach statistical significance (p= 0.49, Fig. 1). Only 9% of patients had a decline of ≥2 MoCA points at 12 months. These results are comparable to the twelve month MoCA data from the SAMMPRIS trial, which showed a mean MoCA for IMM of 25.4 +/- 3.73 and for percutaneous angioplasty and stenting (PTAS) of 25.6 +/- 3.89. The rate of decline of MoCA scores after EDAS plus IMM was significantly less than the reported natural history after TIA or strokes outside the SAMMPRIS trial (9% vs. 30%, p=0.03). Conclusion: Compared to historical data, the decline in MoCA scores after TIA and stroke was lower in patients treated with EDAS plus maximum medical therapy and has similar effects to those reported in the SAMMPRIS IMM and PTAS groups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".