Abstract 68: Impaired Perfusion in Intracranial Atherosclerotic Disease Predicts Cognitive Outcomes
Bibliographic record
Abstract
Background: Poor collateral circulation and hypoperfusion may lead to recurrent stroke in intracranial atherosclerotic disease (ICAD). The role of perfusion in silent strokes and potentially insidious cognitive impairment in ICAD is unknown. We used evidence of impaired perfusion at angiography in SAMMPRIS to predict subsequent cognitive changes. Methods: Angiography at enrollment in the SAMMPRIS trial was independently evaluated, blind to clinical data and cognitive testing. Antegrade flow in the symptomatic arterial territory and corresponding collateral flow were scored. Impaired perfusion was defined by poor antegrade and poor collateral flow. Serial testing with the Montreal Cognitive Assessment (MoCA) was done in subjects without aphasia or neglect at baseline, 4 mo, 12 mo and closeout, or until subjects had a clinical stroke endpoint. Results: 207 subjects (median age 61, range 33-81 years; 37% women) had baseline MoCA scores with angiography data on territorial perfusion. Baseline MoCA scores (mean 24.2±4.1) were similar between categories of antegrade flow and collateral circulation. Impaired perfusion was noted in 33/207 (16%). Serial MoCA revealed that changes in cognition over time were different at 4 mo, 12 mo and closeout based on the presence of impaired perfusion at baseline (p<0.001). After more modest (mean MoCA change = 0.5 increase from baseline, p=0.80) early improved cognitive function at 4 mo, those with impaired perfusion had cognitive decline at 12 mo (mean MoCA change, p<0.01) unlike the continued improvement in other subjects. Cognitive changes in those with impaired perfusion were associated with a higher frequency of subsequent stroke in the territory. Conclusions: Impaired perfusion in the symptomatic arterial territory of ICAD predicts cognitive outcomes that may precede recurrent ischemia. Future studies may define the role of noninvasive perfusion imaging in ICAD to predict cognitive trajectories and recurrent stroke.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".