PO258 Pet imaging of cerebral amyloid load and cognition in tia and minor stroke
Bibliographic record
Abstract
Background Stroke is associated with a doubling in dementia risk but the contribution of neurodegenerative pathology to vascular cognitive impairment (VCI) is uncertain. Previous studies of amyloid PET in VCI are conflicting, and may be confounded by lesional cognitive effects of major stroke. We therefore studied amyloid load versus VCI after TIA/minor stroke. Methods Consecutive consenting TIA/minor stroke patients (Oxford Vascular Study) underwent 18F-Flutemetamol-PET imaging. Cognitive function was defined as normal (MoCA ≥25) or VCI (MoCA <25,MMSE ≥20). 18F-Flutemetamol-binding (automated analysis of regional/global standardised uptake value ratios – SUVr) was defined as positive as SUVr >2 SD relative to pons in two cortical regions or SUVr >3 SD in one region. Results Among 19 TIA/stroke patients who underwent 18F-PET (mean age/SD=78.0/5.4, 50%male), 3 (15.8%) were amyloid positive. Of 9 patients with normal cognition (mean age/SD/MOCA=76.3/5.3/26.9) two were amyloid-positive. Of 10 with VCI (mean age/SD/MOCA=79.3/5.4/20.4), one was positive. There was no significant correlation between MoCA/recall subscore and global SUVr in either group. One ‘positive control’ with Alzheimer’s dementia showed the expected high global uptake. Conclusion Amyloid load was low in cognitively normal and impaired TIA/minor stroke patients, confirming the one previous study of 18F-PET. Follow-up studies are required to determine whether amyloid pattern predicts cognitive decline.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".