Cognition, Olfaction and Uric Acid in Early de novo Parkinson’s Disease
Bibliographic record
Abstract
Uric acid is a risk factor of cardiovascular disease, as well as a major natural antioxidant, prohibiting the occurrence of cellular damage. The relation between uric acid and cognitive decline, in which both vascular mechanisms and oxidative stress are thought to play a role, is unknown. Therefore we assessed the relation between serum uric acid levels and the risk of subsequent dementia in a prospective population-based cohort study among 4618 participants aged 55 years and over. Additionally, we investigated the relation between serum uric acid and cognitive function later in life (on average 11.1 years later) in a subsample of 1724 participants who remained free of dementia during follow-up. All analyses were adjusted for age, sex and cardiovascular risk factors. Our data showed that only after correcting for several cardiovascular risk factors, higher serum uric acid levels were associated with a decreased risk of dementia (HR, adjusted for age, sex and cardiovascular risk factors, 0.89 [95% confidence interval (CI) 0.80–0.99] per standard deviation (SD) increase in uric acid). In participants who remained free of dementia, higher serum uric acid levels at baseline were associated with better cognitive function later in life, for all cognitive domains that were assessed [adjusted difference in Z-score (95% CI) per SD increase in uric acid 0.04 (0.00–0.07) for global cognitive function; 0.02 (−0.02 to 0.06) for executive function; and 0.06 (0.02–0.11) for memory function], but again only after correcting for cardiovascular risk factors. We conclude that notwithstanding the associated increased risk of cardiovascular disease, higher levels of uric acid are associated with a decreased risk of dementia and better cognitive function later in life.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".