Progression of cognitive impairment in Parkinson’s disease correlates with uric acid concentration
Bibliographic record
Abstract
Introduction This study assessed the relationship between the progression of Parkinson’s disease (PD) with cognitive impairment and changes in serum uric acid (UA) and homocysteine (Hcy) concentrations and explored the factors influencing PD with cognitive impairment. Methods The study randomly selected 74 patients with PD and evaluated their cognitive function using the Montreal Cognitive Assessment Scale (MoCA). Patients with PD were divided into two subgroups: those with and without cognitive impairment. PD severity was evaluated and graded using the Hoehn and Yahr (H–Y) scale. Another 60 middle-aged and older individuals without PD during the same period were selected as a control group. Blood UA and Hcy concentrations in each group were measured to assess the relationship between PD, cognitive impairment, and changes in UA and Hcy concentrations. Results The PD group with cognitive impairment had a lower UA concentration and higher Hcy concentration. The UA concentration was significantly higher in the early PD stages than in the middle and late stages (P<0.05). A significant negative relationship between MoCA scores and serum UA levels was found in patients with PD, whereas a positive relationship existed between MoCA scores and serum Hcy concentrations. Regression analysis showed that a higher UA concentration was an independent protective factor for PD with cognitive impairment, while a higher Hcy concentration was a risk factor (P<0.05). A serum UA concentration of 212.9 mmol/L and Hcy concentration of 13.35 mmol/L could distinguish between patients with PD with or without cognitive impairment with a sensitivity of 93.2% and specificity of 43.3%. Conclusion PD and cognitive impairment were associated with a decrease in UA concentration; the later the H–Y stage was, the lower the UA concentration was. The increase in Hcy concentration was related to PD and its cognitive impairment, whereas it is not significantly correlated with PD progression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".