Relationships between Serum Lipid, Uric Acid Levels and Mild Cognitive Impairment in Parkinson's Disease and Multiple System Atrophy
Bibliographic record
Abstract
Background: Mild cognitive impairment is one of the non-motor symptoms in Parkinson's disease (PD) and multiple system atrophy (MSA). Few studies have previously been conducted on the correlation between serum uric acid (SUA) and lipid levels and mild cognitive impairment in PD and MSA. Methods: Participants included 149 patients with PD and 99 patients with MSA. The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to evaluate cognitive function. Evaluations were conducted on SUA and lipid levels, which included triglyceride, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and total cholesterol (TC). Results: Patients with PD and MSA diagnosed with mild cognitive impairment demonstrated multiple cognitive domain impairment when compared with patients with normal cognition. Attentional impairment was more pronounced in patients with MSA when compared with PD (p = 0.001). In PD, the risk of mild cognitive impairment was lower in the highest quartiles and secondary quartile of SUA than in the lowest quartiles (odds ratio [OR] = 0.281, 95% confidence intervals [CI]: 0.097–0.810, p = 0.019; and OR = 0.317, 95% CI: 0.110–0.911, p = 0.033). In MSA, the risk of mild cognitive impairment was lower in the third and highest quartile of SUA than in the lowest quartile (OR = 0.233, 95% CI: 0.063–0.868, p = 0.030; and OR = 0.218, 95% CI: 0.058–0.816, p = 0.024). In patients with PD, the MoCA scores were negatively correlated with TC levels (r = –0.226, p = 0.006) and positively correlated with SUA levels (r = 0.206, p = 0.012). In MSA, the MoCA scores were positively correlated with SUA levels (r = 0.353, p = 0.001). Conclusions: Lower SUA levels and higher TC levels are a possible risk factor for the risk and severity of mild cognitive impairment in PD. Lower SUA levels are a possible risk factor for the risk and severity of mild cognitive impairment in MSA.
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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 | 0.003 |
| 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".