Influence of baseline cognitive function on risk of prodromal Parkinson's disease in Chinese adults aged 55 and older: A prospective cohort study
Bibliographic record
Abstract
BackgroundChanges in cognitive function exist before the onset of clinical Parkinson's disease. However, studies on association between cognitive function and prodromal Parkinson's disease (pPD) are limited.ObjectiveTo estimate probability of pPD and assess its association with global and domain cognitive function in Chinese elders.MethodsData were drawn from the Community-based Cohort Study on Nervous System Disease 2018 (baseline) and 2020 (follow-up). We selected 3911 residents aged 55 and above who participated the two waves, without Alzheimer's disease and Parkinson's disease, and with completed information on demographics, disease history, cognitive function test, and risk factors of Parkinson's disease. Cognitive function was assessed using the Chinese version of Montreal Cognitive Assessment Scale. Calculation of probability of pPD and assessment of possible (probability between 30% and <80%) or probable (probability ≥80%) pPD were performed according to the criteria published by the International Parkinson and Movement Disorder Society. Multiple linear regression model was employed to analyze the association between baseline cognitive function and follow-up probability of pPD.ResultsThe medians of scores of baseline global cognitive function and cognitive domains in terms of memory, execution, visuospatial function, language, attention, and orientation were 23, 12, 9, 6, 5, 14, and 6, respectively. The median of follow-up probability of pPD was 0.87%, and the proportion of participants with possible or probable pPD was 0.4%. The differences in the distribution of follow-up probability of pPD were significant in groups by baseline global cognitive score quartiles (χ2=21.68, P<0.001). A higher baseline global cognitive score was considerably related to a lower follow-up probability of pPD, b(95%CI)=0.994(0.988~0.999), P=0.040. After adjusting for selected confounders, the results of multiple linear regression analyses showed that the probability of pPD in the highest quartile group was decreased by 10.7% (b=0.893, 95%CI: 0.794-0.992, P=0.034) relative to the lowest quartile group, and the trend was significant (trend P=0.031). Higher baseline index scores of execution, attention, and orientation were highly related to a lower follow-up probability of pPD (all P<0.05).ConclusionDeclines in global cognitive function and cognitive domains of execution, attention, and orientation may associate with a higher probability of pPD in middle-aged and elderly population, which suggests the significance of cognitive intervention in early stage for pPD prevention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".