High Cerebrospinal <scp>DOPA</scp> Decarboxylase Level Predicts Cognitive Decline in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: DOPA decarboxylase (DDC) in cerebrospinal fluid (CSF) is an emerging Parkinson's disease (PD) biomarker, but its association with nonmotor symptoms is unclear. OBJECTIVES: We aimed to determine if baseline DDC was associated with future cognitive decline in PD. METHODS: We correlated baseline CSF DDC, detected using the proximity extension assay, with Montreal Cognitive Assessment (MoCA) score using longitudinal data from 3 cohorts: Biopark, PPMI, and PDBP. RESULTS: DDC was significantly associated with cognitive decline in both the Biopark cohort (P-value < 0.0001) and the PDBP/PPMI cohorts (P-value < 0.0001). The results were still significant after correcting for levodopa-equivalent daily dose in the Biopark cohort (P-value < 0.0001) and when the analysis was restricted to the de novo subjects, both in Biopark (P-value: 0.0065) and PPMI (P-value<0.0001) cohorts. CONCLUSIONS: CSF DDC is a potential biomarker for the prediction of cognitive decline in PD patients.
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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 | 0.002 |
| 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".