Cognitive dysfunction in de novo Parkinson disease: Remitting vs. progressive cognitive impairment
Bibliographic record
Abstract
INTRODUCTION: Parkinson's disease (PD) exhibits divergent cognitive trajectories; however, the factors contributing to these variations remain elusive. This study aimed to examine the clinical features of patients with different long-term cognitive trajectories in de novo PD over a five-year follow-up. METHODS: We analyzed 258 patients who completed every annual evaluation for five years. According to the Montreal Cognitive Assessment (MoCA) scores, we classified patients into three groups: cognitively normal (n = 118, CN), remitting MoCA decline (n = 74, RMD), and progressive MoCA decline (n = 66, PMD). RESULTS: The RMD group was associated with lower olfactory scores (Odds Ratio (OR) = 0.958, p = 0.040), whereas PMD was associated with higher depression scores (OR = 1.158, p = 0.045), probable RBD (OR = 3.169, p = 0.002), older age (OR = 1.132, p < 0.001) and lower educational attainment (OR = 0.828, p = 0.004). PMD had higher neurofilament light chain protein values than CN and RMD (p = 0.006, 0.015, respectively). Longitudinally, PMD showed a greater decline in all cognitive scores and hippocampus volumes (p = 0.004). Meanwhile, RMD exhibited intermediate cognitive and volumetric trajectories between CN and PMD and displayed worse score changes in memory tasks than CN. CONCLUSIONS: While PMD exhibited known risk factors for cognitive impairment, along with worse cognitive performance and hippocampal volume decline, RMD displayed baseline lower olfactory scores and intermediate cognitive and hippocampal volume decline between the two groups. These findings suggest individuals in RMD may still be at risk for cognitive deficits. However, further long-term follow-up data are needed to unravel the determinants and dynamics of cognitive functions.
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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 | 0.001 |
| 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".