Population-based Studies on the Clinical Progression of Motor and Non-motor Features in Parkinson’s Disease
Bibliographic record
Abstract
Although Parkinson’s disease (PD) is a movement disorder in which tremor, rigidity and bradykinesia constitute the cardinal signs of the disease, it is increasingly recognised to be associated with a wide range of motor and non-motor features. Population-based studies demonstrate that the motor course in PD is generally slowly progressive, with average annual progression rates of ≤3%. However, there is remarkable inter-individual variation in the clinical course of PD, with advanced age and predominant postural instability and gait difficulties being major risk factors for more rapid motor and cognitive decline. Around 20–40% of patients exhibit subtle cognitive deficits at diagnosis. These usually worsen over time and progress into dementia, which approximately 80% of PD subjects develop during the course of their disease. Population-based studies indicate rather high frequencies of other non-motor symptoms in moderate to advanced stages, such as depression, fatigue, apathy, sleep disorders and autonomic dysfunction, although prevalence rates often are lower than those observed in clinic-based studies. However, as several population-based studies were cross-sectional, uncontrolled and did not use currently accepted rating scales or diagnostic criteria, the relative risk and clinical course of many disease-related features remain unclear in the general PD population. Further population-based studies are warranted in order to extend current knowledge on the clinical course in representative PD cohorts.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".