The Clinical Profile of Nonmotor Fluctuations in Parkinson's Disease Patients
Bibliographic record
Abstract
OBJECTIVE: Recently described nonmotor fluctuations may cause disability in Parkinson's disease patients. These fluctuations are generally grouped as sensory, autonomic and psychiatric. The clinical spectrum and frequency of these fluctuating symptoms are not well-described. METHODS: We studied the relationship of nonmotor fluctuations with motor symptoms and determined the influence of age at disease onset, duration of disease, dosage and duration of levodopa treatment in the appearance of nonmotor fluctuations. RESULTS: Statistical analysis showed a relationship of disease-related parameters with sensory and autonomic fluctuations but psychiatric fluctuations were only found to be associated with the duration of levodopa usage. The nonmotor fluctuations included in the study were observed during "on" periods as well as "off' periods. CONCLUSION: Nonmotor fluctuations had variable presentations. Moreover, their co-appearance with different types of motor fluctuations may be linked to the effect of other neurotransmitter systems acting synchronously with dopamine. Risk factors for sensory and autonomic fluctuations in patients with Parkinson's disease were early age of disease onset, longer duration and higher dose of levodopa use. Psychiatric fluctuations were only associated with higher doses of levodopa.
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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 | 0.002 |
| 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 | 0.000 | 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".