The spectrum of nonmotor symptoms in early Parkinson disease
Bibliographic record
Abstract
OBJECTIVE: Nonmotor symptoms (NMS) are common in patients with established Parkinson disease (PD) but their frequency in early PD has not been extensively studied. Our aim was to determine the frequency of NMS in a cohort of patients with newly diagnosed PD. METHODS: A total of 159 patients with early PD and 99 healthy controls participated in this study. NMS were screened for using the nonmotor symptom questionnaire. Other assessments included measures of motor disability (Movement Disorders Society-revised unified Parkinson's disease rating scale [MDS-UPDRS]), disease severity (Hoehn & Yahr staging), depression (geriatric depression scale), and global cognitive function (Mini-mental state examination and Montreal cognitive assessment). RESULTS: The PD group reported a significantly greater number of NMS compared with controls (8.4 [4.3] vs. 2.8 [2.6]). In the PD group, the most commonly experienced NMS were excessive saliva, forgetfulness, urinary urgency, hyposmia, and constipation. Patients with higher MDS-UPDRS III scores and those with the postural instability gait subtype experienced a greater number of NMS. CONCLUSION: NMS are common in early PD and reflect the multisystem nature of the disorder. Even in the earliest stages of PD, NMS may be detrimental to patients' functional status and sense of well-being.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".