Sex Differences in Clinical Features of Early, Treated Parkinson’s Disease
Bibliographic record
Abstract
INTRODUCTION: To improve our understanding of sex differences in the clinical characteristics of Parkinson's Disease, we sought to examine differences in the clinical features and disease severity of men and women with early treated Parkinson's Disease (PD) enrolled in a large-scale clinical trial. METHODS: Analysis was performed of baseline data from the National Institutes of Health Exploratory Trials in Parkinson's Disease (NET-PD) Long-term Study-1, a randomized, multi-center, double-blind, placebo-controlled study of 10 grams of oral creatine/day in individuals with early, treated PD. We compared mean age at symptom onset, age at PD diagnosis, and age at randomization between men and women using t-test statistics. Sex differences in clinical features were evaluated, including: symptoms at diagnosis (motor) and symptoms at randomization (motor, non-motor, and daily functioning). RESULTS: 1,741 participants were enrolled (62.5% male). No differences were detected in mean age at PD onset, age at PD diagnosis, age at randomization, motor symptoms, or daily functioning between men and women. Differences in non-motor symptoms were observed, with women demonstrating better performance compared to men on SCOPA-COG (Z = 5.064, p<0.0001) and Symbol Digit Modality measures (Z = 5.221, p<0.0001). CONCLUSIONS: Overall, men and women did not demonstrate differences in clinical motor features early in the course of PD. However, the differences observed in non-motor cognitive symptoms suggests further assessment of the influence of sex on non-motor symptoms in later stages of PD is warranted.
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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 | 0.000 | 0.000 |
| 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) | 0.004 | 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".