Gender Differences in the Prevalence of Parkinson's Disease
Bibliographic record
Abstract
Background: Parkinson's disease (PD) affects males more than females. The reasons for the gender differences in PD prevalence remain unclear. Objective: The objective of this systematic review and meta-analysis was to update the overall male/female prevalence ratios (OPR). Methods: We updated previous work by searching MEDLINE, SCOPUS, and OVID for articles reporting PD prevalence for both genders between 2011 and 2021. We calculated OPRs and investigated heterogeneity in effect estimates. Results: We included 19 new articles and 13 articles from a previously published meta-analysis. The OPR was 1.18, 95% CI, [1.03, 1.36]. The OPR was lowest in Asia and appeared to be decreasing over time. Study design, national wealth, and participant age did not explain OPR heterogeneity. Conclusion: Gender differences in PD prevalence may not be as stark as previously thought. Studies are needed to understand the role of other determinants of gender differences in PD prevalence.
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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 | 0.017 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.015 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".