Sex Differences in Neuropsychiatric Symptoms in Alpha‐Synucleinopathies: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Alpha-synucleinopathies, such as Parkinson's disease (PD), Parkinson's disease dementia (PDD), and dementia with Lewy bodies (DLB), demonstrate sex differences with regard to prevalence, age of onset, and motor manifestations. Neuropsychiatric symptoms (NPS) are common early and late manifestations of these disorders. OBJECTIVES: We aimed to describe sex differences in NPS across alpha-synucleinopathies. METHODS: We searched Web of Science Core collection databases to identify observational studies published between January 1, 2000, and June 1, 2022, reporting the prevalence or severity of NPS among individuals with a diagnosis of PD, PDD, or DLB. Prevalence and severity were pooled for each NPS according to sex using random-effects models. RESULTS: Two-hundred-and-forty studies, representing 796,026 participants (45% females), were included in the meta-analysis. Female sex was associated with a higher prevalence of anxiety (OR = 1.60 [95% CI: 1.40, 1.82]), depression (OR = 1.56 [1.45, 1.67]), fatigue (OR = 1.21 [1.02, 1.43]), and psychotic symptoms (OR = 1.26 [1.14, 1.40]) and more severe anxiety (g = 1.35 [95% CI: 0.58, 2.13]), depression (g = 1.57 [1.05, 2.08]), and fatigue (g = 0.86 [0.41, 1.32]), while male sex was associated with a higher prevalence of apathy (OR = 0.77 [0.63, 0.93]), impulse control disorders (OR = 0.67 [0.55, 0.82]), REM sleep behavior disorder (OR = 0.54 [0.42, 0.70]), hypersomnolence (OR = 0.67 [0.56, 0.80]), and suicide (OR = 0.30 [0.20, 0.44]). CONCLUSIONS: NPS have different prevalences and severities in alpha-synucleinopathies according to sex. These findings support consideration of sex in the elaboration of clinical tools.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.040 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".