Sex-specific progression of Parkinson’s disease: A longitudinal mixed-models analysis
Bibliographic record
Abstract
BackgroundDespite its relevance, the clinical progression of motor- and non-motor symptoms associated with Parkinson's disease (PD) is poorly described and understood, particularly in relation to sex-specific differences in clinical progression.ObjectiveIdentification of differential aspects in disease progression in men and women with PD.MethodsLinear mixed-model analyses of 802 people with typical PD from the Luxembourg Parkinson's study's prospective cohort (median time of follow-up = three years). We estimated the effect of time and its moderation by sex (alpha ≤ 0.05), including confidence intervals, for the following outcomes: MDS-UPDRS I-IV, Starkstein Apathy Scale, Beck Depression Inventory, Montreal Cognitive Assessment (MoCA), Sniffin’ sticks, bodily discomfort, rapid eye movement sleep behavior disorder questionnaire, PD Sleep Scale (PDSS), Munich Dysphagia Test-PD, Functional Mobility Composite Score, and the MDS-based tremor and postural instability and gait disturbances scale. In addition, the marginal means illustrated the symptoms’ trajectories in men and women. Men and women had similar age.ResultsOverall, we observed a slower progression (interaction effect) in women compared to men, especially for MoCA (−0.159, 95%CI [−0.272, −0.046], p = 0.006), PDSS (−0.716, 95%CI [−1.229, −0.203], p = 0.006), PIGD (0.133, 95%CI [0.025 0.241], p = 0.016), and MDS-UPDRS II (0.346, 95%CI [0.120, 0.572], p = 0.003). The finding for MDS-UPDRS II was significant (FWER of 5%) after adjustment for multiple comparisons (Bonferroni-Holm).ConclusionsNext to the further exploration of sex-specific progression, interventions, proactive monitoring and communication strategies tailored to the symptoms progression and needs of men and women need to be developed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".