Impact of Progression of Parkinson's Disease and Various Other Factors on Generalized Anxiety Disorder
Bibliographic record
Abstract
ABSTRACT Objective: While much research has been conducted toward understanding the relationship between prevalence of Parkinson's disease (PD) and generalized anxiety, little has been done considering additional influential factors in the relationship by means of a large ethnically diverse sample. Our study strives to fulfill these deficits in the literature as we set out to determine the impact of progression of PD, age, gender, and Hoehn and Yahr (H and Y) staging of PD on generalized anxiety. Methods: A retrospective chart review analysis was performed on PD patients who were regularly examined in a community-based PD and movement disorders center from 2005 to 2010. Results: This study consisted of 310 patients with PD among whom 12% had generalized anxiety. Neither age nor gender was significant onset predictors at P = 0.05. The impact of progression of H and Y Stages 2–3 and 2–4 increased the odds of generalized anxiety disorder (GAD) prevalence though it was statistically insignificant at P = 0.05. Conclusions: Clinicians should not expect the risk of developing anxiety to depend on gender nor change as a function of age though it may increase with symptomatic progression of PD as outlined by H and Y. To the best of our knowledge, this is the largest and most ethnically diverse prevalence study with a focus on generalized anxiety and PD. Significant Outcomes and Limitations: The symptomatic progression of PD, but not age or gender, may be associated with an increased risk for GAD. This study lacked adjustment for potential confounders such as depression and PD medications.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".