Impact of Progression of Parkinson’s Disease on Drooling in Various Ethnic Groups
Bibliographic record
Abstract
BACKGROUND/AIMS: Drooling or sialorrhea is a common non-motor symptom of Parkinson's disease (PD), and is reported by 35-75% of patients. Drooling is primarily due to impaired swallowing rather than hypersecretion of saliva. In this study, we examined the prevalence of drooling in PD and its relation to various factors such as age, stage of disease, gender and ethnicity. METHODS: A retrospective cohort chart analysis of 307 patients with idiopathic PD was conducted. These patients were seen in the Parkinson's Disease and Movement Disorders Clinic between 2005 and 2010. RESULTS: 123 (40%) patients exhibited drooling. No correlation between age and development of drooling was observed. However, gender was found to be a significant factor in developing sialorrhea. Males are twice as more likely to develop sialorrhea than females. In addition, drooling becomes more prevalent with disease progression; Hoehn and Yahr stage 4 patients being the most at risk. Ethnicity and immigration status have no relationship in developing drooling. CONCLUSIONS: Sialorrhea is seen in a significant number of PD patients. This study, to the best of our knowledge, is the most extensive clinical assessment of drooling in PD to date.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".