Prevalence and relation of dementia to various factors in Parkinson's disease
Bibliographic record
Abstract
AIMS: Parkinson's disease is a chronic neurodegenerative disorder characterized by bradykinesia, rigidity, and resting tremor. Dementia, among its non-motor symptoms, is a debilitating complication affecting intellectual functioning. The aim of the present study was to determine the prevalence of dementia in Parkinson's disease and its relation to age, gender and stage of the disease. METHODS: A retrospective chart analysis was performed on Parkinson's disease patients seen in a community-based Parkinson's disease and movement disorder clinic between 2005 and 2010. RESULTS: A total of 310 patients were included in this survey, among whom 61 patients (19.7%) with Parkinson's disease met the criteria for dementia. Age was found to be a significant factor in developing dementia, with 90% of patients with dementia aged ≥70. Gender, however, was not correlated with dementia in Parkinson's disease. On analysis of stage at which dementia developed, progression of the disease was positively correlated with prevalence of dementia. CONCLUSIONS: As age increases, the chances of developing dementia increase. Dementia, contrarily, is not selective between genders. The likelihood of developing dementia increases as the stage of disease advances. Further research is required in order to understand underlying mechanisms of dementia in Parkinson's disease.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".