Dementia in Parkinson’s disease – a comprehensive review
Bibliographic record
Abstract
Muhammad Saad Yousuf,1,2 Usama Daniyal11Parkinson’s Clinic and Movement Disorder Center, Toronto, Ontario, Canada; 2University of Toronto Scarborough, Toronto, Ontario, Canada Abstract: Parkinson’s disease is neurodegenerative disease characterized by motor and non-motor symptoms. Dementia is one of the most debilitating non-motor symptoms of Parkinson’s disease. It affects intellectual and cognitive functioning at various levels. In this regard, this review acts as a comprehensive overview of history, pathology, symptomology, and treat-ments while suggesting future avenues for further research. The review assesses disease pathology covering aspects of clinical manifestations, risk factors, morphological changes in the brain, and etiology. Dementia is correlated with increasing age, severity of underlying complications (Hoehn and Yahr Stage), and is more prevalent in males. On average, approximately, 1 in 4 patients with Parkinson’s disease will develop dementia. With better health care and technological advancements, life expectancy has been shown to be on a rise. Also, the baby boomers are reaching retirement age and are most at risk of neurological disorders. As a result, it is estimated that dementia will become as prevalent as affecting 81.1 million individuals by the year 2040. Parkinson’s disease by itself is debilitating and in conjunction with dementia completely hampers independent living. Thus, future avenues for further understanding and preventing dementia in Parkinson’s disease are necessary.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".