Behind the Mask: Parkinson's Disease and Depression
Bibliographic record
Abstract
Parkinson's disease (PD) is a common, prevalent neurodegenerative disease. It is mainly characterized by motor symptoms such as rigidity, tremors, and bradykinesia, but it can also manifest with non-motor symptoms, of which depression is the most frequent. The latter can impair the quality of life, yet it gets overlooked and goes untreated because of the significant overlap in their clinical features, hence making the diagnosis difficult. Furthermore, there is limited data on the availability of appropriate criteria for making the diagnosis of depression in PD patients, as it can occur with varying expressions throughout the course of PD or it can also precede it. This review article has included a brief discussion on the diagnosis of depression in PD patients and their overlapped clinical manifestations. Understanding the mechanisms underlying the disease processes of PD and depression and the pathways interconnecting them gives better knowledge on devising treatment options for the patients. Only studies from Pubmed were included and all other databases were excluded. Studies from the last 50 years were included. Suitable references included in these studies were also extracted. Thus, depression in PD and PD in depression, along with their pharmacological and non-pharmacological treatment options, have been discussed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".