CORRELATION AMONG OLFACTORY DYSFUNCTION, APATHY AND FATIGUE IN PATIENTS WITH PARKINSON’S DISEASE
Bibliographic record
Abstract
Abstract \nObjectives: Although Parkinson's disease (PD) is usually described as a movement disorder, it exhibits strong associations with non motor symptoms (NMS), including smell and taste dysfunction, neuropsychiatric symptoms, sleep problems and autonomic dysregulation. The olfactory deficit is considered the most common NMS in PD preceding motor symptoms. \nAim of this study was first to investigate olfactory function, cognitive impairment, apathy and fatigue in subjects with Parkinson's in relation to healthy controls, and subsequently to analyse the correlation among these NMS in subjects with PD. \nMethods: One hundred and forty seven subjects (51controls, mean age 65.1 ± 11.8 years and 96 PD subjects with a mean age of 67.8 ± 8.2 years) were enrolled. Olfactory function was evaluated through the Sniffin’ Sticks Extended Test comprised of three different subtests (odor detection threshold, discrimination and identification) and their sum (TDI score). The Montreal Cognitive Assessment (MoCA) test was used to evaluate cognitive impairment. Apathy was examined by self-report version of Starkstein Apathy Scale (SAS) and fatigue was evaluated with the Parkinson’s Disease Fatigue Scale (PFS-16). \nResults: PD patients showed severe impairment in odor detection threshold, discrimination and identification compared to healthy controls. Moreover, in PD patients apathy score was significantly increased in respect to controls. A negative correlation was observed among all parameters of olfactory function and apathy score. \nDiscussion: Our results identified a greater level of apathy in PD patients affected by severe olfactory loss. These findings suggest that possible common pathways might be involved in these two different NMS. Moreover, the present study confirms that alteration of olfactory parameters, such as odor threshold, identification, discrimination and TDI score, should be related to other NMS, influencing negatively the global quality of life in PD patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".