Apathy and neuropsychological characteristics of newly diagnosed Parkinson's disease patients
Bibliographic record
Abstract
Objective To investigate the apathy and neuropsychological characteristics of newly diagnosed Parkinson's disease (PD) patients. Methods Eighty-two newly diagnosed PD patients and 30 matched healthy controls by age, sex and education level were recruited in the present study.Apathy was assessed using Apathy Evaluation Scale (AES) and related factors, including age, sex, education level and disease duration were simultaneously evaluated.Unified Parkinson's Disease Rating Scale (UPDRS), Hamilton Depression Rating Scale (HAMD), as well as Montreal Cognitive Assessment (MoCA) were employed in order to respectively evaluate the motor function, depression and cognition. Results The AES scores in the PD patients were significantly higher when compared to the healthy controls. The prevalence of apathy and depression in the PD patients was 51.2%(42/82) and 19.5%(16/82), respectively. There were no statistically significant differences in age, sex, education level, UPDRS-Ⅱ/Ⅲ scores and MoCA scores between apathy (n=42) and no-apathy (n=40) PD patients (P>0.05), while the statistically significant difference in HAMD scores between apathy (n=42) and no-apathy (n=40)PD patients was shown (the HAMD scores of apathy PD patients were 10.61±3.30, the HAMD scores of no-apathy PD patients were 5.96±1.90, t=7.87, P<0.05). The correlation analysis indicated that there were no correlations between AES scores and the related factors, including age, education level, disease duration and UPDRS-Ⅱ/Ⅲ scores, but AES scores were positively correlated with HAMD scores. Conclusion In newly diagnosed PD patients, the apathy is independent of depression, motor dysfunction, as well as cognitive impairment, which may be an early signal for PD. Key words: Parkinson disease; Apathy; Neuropsychological test; Newly diagnosed
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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 | 0.001 | 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".