Influencing Factors and Correlation Analysis of Apathy in Patients with Parkinson's Disease
Bibliographic record
Abstract
Abstract Background Parkinson's disease (PD) is a complex progressive neurodegenerative disease. The prevalence of Parkinson's disease has increased rapidly in the last 20 years. Apathy, one of the non-motor symptoms of Parkinson's disease, severely affects patients' daily functioning and quality of life, increases the burden on caregivers, and maybe a precursor to dementia. Identifying the factors associated with indifferent PD patients is essential in slowing disease progression and improving patient prognosis.Methods A total of 73 PD patients from the outpatient or inpatient department of Neurology at the Third Affiliated Hospital of Xinxiang Medical University were collected. The clinical scales of PD patients were assessed. According to Starkstein Apathy Scale (AS), these patients were divided into an apathetic group (46 patients) and a non-apathetic group (27 patients). Spearman correlation analysis and Stepwise multiple linear regression analysis were used to explore the correlation between total AS scores and clinical characteristics.Results Spearman correlation analysis showed that the total scores of AS were positively correlated with disease duration, HY stages, Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) scores, Hamilton Anxiety Rating Scale (HAMA) scores, Hamilton Depression Rating Scale (HAMD) scores, Pittsburgh Sleep Quality Index (PSQI) scores, King's Parkinson's Disease Pain Scale ( KPPS) scores, Parkinson Autonomic Symptom Scale (SCOPA-AUT) scores, and 39-item Parkinson's Disease Questionnaire (PDQ-39) scores. It was negatively correlated with Montreal Cognitive Assessment (MoCA) scores and Mini-Mental Status Examination (MMSE) scores. Stepwise multiple linear regression analysis showed that low MoCA scores and high HAMA scores were correlated with apathy, indicating that MoCA scores and HAMA scores may be important determinants of apathy in PD patients.Conclusion PD patients with apathy showed longer disease duration, higher Hoehn and Yahr (HY) stages, more severe motor dysfunction, more severe cognitive impairment, more severe anxiety, more depression symptoms, more severe sleep symptoms, more severe autonomic dysfunction and worse quality of life. Cognitive dysfunction and anxiety may be the risk factors for PD patients with apathy.
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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 | 0.003 |
| 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) | 0.001 | 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".