Effect of emotion on the cognitive function of patients with mild to moderate Parkinson's disease
Bibliographic record
Abstract
Objective To explore the effect of anxiety and depression on cognitive function in patients with mild to moderate Parkinson's disease (PD). Methods A total of 71 patients with primary PD were enrolled in this study. Unified Parkinson's Disease Rating Scale (UPDRS) and Hoehn-Yahr stage were used to evaluate the severity of the disease. Hamilton Anxiety Rating Scale (14-item version, HAMA-14) and Hamilton Depression Rating Scale (24-item version, HAMD-24) were used to evaluate the anxiety and depression. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA, Beijing version) were used to evaluate the cognitive function. The impact of anxiety and depression on cognitive function was analyzed. Results All of these patients were diagnosed as mild to moderate PD, including 61 patients (85.92% ) with anxiety, 55 patients (77.46% ) with depression and 52 patients (73.24% ) with concurrent anxiety and depression. The UPDRS score of patients with anxiety and depression were significantly higher than that of patients without anxiety (P = 0.016) or depression (P = 0.000). The MoCA score of PD patients with anxiety were significantly lower than that of patients without anxiety (P = 0.042). Among 71 patients, there were 49 cases (69.01% ) with cognitive dysfunction, including 28 patients (39.44% ) with mild cognitive impairment (MCI) and 21 cases (29.58% ) with dementia. There was no statistical difference of HAMA-14 and HAMD-24 scores among PD patients with different cognitive levels (P > 0.05, for all). Logistic regression analysis showed only anxiety was the independent risk factor for cognitive dysfunction of PD patients (OR = 10.816, 95%CI: 1.682-69.560; P = 0.012). Conclusions The illness of PD patients accompanied by anxiety or depression is more serious. PD patients with anxiety have higher prevalence of cognitive dysfunction. DOI: 10.3969/j.issn.1672-6731.2016.02.006
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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 | 0.000 | 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) | 0.001 | 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".