A cross-sectional study of affective, psychiatric, cognitive disorders and motor complications of Parkinson's disease
Bibliographic record
Abstract
Objective To investigate the prevalence, diagnosis and treatment of depression, anxiety, psychiatric symptom, cognitive impairment and motor complications of Parkinson's disease (PD). Methods Face to face interview was carried out among patients with idiopathic PD from Outpatient Department of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine from March to May 2015. Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), Mini-Mental State Examination (MMSE) were used for evaluation of depression, anxiety and cognitive impairment. Results A total of 55 patients with PD were enrolled in this study. Prevalences of depression, anxiety, psychiatric symptom and cognitive impairment of PD were 16.36% (9/55), 14.55% (8/55), 23.64% (13/55) and 9.09% (5/55), respectively. Ratio of previous diagnosis and treatment were 2/9, 2/8, 2/13 and 1/5, respectively. Prevalences of fluctuation and dyskinesia were 27.27% (15/55) and 9.09% (5/55), separately. There were no significant differences in prevalences of depression (P = 0.858), anxiety (P = 0.188), psychiatric symptom (P = 0.926), cognitive impairment (P = 0.286), fluctuation (P = 0.205) or dyskinesia (P = 0.417) between male and female PD patients. Conclusions Prevalences of depression, anxiety, psychiatric symptom, cognitive impairment and motor complications of PD were high, while ratios of diagnosis and treatment were relatively low. DOI: 10.3969/j.issn.1672-6731.2015.06.010
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".