Depression and other nonmotor manifestations of Parkinson’s disease
Bibliographic record
Abstract
Background. The occurrence of emotional, cognitive, behavioral disorders associated with Parkinson’s disease is on the average 1.5-3 times higher than in the general population of the same age. At least one neuropsychiatric symptom is diagnosed in 77% of the patients and 46% have combination of three or more disturbances. Non-motor disturbances are manifested at all stages of Parkinson’s disease, but information about the relationship between their frequency and manifestations and the duration and severity of the disease is rather contradictory. Aim. To evaluate the prevalence and severity of depression and other non-motor symptoms in patients with Parkinson’s disease. Materials and methods. 206 patients at the average age 65.9±9.7 yr with Parkinson’s disease receiving pharmacotherapy were studied. The clinical assessment was carried out using the Unified Parkinson’s Disease Rating Scale, Hoehn & Yahr Scale, Beck depression inventory II, Hospital anxiety and depression scale, Apathy Scale, Questionnaire for Impulsive-Compulsive Disorders in PD-Rating Scale, Montreal Cognitive Assessment, Parkinson’s Disease Quality of Life Questionnaire- 39, Medical Outcomes Study 36-Item Short Form. Results. 30.9% of the 62 patients with Parkinson’s disease suffered mild, 56 (27.4%) moderate, 21 (10.2%) severe depression and only 67 (32.5%) patients had no depression. The study revealed correlation of depression with apathy (r=0,488; p<0,001), low quality of life according to the PDQ-39 (r=0,471; p<0,001), cognition (r=0,451; p<0,001), emotional well-being (r=0,450; p≤0,001), anxiety (r=0,436; p<0,001). Conclusion. The prevalence of depression in patients with Parkinson’s disease is up to 67.5%. The proportion of patients with severe depression reaches 10.2%. Depression is one of the most frequent non-motor syndromes of Parkinson’s disease deteriorating the quality of life of the 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 | 0.000 | 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) | 0.002 | 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".