Depression in Parkinson's Disease
Bibliographic record
Abstract
OBJECTIVE: To examine predictive factors associated with onset of depression among individuals diagnosed with Parkinson's disease (PD). BACKGROUND: Depression may precede or follow symptomatic parkinsonism in PD. It is frequently treatable but often overlooked. METHODS: The clinical series comprised 685 individuals who were diagnosed with PD and followed by one neurologist (RJU) from 1994 to 2007. The primary outcome was time to depression following the onset of PD. Diagnosis of depression was based on clinical assessment of depressive symptoms from patients (and spouse/family/caregiver) and antidepressant usage. A number of demographic, historical and clinical predictive factors were examined, including gender, age at symptomatic onset, disease duration, onset characteristics, clinical ratings, antiparkinsonian medications, cognitive status, depression history, and familial history of PD and other neurodegenerative disorders. RESULTS: Seventy-two percent of patients developed depression within ten years of symptomatic PD onset, and the mean time to depression was 7.9 years (median: 5.7 years). Factors associated with depression included longer PD duration, greater impairment in activities of daily living, and positive family history of motor neuron disease (MND). CONCLUSIONS: A high rate of individuals with PD develop depressive symptoms during the course of the disease. Based on first clinic visit characteristics, most factors examined were not helpful in identifying individuals with an increased risk of depression. However, disease duration, functional limitations and family history of MND should lead clinicians to an increased vigilance for identifying depression.
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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 | 0.002 |
| 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 | 0.001 |
| 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".