Approach To Treatment Of Depression In Parkinson’s Disease: Results from NPF-QII (P7.073)
Bibliographic record
Abstract
OBJECTIVE: Characterize correlations between approach to depression care and prevalence of depression in Parkinson’s disease (PD) patients. BACKGROUND: Depressive disturbances are highly prevalent in people with PD but under-diagnosed and under-treated. Many approaches to depression care are employed, but relative efficacy has not been established. METHODS: We examined intervention approaches to depression care at clinics for associations with its prevalence, including antidepressant medications (AD), meeting with a social worker (SW), treatment by a mental health professional (MH), or combinations in subjects from the NPF Quality Improvement Initiative (NPF-QII), an ongoing study of PD at specialty movement disorders clinics. The PDQ-39 Emotional Well-being score (PDQe) provided a surrogate marker of depression with PDQe > 25% indicating clinically significant depression. Subjects were limited to those without comorbid conditions between 50 and 70 years old with Hoehn and Yahr stage 2 or 3, at clinics with 75 or more subjects meeting the criteria. RESULTS: Of 2011 subjects at 11 clinics, 805 (40%) were depressed; prevalence ranged from 29% to 52% across clinics. The overall intervention rate varied from 37% to 66% for depressed subjects (mean, 47%). Intervention rates at clinics by modality were measured to range as follows: AD 26%-52% SW 0%-26% MH 5%-44% Centers with lower overall prevalence of depression more frequently utilized MH (r2 = 0.66; p = 0.0017). There were no differences in depression prevalence associated with SW or AD. CONCLUSIONS: A reduced burden of depression is associated with increased referral to MH. Neither AD nor SW were similarly associated. These results, which will be validated against longitudinal follow up data, support the importance of involving mental health professionals the care of patients with PD.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".