Longitudinal Study of Treatment Variability for Parkinson's Disease across Specialized Centers
Bibliographic record
Abstract
BACKGROUND: Real-world evidence on treatment practices in Parkinson's disease (PD) has been limited due to the difficulty in collecting comprehensive and generalizable clinical data. OBJECTIVES: We sought to identify treatment patterns and test how treatment changed in response to (1) falling, (2) worsening disease, and (3) worsening quality of life across PD specialized centers. METHODS: We used the Parkinson Outcomes Project data collected from 2010 to 2023 across 31 international PD specialized centers. Demographic and clinical characteristics were collected annually and included medication use, physical therapy referral, psychologist or psychiatrist care, and deep brain stimulation (DBS) surgery. Treatment practice variation was described by center and in response to outcomes (self-reported falls, higher Hoehn and Yahr stage, worse emotional and mobility subscale scores on quality-of-life scale). RESULTS: A total of 12,664 participants were analyzed. Treatment practices varied substantially across centers with the use of levodopa in the first 5 years of disease ranging from 59.3% to 94.6% and physical therapy referral ranging from 13% to 71%. At ≥ 5 years of disease, DBS rates varied from 2% to 41%. After a fall, individuals were more likely to be referred for physical therapy (β: 0.44, 95% confidence interval [CI]: 0.36, 0.52), and mental health services were recommended after a decline in emotional subscores (β: 1.74, 95% CI: 1.50, 1.98). However, there was no change in levodopa-equivalent daily dose after worsening mobility subscores (β: -29.97, 95% CI: -76.67, 16.73). CONCLUSIONS: These results highlight the large variability in PD practice across specialty centers and the importance of establishing best practice guidelines. Understanding the drivers of this variability is an essential next step.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".