Characterizing advanced Parkinson’s disease: OBSERVE-PD observational study results of 2615 patients
Bibliographic record
Abstract
BACKGROUND: There are currently no standard diagnostic criteria for characterizing advanced Parkinson's disease (APD) in clinical practice, a critical component in determining ongoing clinical care and therapeutic strategies, including transitioning to device-aided treatment. The goal of this analysis was to determine the proportion of APD vs. non-advanced PD (non-APD) patients attending specialist PD clinics and to demonstrate the clinical burden of APD. METHODS: OBSERVE-PD, a cross-sectional, international, observational study, was conducted with 2615 PD patients at 128 movement disorder centers in 18 countries. Motor and non-motor symptoms, activities of daily living, and quality-of-life end points were assessed. The correlation between physician's global assessment of advanced PD and the advanced PD criteria from a consensus of an international group of experts (Delphi criteria for APD) were evaluated. RESULTS: According to physician's judgment, 51% of patients were considered to have APD. There was a moderate correlation between physician's judgment and Delphi criteria for APD (K = 0.430; 95% CI 0.406-0.473). Activities of daily living, motor symptom severity, dyskinesia duration/disability, "Off" time duration, non-motor symptoms, and quality-of-life scores were worse among APD vs. non-APD patients (p < 0.0001 for all). APD patients (assessed by physicians) had higher disease burden by motor and non-motor symptoms compared with non-APD patients and a negative impact on activities of daily living and quality of life. CONCLUSIONS: These findings aid in identifying standard APD classification parameters for use in practicing physicians. Improvements in identification of APD patients may be particularly relevant for optimizing treatment strategies including transitioning to device-aided treatment.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".