The Parkinson's Disease Composite Scale: results of the first validation study
Bibliographic record
Abstract
Background and purpose The aim was to validate the Parkinson's Disease Composite Scale ( PDCS ). Methods The study included 194 Parkinson's disease ( PD ) patients in five countries. Investigators completed the following scales: PDCS , the Movement Disorder Society Unified Parkinson's Disease Rating Scale ( MDS ‐ UPDRS ), Parkinson's Disease Sleep Scale Version 2, Montreal Cognitive Assessment, the Scale for Evaluation of Neuropsychiatric Disorders in Parkinson's Disease and the Clinical Impression of Severity Index for PD ( CISI ‐ PD ). For test−retest analysis, a second administration of the PDCS was carried out in 61 stable patients (as per the CISI ‐ PD ) in 7–14 days after the first evaluation. The PDCS is a novel scale for PD with a total of 17 items divided into four domains: motor, non‐motor, treatment complications and disability. Results Parkinson's Disease Composite Scale mean and median values were close. Skewness values were into the criterion limits (−1 to +1). The complete range of scores was covered for 14 of the 17 items (83.4%). A floor effect of 25.26% and 28.25% was observed in the complications and disability level dimensions due to the proportion of patients free of these difficulties. No relevant floor or ceiling effect was observed for the PDCS total score (1.03% and 0.52%, respectively). The stability of the scale appeared excellent with most items meeting weighted kappa and intraclass correlation coefficient values >0.80. The convergent validity of the PDCS with corresponding scores of the MDS ‐ UPDRS showed high correlation values ( r S ≥ 0.60). The internal validity was into acceptable limits, with the majority of values higher than the minimal 0.30 threshold. The standard error of measurement suggested a satisfactory precision (SEM 3.81, <30% of the PDCS total score standard deviation). Conclusion The PDCS appears to be a feasible, acceptable, reproducible and valid scale.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".