Parkinson's disease‐cognitive rating scale: Psychometrics for mild cognitive impairment
Bibliographic record
Abstract
Lack of validated data on cutoff scores for mild cognitive impairment (MCI) and sensitivity to change in predementia stages of Parkinson's disease (PD) limit the utility of instruments measuring global cognition as screening and outcome measures in therapeutic trials. Investigators who were blinded to PD-Cognitive Rating Scale (PD-CRS) scores classified a cohort of prospectively recruited, nondemented patients into a PD with normal cognition (PD-NC) group and a PD with MCI (PD-MCI) group using Clinical Dementia Rating (CDR) and the Mattis Dementia Rating Scale-2 (MDRS-2). The discriminative power of the PD-CRS for PD-MCI was examined in a representative sample of 234 patients (145 in the PD-NC group; 89 in the PD-MCI group) and in a control group of 98 healthy individuals. Sensitivity to change in the PD-CRS score (the minimal clinically important difference was examined with the Clinical Global Impression of Change scale and was calculated with a combination of distribution-based and anchor-based approaches) was explored in a 6-month observational multicenter trial involving a subset of 120 patients (PD-NC, 63; PD-MCI, 57). Regression analysis demonstrated that PD-CRS total scores (P < 0.001) and age (P = 0.01) independently differentiated PD-NC from PD-MCI. Area under the receiver operating characteristic curve (AUC) analysis (AUC, 0.85; 95% confidence interval, 0.80-0.90) indicated that a score ≤ 81 of 134 was the optimal cutoff point on the total score for the PD-CRS (sensitivity, 79%; specificity, 80%; positive predictive value, 59%; negative predictive value, 91%). A range of change from 10 to 13 points on the PD-CRS total score was indicative of clinically significant change. These findings suggest that the PD-CRS is a useful tool to identify PD-MCI and to track cognitive changes in nondemented patients with PD.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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 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".