Longitudinal Change in Quality of Life in Neurological Disorders Measures Over 3 Years in Patients with Early Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: The Quality of Life in Neurological Disorders (Neuro-QoL) is a publicly available health-related quality-of-life measurement system. OBJECTIVE: The aim of this study was to evaluate the utility of Neuro-QoL item banks as outcome measures for clinical trials in Parkinson's disease. METHODS: An analysis of Neuro-QoL responsiveness to change and construct validity was performed in a multicenter clinical trial cohort. RESULTS: Among 310 participants over 3 years, changes in five of eight Neuro-QoL domains were significant (P < 0.05) but very modest. The largest effect sizes were seen in the cognition and mobility domains (0.35-0.39). The largest effect size for change over the year in which levodopa was initiated was -0.19 for lower extremity function-mobility. For a similarly designed clinical trial, estimated sample size required to demonstrate a 50% reduction in worsening ranged from 420 to more than 1000 participants per group. CONCLUSIONS: More sensitive tools will be required to serve as an outcome measure in early Parkinson's disease. © 2021 International Parkinson and Movement Disorder Society.
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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 | 0.001 |
| 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".