Health-Related Quality of Life in Parkinson disease: Correlation between Health Utilities Index III and Unified Parkinson's Disease Rating Scale (UPDRS) in U.S. male veterans
Bibliographic record
Abstract
OBJECTIVE: To apply a scaled, preference-based measure to the evaluation of health-related quality of life (HRQoL) in Parkinson's disease (PD); to evaluate the relationship between disease-specific rating scales and estimated HRQoL; and to identify predictors of diminished HRQoL. BACKGROUND: Scaled, preference-based measures of HRQoL ("utilities") serve as indices of impact of disease, and can be used to generate quality-adjusted estimates of survival for health-economic evaluations. Evaluation of utilities for PD and their correlation with standard rating scales have been limited. METHODS: Utilities were generated using the Health Utilities Index Mark III (HUI-III) on consecutive patients attending a PD Clinic between October 2003 and June 2006. Disease severity, medical, surgical (subthalamic nucleus deep brain stimulation (STN-DBS)), and demographic information were used as model covariates. Predictors of HUI-III utility scores were evaluated using the Wilxocon rank-sum test and linear regression models. RESULTS: 68 men with a diagnosis of PD and a mean age of 74.0 (SD 7.4) were included in the data analysis. Mean HUI-III utility at first visit was 0.45 (SD 0.33). In multivariable models, UPDRS-II score (r2 = 0.56, P < 0.001) was highly predictive of HRQoL. UPDRS-III was a weaker, but still significant, predictor of utility scores, even after adjustment for UPDRS-II (P = 0.01). CONCLUSIONS: Poor self-care in PD reflected by worsening UPDRS-II scores is strongly correlated with low generic HRQoL. HUI-III-based health utilities display convergent validity with the UPDRS-II. These findings highlight the importance of measures of independence as determinants of HRQoL in PD, and will facilitate the utilization of existing UPDRS data into economic analyses of PD therapies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".