Clinical correlates of quality of life in systemic sclerosis measured with the World Health Organization Disability Assessment Schedule II
Bibliographic record
Abstract
OBJECTIVE: To identify the clinical characteristics of systemic sclerosis (SSc) that best correlate with the health-related quality of life (HRQOL) of patients with SSc, using the World Health Organization Disability Assessment Schedule II (WHODAS II) as the measure of HRQOL. METHODS: A cross-sectional, multicenter study of 337 patients from the Canadian Scleroderma Research Group Registry was conducted. Patients were assessed through detailed clinical histories, medical examination, and the WHODAS II. Hierarchical multiple linear regression was used to assess the relationship between selected clinical variables and HRQOL. RESULTS: The mean WHODAS II score was 23.7 (range 0-100), with the greatest impairments seen in the subscales measuring life activities, mobility, and participation in society. In multivariate analysis, significant predictors of the WHODAS II were skin scores, shortness of breath, number of gastrointestinal problems, fatigue, pain, and depression. The final model explained 61% of the variance in the WHODAS II scores. CONCLUSION: The clinical characteristics identified in this study as significant correlates of HRQOL in SSc should each be targets of intervention in order to improve the HRQOL of patients with this disease.
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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 | 0.006 |
| 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) | 0.002 | 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".