Factors associated with disease-specific quality of life in Taiwanese patients with ankylosing spondylitis: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to assess the factors associated with disease-specific quality of life in Taiwanese patients with ankylosing spondylitis. DESIGN: A cross-sectional study. SETTING: A regional teaching hospital in southern Taiwan. PARTICIPANTS: Adult patients with ankylosing spondylitis recruited from the outpatient rheumatology clinics of the study hospital. PRIMARY OUTCOME MEASURE: Disease-specific quality of life assessed by the Evaluation of Ankylosing Spondylitis Quality of Life (EASi-QoL). RESULTS: Of the 265 patients, 57% were 20-49 years of age, with a male preponderance (75.5%). Multiple stepwise linear regression analysis indicated that a higher disease activity, assessed by the Ankylosing Spondylitis Disease Activity Score, was significantly and independently associated with a lower quality of life in all four domains (physical function, disease activity, emotional well-being and social participation) of the EASi-QoL. In addition, various independent factors, including educational level, nature of occupation, disease duration, dietary habit and body mass index, were significantly associated with different domains of the EASi-QoL. CONCLUSIONS: Our findings indicated that, in addition to disease activity and perceived health status, a number of other factors could significantly impact the different aspects of quality of life in patients with ankylosing spondylitis, which warrant special consideration and support from healthcare providers.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".