The relationship between patient satisfaction with health and clinical measures of function and disease status in patients with psoriatic arthritis.
Bibliographic record
Abstract
OBJECTIVE: To investigate whether patient satisfaction with health is a distinct aspect of clinical or health status in a sample of patients with psoriatic arthritis (PsA). METHODS: One hundred sixty-nine consecutive outpatients attending the University of Toronto PsA Clinic completed the Arthritis Impact Measurement Scales II (AIMS2), which includes both a global rating of patient satisfaction with health and a scale that assesses satisfaction with functioning in 12 health domains. Clinical, laboratory, and radiological assessments of function, pain, inflammation, and damage were also performed according to a standard protocol. RESULTS: Logistic regression analysis indicated that the AIMS2 global ratings of patient satisfaction with health were not associated with traditional clinical measures of inflammation and damage, but were associated with American College of Rheumatology (ACR) functional class and number of fibromyalgia tender points. Patient satisfaction was also related to annual family income and use of retinoids or corticosteroids. Similarly, linear regression analysis showed that scores on the AIMS2 satisfaction scale were unrelated to traditional clinical measures of inflammation and damage, with the exception of total number of actively inflamed joints. ACR functional class, annual family income, and comorbidity were also related to scores on the satisfaction scale. CONCLUSION: Patient satisfaction with health appears to be relatively independent of traditional clinical measures of physical functioning, pain, and disease status.
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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 | 0.000 | 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) | 0.002 | 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".