Do Comorbidities Play a Role in Hand Osteoarthritis Disease Burden? Data from the Hand Osteoarthritis in Secondary Care Cohort
Bibliographic record
Abstract
OBJECTIVE: Because the association and its clinical relevance between comorbidities and primary hand osteoarthritis (OA) disease burden is unclear, we studied this in patients with hand OA from our Hand OSTeoArthritis in Secondary care (HOSTAS) cohort. METHODS: ). Mean differences were estimated between patients with versus without comorbidities, adjusted for age and sex: for general disease burden [health-related quality of life (HRQOL), Medical Outcomes Study Short Form-36 physical component scale (0-100)] and disease-specific burden [self-reported hand function (0-36), pain (0-20; Australian/Canadian Hand OA Index), and tender joint count (TJC, 0-30)]. Differences above a minimal clinically important improvement/difference were considered clinically relevant. RESULTS: The study included 538 patients (mean age 61 yrs, 86% women, 88% fulfilled American College of Rheumatology classification criteria). Mean (SD) HRQOL, function, pain, and TJC were 44.7 (8), 15.6 (9), 9.3 (4), and 4.8 (5), respectively. Any comorbidity was present in 54% (287/531) of patients and this was unfavorable [adjusted mean difference presence/absence any comorbidity (95% CI): HRQOL -4.4 (-5.8 to -3.0), function 1.9 (0.4-3.3), pain 1.4 (0.6-2.1), TJC 1.3 (0.4-2.2)]. Number of comorbidities and both musculoskeletal (e.g., connective tissue disease) and nonmusculoskeletal comorbidities (e.g., pulmonary and cardiovascular disease) were associated with disease burden. Associations with HRQOL and function were clinically relevant. CONCLUSION: Comorbidities showed clinically relevant associations with disease burden. Therefore, the role of comorbidities in hand OA should be considered when interpreting disease outcomes and in patient management.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".