Subsets of symptomatic hand osteoarthritis in community-dwelling older adults in the United Kingdom: prevalence, inter-relationships, risk factor profiles and clinical characteristics at baseline and 3-years
Bibliographic record
Abstract
OBJECTIVE: To compare the population prevalence, inter-relationships, risk factor profiles and clinical characteristics of subsets of symptomatic hand osteoarthritis (OA) with a view to understanding their relative frequency and distinctiveness. METHOD: 1076 community-dwelling adults with hand symptoms (60% women, mean age 64.7 years) were recruited and classified into pre-defined subsets using physical examination and standardised hand radiographs, scored with the Kellgren & Lawrence (K&L) and Verbruggen-Veys grading systems. Detailed information on selected risk factors was obtained from direct measurement (Body Mass Index (BMI)), self-complete questionnaires (excessive use of hands, previous hand injury) and medical record review (hypertension, dyslipidaemia, type 2 diabetes). Hand pain and disability were self-reported at baseline and 3-year follow-up using Australian/Canadian Osteoarthritis Hand Index (AUSCAN). RESULTS: Crude population prevalence estimates for symptomatic hand OA subsets in the adult population aged 50 years and over were: thumb base OA (22.4%), nodal interphalangeal joint (IPJ) OA (15.5%), generalised hand OA (10.4%), non-nodal IPJ OA (4.9%), erosive OA (1.0%). Apart from thumb base OA, there was considerable overlap between the subsets. Erosive OA appeared the most distinctive with the highest female: male ratio, and the most disability at baseline and 3-years. A higher frequency of obesity, hypertension, dyslipidaemia, and metabolic syndrome was observed in this subset. CONCLUSION: Overlap in the occurrence of hand OA subsets poses conceptual and practical challenges to the pursuit of distinct phenotypes. Erosive OA may nevertheless provide particular insight into the role of metabolic and cardiovascular risk factors in the pathogenesis of OA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".