Frequency of multisite non-hand joint involvement in patients with thumb-base osteoarthritis, and associations with functional and patient-reported outcomes
Bibliographic record
Abstract
Purpose: In OA studies, the focus often is on an index-joint; other affected joint sites are often overlooked. In this thumb-base OA study, we documented the frequency of symptomatic non-hand joint sites and investigated whether their count was associated with thumb-specific functional and patient-reported outcome measures. Design: Patients seeking care for thumb-base OA (conservative or surgical) were included. A patient-completed questionnaire captured sociodemographic and health characteristics, symptomatic hand and non-hand joint sites, and outcome measures (thumb-base pain intensity, symptoms and disability (TASD) and upper-extremity disability/symptoms (quickDASH)). Grip and pinch strength were measured. Linear regressions examined the association between each outcome and symptomatic joint site count, adjusted for several covariates. Results: The mean age of the 145 patients was 62 years, 72% were female. Mean symptomatic non-hand joint site count was 3.6. Ten percent reported only their hands as symptomatic; 30% reported 2-3 other symptomatic sites, and 49% reported 4+. From cross-sectional multivariable analyses, a higher symptomatic non-hand joint site count was associated with worse scores for all patient-reported outcomes and grip strength. Every unit increase in joint site count (49% had a 4+ count) was associated with a 2.1-3.3 unit increase (worse) in patient-reported outcome scores (all p < 0.02). Conclusions: In this sample, nearly 80% of patients had 2+ symptomatic non-hand joint sites. These symptoms were associated with worse thumb- and hand-specific outcomes, suggesting a need for awareness of whole body OA burden, with implications for outcome score interpretations, study designs, and provision of care in thumb-base 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 | 0.003 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".