Hand Examination, Ultrasound, and the Association With Hand Pain and Function in Community‐Based Older Adults
Bibliographic record
Abstract
OBJECTIVE: To describe cross-sectional associations between features observed on ultrasound (US) or clinical joint examination and hand symptoms among community-dwelling older adults (n = 519), and to determine whether such associations are independent of age, sex, body mass index, and other imaging features. METHODS: Hand pain, function, and stiffness were assessed using a visual analog scale (VAS) and the Australian/Canadian Hand Osteoarthritis (AUSCAN) index. Standardized clinical and US examinations were performed, and grip strength was assessed using a dynamometer. Data were analyzed using hurdle and linear models and adjusted for demographic factors and other features. RESULTS: Abnormal findings on joint examination and on US imaging are common in older adults with and without hand pain. Greater numbers of tender joints were associated with greater pain (VAS: β = 2.63 [95% confidence interval (95% CI) 1.88, 3.39]; AUSCAN pain: β = 10.57 [95% CI 4.00, 17.13]), poorer AUSCAN function (β = 4.07 [95% CI 1.28, 6.86]), and poorer grip strength (β = -0.15 [95% CI -0.27, -0.03]). Power Doppler imaging (PDI) synovitis was associated with greater pain (VAS: β = 2.61 [95% CI 1.03, 4.19]; AUSCAN pain: β = 13.07 [95% CI 3.82, 22.32]), but not function. Joint deformity was associated with poorer function (β = 4.51 [95% CI 1.75, 7.26]) and grip strength (β = -0.23 [95% CI -0.40, -0.05]), but not pain. Gray-scale synovitis was associated only with poorer grip strength (β = -0.22 [95% CI -0.41, -0.04]). Associations with function and grip strength were partially mediated by pain. CONCLUSION: Joints that are tender on palpation or have US-identified PDI synovitis are potential treatment targets for hand pain. Treating tender joints and preventing hand deformity is required to improve hand function in community-dwelling older adults.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".