Assessment of strength of individual digits in persons with osteoarthritis of the hand
Bibliographic record
Abstract
Introduction The purpose of this study was to determine the extent to which individual digit strength measures correlate with overall hand strength, pain and function in persons with osteoarthritis (OA) of the hand, and thereby judge whether individual digit strength measures are relevant to the clinical assessment of hand disability in this population. Methods One hundred and four community-dwelling persons with OA of the dominant hand (84 women) participated in this cross-sectional study. Correlations between measures of hand strength (grip: digit and total; pinch: tripod, wide key and narrow key), dexterity and self-reported pain and function (subscales of the Patient-Rated Wrist and Hand Evaluation) were investigated. Results Although OA involved radial digits more than ulnar digits, radial digit strength contributes more to total grip (59% versus 41%). Correlations between total grip and digit strength varied from excellent (digits 3 and 4: r = 0.93 and 0.88, respectively) to moderate (digits 2 and 5: r = 0.75 and 0.74, respectively). Correlations between pinch and individual digit strength (digits 2 and 3) were moderate ( r = 0.66–0.74). Correlations between measures of different constructs (strength, pain and physical function) did not exceed 0.41. Conclusions Individual digit strength is not linked with OA involvement of that digit. At most, strength of individual digits explains just over half of the variance in total grip strength and pinch strength. Assessment of individual digit grip strength appears to provide unique information regarding hand disability in persons with 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".