The Association of Index-to-Ring Finger Ratio With Trapeziometacarpal Joint Osteoarthritis in an Elderly Korean Population
Bibliographic record
Abstract
OBJECTIVE: Index-to-ring finger ratio (IRFR) has been reported to be associated with joint osteoarthritis (OA). We aimed to evaluate the association between IRFR and trapeziometacarpal joint (TMCJ) OA in an elderly Korean population. METHODS: A population-based sample included 604 participants with a mean age of 74.8 years. IRFR was radiographically measured by the ratio of the length of the right second to fourth phalangeal bones ("phalangeal IRFR") and metacarpal bones ("metacarpal IRFR"), and was visually classified as either type 1 (index finger longer than or equal to ring finger) or type 2 (index finger shorter than ring finger). Odds ratios (ORs) for the presence of OA (Kellgren-Lawrence [KL] grade > 1) and for severe OA (KL grade > 2) were analyzed using logistic regression. RESULTS: The phalangeal IRFR averaged 91.3%, the metacarpal IRFR 116.7%, and 304 out of 604 participants (50.3%) had type 2 IRFR. We found TMCJ OA in 112 participants (18.5%), and severe TMCJ OA in 33 participants (5.5%). Presence of TMCJ OA was significantly associated with age (OR 1.04; 95% CI 1.01-1.06) and metacarpal IRFR (OR 0.94; 95% CI 0.88-0.99), and severe TMCJ OA with age (OR 1.08; 95% CI 1.03-1.12) and type 2 IRFR (OR 3.07; 95% CI 1.13-8.33). CONCLUSION: Radiographic IRFR, specifically metacarpal IRFR, was associated with the presence of TMCJ OA, and visual IRFR with severe TMCJ OA in both elderly Korean men and women. The results of this study suggest that IRFR might serve as an easily measurable biomarker to identify patients vulnerable to TMCJ 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".