Early Detection of First Carpometacarpal Joint Osteoarthritis Using Magnetic Resonance Imaging Assessment in Women With High Hypermobility Scores
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to explore association between hypermobility and osteoarthritis (OA) at the first carpometacarpal (CMC) joint, using magnetic resonance imaging (MRI) to identify early change in women at high risk of developing OA but without yet established diagnoses. METHODS: For this observational study, 33 women (aged 30-50 years) with self-reported history of maternal hand OA but without personal diagnoses of OA were recruited. Participants completed a 5-point hypermobility questionnaire. The 20 participants with 2 or more positive responses were categorized with "high hypermobility scores." The remaining 13 were categorized with "low hypermobility scores." Data collection included functional index, hand pain measure, parity, smoking status, and body mass index. Each participant underwent dominant hand radiographic and MRI examination. Imaging studies were interpreted by assessors blinded to hypermobility score categorization. RESULTS: No significant differences in age, body mass index, parity, functional index, or pain scores were observed between higher and lower hypermobility score groups. Similarly, there were no significant differences between groups for radiographic changes. However, significantly higher proportions of women with higher hypermobility scores were observed on MRI to have abnormalities of trapezium cartilage (75% vs. 38%), metacarpal cartilage (80% vs. 38%), and trapezium bone (70% vs. 31%); p < 0.05 for all. CONCLUSIONS: First CMC joint structural abnormalities were more frequently observed in women with higher hypermobility scores. Identification of early preradiographic changes in this group supports the concept that early-life joint laxity may contribute to future OA predisposition. Magnetic resonance imaging may be a preferred imaging test for detection of early cartilage changes in people at high risk of CMC joint 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 | 0.000 |
| 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".