Characteristics of Accelerated Hand Osteoarthritis: Data from the Osteoarthritis Initiative
Bibliographic record
Abstract
OBJECTIVE: We aimed to determine whether hand joints develop an accelerated form of osteoarthritis (OA) and to characterize individuals who develop accelerated hand osteoarthritis (AHOA). METHODS: We evaluated 3519 participants in the Osteoarthritis Initiative with complete data for baseline and 48-month radiographic hand osteoarthritis (HOA). One reader scored posteroanterior radiographs of the dominant hand using a modified Kellgren-Lawrence (KL) scale and another reader scored the presence of central or marginal erosions. A third reader read images flagged for signs of diseases other than OA. We defined AHOA as ≥ 1 joints that progressed from a KL grade of 0 or 1 at baseline to KL grade 3 or 4 at 48 months. RESULTS: The definition of AHOA was met by 1% over 4 years: 37 hands had 1 joint affected and 1 hand had 2 joints affected. At baseline, adults who developed AHOA were more likely to have hand pain (37% vs 22%), radiographic HOA (71% vs 36%), as well as central (22% vs 7%) and marginal erosions (11% vs 2%) in other joints compared to those without AHOA. Adults with AHOA were more likely to develop new erosions over 48 months (central 35%, marginal 5%) than those without AHOA (central 5%, marginal 1%). The most common locations of accelerated OA were the second metacarpophalangeal and first carpometacarpal joint. CONCLUSION: Accelerated OA can occur in the hand, especially among digits commonly used for pinching and fine motor skills.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".