The genetic contribution to severe post-traumatic osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: to compare the combined role of genetic variants loci associated with risk of knee or hip osteoarthritis (OA) in post-traumatic (PT) and non-traumatic (NT) cases of clinically severe OA leading to total joint replacement. METHODS: A total of 1590 controls, 2168 total knee replacement (TKR) cases (33.2% PT) and 1567 total hip replacement (THR) cases (8.7% PT) from 2 UK cohorts were genotyped for 12 variants previously reported to be reproducibly associated with risk of knee or hip OA. A genetic risk score was generated and the association with PT and NT TKR and THR was assessed adjusting for covariates. RESULTS: For THR, each additional genetic risk variant conferred lower risk among PT cases (OR=1.07, 95% CI 0.96 to 1.19; p=0.24) than NT cases (OR 1.11, 95% CI 1.06 to 1.17; p=1.55×10⁻⁵). In contrast, for TKR, each risk variant conferred slightly higher risk among PT cases (OR 1.12, 95% CI 1.07 to 1.19; p=1.82×10⁻⁵) than among NT cases (OR 1.08, 95% CI 1.03 to 1.1; p=0.00063). CONCLUSIONS: Based on the variants reported to date PT TKR cases have at least as high a genetic contribution as NT cases.
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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 | 0.001 |
| 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) | 0.003 | 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".