Knee confidence in youth and young adults at risk of post-traumatic osteoarthritis 3–10 years following intra-articular knee injury
Bibliographic record
Abstract
Objectives To examine differences in knee confidence between individuals with a history of youth sport-related knee injury and uninjured controls. Design Historical cohort study. Methods Participants include 100 individuals who sustained a youth sport-related intra-articular knee injury 3–10 years previously and 100 age-, sex- and sport-matched uninjured controls. Outcomes included: Knee confidence (Knee Osteoarthritis and Outcome Score); fat mass index (FMI; dual-energy X-ray absorptiometry); and weekly physical activity (modified Godin–Shephard Leisure Time Questionnaire). Mean within-pair differences (95% CI) were calculated for all outcomes. Unadjusted and adjusted (FMI and physical activity) conditional (matched-design) logistic regression (OR 95% CI) examined the association between injury history and knee confidence. Results Median age of participants was 22 years (range 15–26) and median age at injury was 16 years (range 9–18). Forty-nine percent (95% CI; 39.0, 59.0) of previously injured participants were bothered by knee confidence, compared to 12% (5.5, 18.5) of uninjured participants. Although there was no between group difference in physical activity, injured participants had higher FMI compared to controls (within-pair difference; (95% CI): 1.05kg/m 2 ; (0.53, 1.57)). Logistic regression revealed that injured participants had 5.0 (unadjusted OR; 95% CI; 2.4, 10.2) and 7.5 times (adjusted OR; 95% CI: 2.7, 21.1) greater odds of being bothered by knee confidence than controls. Conclusions Knee confidence differs between individuals with a previous youth sport-related knee injury and healthy controls. Knee confidence may be an important consideration for evaluating osteoarthritis risk after knee injury and developing secondary prevention strategies.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".