Comparing Short-Term Knee-Related Quality of Life and Associated Clinical Outcomes Between Youth With and Without a Sport-Related Knee Injury
Bibliographic record
Abstract
OBJECTIVE: To compare short-term changes in knee-related quality of life (QOL) and associated clinical outcomes between youth with and without a sport-related knee injury. DESIGN: Prospective cohort study. SETTING: Sport medicine and physiotherapy clinics. PARTICIPANTS: Youth (11-19 years old) who sustained an intra-articular, sport-related knee injury in the past 4 months and uninjured youth of similar age, sex, and sport. INDEPENDENT VARIABLE: Injury history. MAIN OUTCOME MEASURES: Knee-related QOL (Knee injury and Osteoarthritis Outcome Score, KOOS), knee extensor and flexor strength (dynamometry), physical activity (accelerometer), fat mass index (FMI; bioelectrical impedance), and kinesiophobia (Tampa Scale for Kinesiophobia, TSK) were measured at baseline (within 4 months of injury) and at 6-month follow-up. Wilcoxon rank sum tests assessed between-group differences for all outcomes. Regression models assessed the association between injury history and outcome change (baseline to 6-month follow-up), considering sex. The influence of injury type, baseline values, and physiotherapy attendance was explored. RESULTS: Participants' (93 injured youth, 73 uninjured control subjects) median age was 16 (range 11-20) years and 66% were female. Despite greater improvements in KOOS QOL scores (20; 95% confidence interval, 15-25), injured participants demonstrated deficits at 6-month follow-up (z = 9.3, P < 0.01) compared with control subjects, regardless of sex. Similar findings were observed for knee extensor and flexor strength and TSK scores but not for physical activity or FMI. Lower baseline values were associated with greater outcome changes in injured youth. CONCLUSIONS: Youth have worse knee-related QOL, muscle strength, and kinesiophobia early after a sport-related knee injury than control subjects. Despite improvements, deficits persist 6 months later.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".