Risk factors for knee osteoarthritis after traumatic knee injury: a systematic review and meta-analysis of randomised controlled trials and cohort studies for the OPTIKNEE Consensus
Bibliographic record
Abstract
OBJECTIVE: To identify and quantify potential risk factors for osteoarthritis (OA) following traumatic knee injury. DESIGN: Systematic review and meta-analyses that estimated the odds of OA for individual risk factors assessed in more than four studies using random-effects models. Remaining risk factors underwent semiquantitative synthesis. The modified GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach for prognostic factors guided the assessment. DATA SOURCES: MEDLINE, EMBASE, CENTRAL, SPORTDiscus, CINAHL searched from inception to 2009-2021. ELIGIBILITY: Randomised controlled trials and cohort studies assessing risk factors for symptomatic or structural OA in persons with a traumatic knee injury, mean injury age ≤30 years and minimum 2-year follow-up. RESULTS: Across 66 included studies, 81 unique potential risk factors were identified. High risk of bias due to attrition or confounding was present in 64% and 49% of studies, respectively. Ten risk factors for structural OA underwent meta-analysis (sex, rehabilitation for anterior cruciate ligament (ACL) tear, ACL reconstruction (ACLR), ACLR age, ACLR body mass index, ACLR graft source, ACLR graft augmentation, ACLR+cartilage injury, ACLR+partial meniscectomy, ACLR+total medial meniscectomy). Very-low certainty evidence suggests increased odds of structural OA related to ACLR+cartilage injury (OR=2.31; 95% CI 1.35 to 3.94), ACLR+partial meniscectomy (OR=1.87; 1.45 to 2.42) and ACLR+total medial meniscectomy (OR=3.14; 2.20 to 4.48). Semiquantitative syntheses identified moderate-certainty evidence that cruciate ligament, collateral ligament, meniscal, chondral, patellar/tibiofemoral dislocation, fracture and multistructure injuries increase the odds of symptomatic OA. CONCLUSION: Moderate-certainty evidence suggests that various single and multistructure knee injuries (beyond ACL tears) increase the odds of symptomatic OA. Risk factor heterogeneity, high risk of bias, and inconsistency in risk factors and OA definition make identifying treatment targets for preventing post-traumatic knee OA challenging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.049 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".