Risk factors for the development of knee osteoarthritis across the lifespan: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To identify and quantify risk factors for incident knee osteoarthritis (KOA) across the lifespan. METHODS: This systematic review and meta-analysis identified eligible studies from seven electronic databases and three registries. Longitudinal cohort studies or randomised controlled trials evaluating participants who developed incident symptomatic and/or radiographic KOA were included. Two independent reviewers completed data screening and extraction. Estimates were pooled using a random effects model and reported as odds ratio (OR), hazard ratio, or risk ratio and corresponding 95% confidence intervals (95% CI). Grading of Recommendations, Assessment, Development and Evaluation was used to determine the certainty of evidence. Population attributable fractions were calculated, including risk factors significantly associated with radiographic KOA based on the pooled meta-analysis and where we could determine communality scores using existing clinical datasets. RESULTS: We identified 131 studies evaluating > 150 risk factors. Previous knee injury, older age and high bone mineral density were associated with an increased risk of incident radiographic KOA based on the pooled analysis [OR (95% CI): 2.67 (1.41, 5.05), 1.15 (1.00, 1.33) and 1.82 (1.12, 2.94), respectively], with moderate-to-high certainty. Two risk factors (overweight/obesity and previous knee injury) accounted for 14% of incident radiographic KOA. Other modifiable risk factors, including occupational physical activity, also contribute to radiographic or symptomatic KOA. CONCLUSION: Novel strategies addressing known modifiable risk factors including overweight/obesity, knee injuries and occupational physical activity are needed to reduce overall burden of KOA. SYSTEMATIC REVIEW REGISTRATION: PROSPERO ID: CRD42023391187.
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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 | 0.022 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".