Is body mass index associated with patellofemoral pain and patellofemoral osteoarthritis? A systematic review and meta-regression and analysis
Bibliographic record
Abstract
BACKGROUND: Patellofemoral pain (PFP) occurs frequently, and may be related to patellofemoral osteoarthritis (PFOA). Obesity is associated with increased risk of knee OA. This systematic review involves a meta-regression and analysis to determine the relationship between body mass index (BMI) and PFP and PFOA, and to determine the link between BMI and interventional outcomes. METHODS: We searched seven electronic databases and reference lists of relevant papers and systematic reviews, for cross-sectional, prospective, human-based observational and interventional studies reporting BMI in individuals with PFP or PFOA compared to healthy controls. Two independent reviewers appraised methodological quality (epidemiological appraisal instrument). Where possible, data from prospective studies were pooled to conduct meta-regression and case-control, and intervention studies to conduct meta-analysis using the following categories: adolescents with PFP, adults with PFP and PFOA. RESULTS: 52 studies were included. We found greater BMI in adults with PFP (standardised mean difference: 0.24, 95% CI 0.12 to 0.36) and PFOA (0.73, 0.46 to 0.99) compared to healthy controls, but not in adolescents with PFP (-0.19, -0.56 to 0.18). We also observed statistical trends (p<0.10) towards higher BMI being a predictor for development of PFP in adults (0.34, -0.04 to 0.71). No significant link between BMI and intervention outcomes in adults with PFP was identified. CONCLUSIONS: Higher BMI is present in PFP and PFOA, but not in adolescents with PFP. PROSPERO REGISTRATION NUMBER: CRD42015024812.
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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 | 0.023 | 0.065 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.041 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".