How Are Obesity and Body Composition Related to Patellar Cartilage? A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: The aim of this review was to systematically examine the evidence for an association between measures of obesity [weight and body mass index (BMI)] and body composition (fat mass and fat-free mass) and patellar cartilage, assessed using magnetic resonance imaging. METHODS: Three electronic databases (MEDLINE, EMBASE, and CINAHL) were searched up to April 2016 using full text and MeSH terms to identify studies examining the associations between obesity and body composition, and patellar cartilage. Two independent reviewers extracted the data and assessed the methodological quality of included studies. RESULTS: Seventeen studies were included: 5 cross-sectional, 10 cohort studies measuring outcomes at 2 timepoints, and 2 longitudinal studies assessing outcome only at the timepoint. Eleven studies were of high or moderate quality. In asymptomatic middle-aged adults, elevated body weight and BMI were systematically associated with worse patellofemoral cartilage scores. There was more consistent evidence for patellar cartilage defects than patellar cartilage volume, particularly in women. Increased BMI was also consistently associated with increased cartilage loss in longitudinal studies, although not all attained statistical significance. CONCLUSION: There is a need for more high-quality research to confirm these findings and to better explain the relative contributions of metabolic and biomechanical factors to the initiation of patellofemoral osteoarthritis, to devise effective strategies to manage this common and disabling condition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".