Infrapatellar fat pad in the knee: is local fat good or bad for knee osteoarthritis?
Bibliographic record
Abstract
INTRODUCTION: Recent studies regarding the infrapatellar fat pad (IPFP) mainly focus on the roles of the cells derived from the IPFP. There have been few clinical or epidemiological studies reporting on the association between the IPFP and knee osteoarthritis (OA). Our objective is to generate hypotheses regarding the associations between IPFP maximum area and knee OA measures in older adults. METHODS: A total of 977 subjects between 50 and 80 years of age (mean, 62.4 years) participated in the study. Radiographic knee osteophyte and joint space narrowing (JSN) were assessed using the Osteoarthritis Research Society International atlas. T1- or T2-weighted fat suppressed magnetic resonance imaging (MRI) was utilized to assess IPFP maximum area, cartilage volume, cartilage defects, and bone marrow lesions (BMLs). Knee pain was assessed by self-administered Western Ontario McMaster Osteoarthritis Index (WOMAC) questionnaire. RESULTS: After adjustment for potential confounders, IPFP maximum area was significantly associated with joint space narrowing (odds ratio (OR): 0.75, 95% confidence interval (CI): 0.62 to 0.91 (medial), 0.77, 95% CI: 0.62 to 0.96 (lateral)) and medial osteophytes (OR: 0.52, 95% CI: 0.35 to 0.76), knee tibial and patellar cartilage volume (β: 56.9 to 164.9 mm3/cm2, all P <0.001), tibial cartilage defects (OR: 0.58, 95% CI: 0.41 to 0.81 (medial), 0.53, 95% CI: 0.40-0.71 (lateral)), any BMLs (OR: 0.77, 95% CI: 0.63 to 0.94), and knee pain on a flat surface (OR: 0.79, 95% CI: 0.63 to 0.98). IPFP maximum area was negatively, but not significantly, associated with femoral cartilage defects, lateral tibiofemoral BMLs, and total knee pain or other knee pain subscales. CONCLUSION: IPFP maximum area is beneficially associated with radiographic OA, MRI structural pathology and knee pain on a flat surface suggesting a protective role for IPFP possibly through shock absorption. Consequently, we must pay special attention to IPFP in the clinical settings, avoiding resection of normal IPFP in knee surgery.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".