Psychological and Pain Sensitization Characteristics Are Associated With Patellofemoral Osteoarthritis Symptoms: The Multicenter Osteoarthritis Study
Bibliographic record
Abstract
OBJECTIVE: Determine the relation of symptomatic and structural features of patellofemoral osteoarthritis (PFOA) to psychological characteristics and measures of pain sensitization, in older adults with or at risk of knee osteoarthritis (OA). METHODS: ). Participants were grouped based on the presence of PFOA symptoms (anterior knee pain and pain on stairs) and magnetic resonance imaging (MRI) PFOA (full-thickness cartilage lesion with bone marrow lesion): (1) patellofemoral (PF) symptoms with MRI PFOA; (2) PF symptoms without MRI PFOA; (3) MRI PFOA without PF symptoms; and (4) no PF symptoms or MRI PFOA (no PFOA). Relation of PFOA classification to depressive symptoms, catastrophizing, temporal summation (TS) and pressure pain thresholds (PPT) was evaluated using logistic (categorical variables) and linear regression (continuous variables). RESULTS: Compared with no PFOA, those with PF symptoms with or without MRI PFOA had significantly greater odds of depressive symptoms, catastrophizing, and patellar TS (OR range 1.5-2.01), and those with PF symptoms without MRI PFOA had significantly greater odds of wrist TS (OR 1.66). Males with PF symptoms without MRI PFOA had significantly lower pressure PPT at the patella compared with no PFOA and those with MRI PFOA only (no symptoms). There were no significant differences at the wrist for males, or the patella or wrist for females. CONCLUSION: Persons with PFOA symptoms, regardless of MRI PFOA status, are more likely to demonstrate depressive symptoms, catastrophizing, and TS. Males with PFOA symptoms without MRI PFOA demonstrate local hyperalgesia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".