Associations of Joint Line Tenderness and Patellofemoral Grind With Long‐Term Knee Joint Outcomes: Data From the Osteoarthritis Initiative
Bibliographic record
Abstract
OBJECTIVE: To examine whether joint line tenderness and patellofemoral grind from physical examination were associated with cartilage volume loss, worsening of radiographic osteoarthritis, and the risk of total knee replacement. METHODS: This study examined 4,353 Osteoarthritis Initiative participants. For each measurement of joint line tenderness and patellofemoral grind, the patterns were defined as no (none at baseline and at 1 year), fluctuating (present at either time point), and persistent (present at both time points). Cartilage volume loss and worsening of radiographic osteoarthritis over 4 years were assessed using magnetic resonance imaging and radiographs, and total knee replacement over 6 years was assessed. RESULTS: A total of 35.0% of participants had joint line tenderness, and 15.8% had patellofemoral grind. Baseline patellofemoral grind, but not joint line tenderness, was associated with increased cartilage volume loss (1.08% per year versus 0.96% per year; P = 0.02) and an increased risk of total knee replacement (odds ratio [OR] 1.55 [95% confidence interval (95% CI) 1.11-2.17]; P = 0.01). While the patterns of joint line tenderness were not significantly associated with joint outcomes, participants with persistent patellofemoral grind had an increased rate of cartilage volume loss (1.30% per year versus 0.90% per year; P < 0.001) and an increased risk of total knee replacement (OR 2.10 [95% CI 1.30-3.38]; P = 0.002) compared with those participants without patellofemoral grind. CONCLUSION: Patellofemoral grind, but not joint line tenderness, may represent a clinical marker associated with accelerated cartilage volume loss over 4 years and an increased risk of total knee replacement over 6 years. This simple clinical examination may provide clinicians with an inexpensive way to identify those at higher risk of disease progression who should be targeted for surveillance and management.
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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 | 0.002 | 0.005 |
| 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 | 0.000 | 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".