Noisy knees - knee crepitus prevalence and association with structural pathology: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective: Knee crepitus, the audible crackling or grinding noise during knee movement, can be experienced across the lifespan and create concern for underlying pathology. Our systematic review aims to provide a summary estimate of knee crepitus prevalence and its association with structural pathology among the general population and across knee conditions. Design: Systematic review and meta-analysis. Data sources: Medline, Embase, CENTRAL, Web of Science, SPORTDiscus and CINAHL. Eligibility criteria: Studies evaluating knee crepitus prevalence. Results: 103 studies involving 36 439 participants (42 816 knees) were included. Based on very low certainty evidence, the pooled prevalence of knee crepitus in the general population was 41% (7609 knees; 95% CI 36% to 45%; I2=92.6%); in pain-free persons 36% (852 knees; 95% CI 23% to 50%; I2=91.9%), and in those with osteoarthritis (OA) 81% (18 821 knees; 95% CI 75% to 87%; I2=97.9%). Across other musculoskeletal knee conditions, the pooled prevalence of knee crepitus ranged from 35% (ligament injury; 2740 knees; 95% CI 27% to 44%; I2=95.6%) to 61% (cartilage pathology; 1445 knees; 95% CI 40% to 81%; I2=98.2%). There was low to very low certainty evidence of an association between knee crepitus and radiographic OA (OR 3.79, 95% CI 1.99 to 7.24; 1725 knees; I2=53.0%) and several OA-related features on magnetic resonance imaging (MRI). Conclusion: In this review, knee crepitus was prevalent in the general population, pain-free persons, those with knee OA and other musculoskeletal knee conditions. Knee crepitus was associated with a more than threefold increased odds of radiographic OA diagnosis and several OA-related MRI features. The low to very low certainty of evidence informing our aggregated prevalence estimates and association outcomes suggest that results should be interpreted with caution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".