Occupational Kneeling and Meniscal Tears: A Magnetic Resonance Imaging Study in Floor Layers
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between occupational kneeling and degenerative meniscal tears. METHODS: Magnetic resonance imaging (MRI) of both knees was conducted in 92 male floor layers and 49 male graphic designers (referents), with a mean age of 55.6 years (range 42-70 yrs). The presence of grade 3 MRI signal intensities indicating degenerative tears of the anterior, middle, and posterior one-third of the lateral and medial menisci was assessed on 1.5-Tesla MRI scans. The odds ratio (OR) of meniscal tears was determined among floor layers compared to graphic designers. Using logistic regression, models were adjusted for age, body mass index, and knee-straining sports. RESULTS: Degenerative tears were significantly more prevalent in the medial meniscus among floor layers than among graphic designers [OR 2.28, 95% confidence interval (CI) 1.10-4.98] and significantly more floor layers had medial tears in both knees (OR 3.46, 95% CI 1.41-8.48). Tears extending to the tibial aspect and localized in the middle and posterior one-third of the medial meniscus were most prevalent. Lateral meniscal tears were predominantly unilateral and the prevalence of lateral tears did not differ between the 2 study groups. Knee complaints occurred in about 50% of all floor layers, irrespective of the presence of meniscal tears. CONCLUSION: Occupational kneeling increases the risk of degenerative tears in the medial but not the lateral menisci in both knees.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".