The Relationship Between Knee Moments and Function with Western Ontario and McMaster Universities in Moderate Knee Osteoarthritis
Bibliographic record
Abstract
Introduction: The knee is the most affected weight-bearing joint by osteoarthritis. The kinetics parameters are correlated with the progression of knee osteoarthritis (KOA). This study was done to investigate the relationship between kinetics parameters and functional tests with Western Ontario and McMaster Universities osteoarthritis index (WOMAC) scores in people with moderate KOA. Materials and Methods: Twenty- three participants with moderate KOA participated in this study. Gait analysis involved the measurement of the external peak knee adduction moment (PKAM), peak knee flexion moment (PKFM), knee adduction moment impulse (KAM impulse), and knee flexion moment impulse (KFM impulse) during level walking. Functional tests included timed up and go (TUG) and figure of eight walkings (FO8W) tests. Pearson’s correlation coefficient was used to investigate the correlation between kinetics parameters and functional test scores with WOMAC total scores and sub-scores. Results: There was a significant inverse correlation between the first PKAM and WOMAC total score and pain sub-score (r=-0.43 P=0.03 and r=-0.6 P=0.002, respectively). Also, there was a significant inverse correlation between the second PKAM and pain sub-score (r=-0.46 P=0.02). There was no significant correlation between functional tests and WOMAC scores. Conclusion: The low score of the WOMAC in the moderate KOA should not be attributed to the low level of joint knee moments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".