Knee Joint Stiffness in Individuals With and Without Knee Osteoarthritis: A Preliminary Study
Bibliographic record
Abstract
STUDY DESIGN: Descriptive, case-matched comparison. OBJECTIVES: To compare the knee joint stiffness and damping coefficients of individuals with knee osteoarthritis (KOA) to those of age- and gender-matched individuals without KOA. A secondary purpose was to investigate relationships between these coefficients and complaints of stiffness in individuals with KOA. BACKGROUND: KOA is a leading cause of disability, and stiffness is a common complaint in individuals with KOA. Yet the most common method of assessing knee joint stiffness is through a self-report questionnaire. METHODS AND MEASURES: Stiffness and damping coefficients at the knee were calculated in 10 volunteers (mean age +/- SD, 64.1+/-15.5 years) with KOA and compared to coefficients from age-and gender-matched individuals without KOA, collected in a previous study (mean age +/- SD, 62.1+/-13.9 years). Stiffness and damping coefficients were calculated from the angular motion of the knee during a relaxed oscillation. Spearman correlation coefficients were calculated between stiffness and damping coefficients and WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) scores for subjects with KOA. RESULTS: Independent 2-tailed t tests revealed significantly larger damping coefficients (P = .035) among those with KOA (95% CI, 0.10-2.32 Nm s/rad). Spearman rank correlations revealed a significant positive relationship (r = .85, P = .003) between the damping coefficient and the stiffness subscore of the WOMAC. CONCLUSION: This study offers preliminary data demonstrating the feasibility of measuring stiffness and damping coefficients in individuals with KOA. Additionally, the damping coefficient is increased in people with KOA when compared to age- and gender-matched individuals without KOA. The damping coefficient appears to be associated with the complaints of stiffness reported by the WOMAC.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".