Muscle function, physical function, and gait in older women with and without knee osteoarthritis
Bibliographic record
Abstract
Aim: To compare muscle function of knee extensors, gait parameters, and physical function in older women with and without knee osteoarthritis (KOA) and to associate these parameters to the KOA incidence in this population. Methods: Sixteen older women with KOA (66.9 ± 5.5 years; 74.9 ± 10.0 kg; 157.9 ± 0.9 cm; 30.2 ± 5.0 kg/m2) and fourteen healthy counterparts (control group: CG; 68.8 ± 5.8 years; 68.9 ± 10.5 kg; 158 ± 0.06 cm; 27.4 ± 4.0 kg/m2) participated in this study. Muscle function, physical function, and gait parameters were evaluated in both groups. The Western Ontario and McMaster Index (WOMAC) questionnaire was answered only by the KOA group. A correlation was performed to verify if KOA incidence was associated with muscle function, physical function, and gait parameters. Results: KOA group showed lower peak torque at 60°/s (30%; p = 0.003) and 180°/s (37%; p < 0.001), greater acceleration time at 60°/s (382%; p < 0.001), lower cadence (12.2%; p = 0.002), slower gait speed (19.5%; p < 0.001) and greater stride time (12.5%; p = 0.001) than CG group. However, there was no difference between groups in physical function (p < 0.0045). The KOA incidence presented a negative correlation with peak torque (rho = −0.602; p < 0.001), cadence (rho = −0.533; p = 0.002), gait speed (rho = −0.633; p < 0.001), stride length (rho = −0.517; p = 0.003) and a positive correlation with stride time (rho = 0.533; p = 0.002) and acceleration time (rho = 0.655; p < 0.001). Conclusion: Our findings suggest that knee osteoarthritis may impair the function of the knee extensors muscles and gait parameters. An association between the ability to produce force rapidly and gait speed with the KOA incidence in older women was also observed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".