Physical Performance Correlates with Self-Reported Physical Function and Quality of Life in Patients at 3 Months after Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Although total knee arthroplasty (TKA) is an effective treatment for knee osteoarthritis, assessment of postoperative outcomes remains unclear. This study aimed to identify postoperative physical performance factors that are correlated with self-reported physical function and quality of life (QoL) at 3 months after unilateral TKA. METHODS: In total, 158 patients who underwent unilateral primary TKA completed performance-based physical function tests at 3 months after surgery, including Stair Climbing Tests (SCT), 6-Minute Walk Tests (6MWT), Timed Up and Go tests (TUG), and instrumental gait analysis. We also measured the isometric knee flexor and extensor strengths of the operated and non-operated knees. Self-reported physical function and QoL were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Euro-QoL Five Dimensions (EQ-5D) questionnaire, respectively. RESULTS: Bivariate analyses showed that WOMAC function and EQ-5D were correlated with age, other self-reported measures, and performance-based measures. The WOMAC pain (r=0.71, p<0.001) showed a high positive correlation. While the EQ-5D (r=-0.7, p<0.001) showed a highly negative correlation with WOMAC function, WOMAC pain (r=-0.67, p<0.001) showed a moderately negative correlation with EQ-5D. In multivariate linear regression analyses, WOMAC pain, peak torque of the flexor of the non-operated knee, and reductions in extensor and stride length were associated with self-reported physical function, whereas WOMAC pain, SCT ascent, and cadence were associated with postoperative QoL. CONCLUSIONS: Physical performance factors were significantly associated with self-reported physical function and QoL in patients at 3 months after unilateral TKA. These findings suggest that performance-based physical function could be used to assess outcomes after TKA.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".