Light intensity physical activity increases and sedentary behavior decreases following total knee arthroplasty in patients with osteoarthritis
Bibliographic record
Abstract
PURPOSE: To describe objectively measured changes in the volume and pattern of physical activity and sedentary behavior in patients undergoing total knee arthroplasty for osteoarthritis. METHODS: Physical activity and sedentary behavior were measured in patients (13 males, 76 females) with a mean age of 64 years (range 55-80) and end-stage osteoarthritis of the knee, using an accelerometer (ActiGraph GT3X+) for seven consecutive days (24 h/day) prior to, 6 weeks and 6 months after total knee arthroplasty. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), University of California Los Angeles (UCLA) Activity index and range of motion (ROM) were also assessed. RESULTS: Proportion of time spent in sedentary behavior decreased from baseline to 6 months (mean 70.1 vs. 64.0%; p = 0.009) and the interruptions to sedentary behavior improved between baseline and 6 months after total knee arthroplasty (mean 85.0-93.0 breaks/day, p = 0.014). Proportion of time spent in light physical activity increased from baseline to 6 months after total knee arthroplasty (29.0 vs. 34.8%; p = 0.008). There was no change in time spent in moderate to vigorous physical activity after total knee arthroplasty. WOMAC (median 71.0 vs. 4.0, p < 0.001), UCLA (median 2.0 vs. 5.0, p < 0.001) as well as ROM [median (0.0°-90.0°) vs. (0.0°-110°), p < 0.05] scores improved between baseline and 6 months after total knee arthroplasty. CONCLUSION: Clinically, functional improvements in patients following total knee arthroplasty may be assessed by objectively measuring changes in low intensity activity behaviors. The use of accelerometers in this study gives new insights into activity accumulation patterns in a clinical population and highlights their use in determining a behavioral response to an intervention. LEVEL OF EVIDENCE: II.
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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 | 0.000 | 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) | 0.001 | 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".