A randomized trial to compare exercise treatment methods for patients after total knee replacement: protocol paper
Bibliographic record
Abstract
BACKGROUND: Although the outcome of total knee replacement (TKR) is favorable, surgery alone fails to resolve the functional limitations and physical inactivity that existed prior to surgery. Exercise is likely the only intervention capable of improving these persistent limitations, but exercises have to be performed with intensity sufficient to promote significant changes, at levels that cannot be tolerated until later stages post TKR. The current evidence is limited regarding the effectiveness of exercise at a later stage post TKR. To that end, this study aims to compare the outcomes of physical function and physical activity between 3 treatment groups: clinic-based individual outpatient rehabilitative exercise during 12 weeks, community-based group exercise classes during 12 weeks, and usual medical care (wait-listed control group). The secondary aim is to identify baseline predictors of functional recovery for the exercise groups. METHODS/DESIGN: This protocol paper describes a comparative effectiveness study, designed as a 3-group single-blind randomized clinical trial. Two hundred and forty older adults who underwent TKR at least 2 months prior will be randomized into one of the three treatment approaches. Data will be collected at baseline, 3 months, and 6 months. The wait-listed control group will be randomized to one of the 2 exercise groups after 6 months of study participation, and will complete a 9-month follow-up. Primary outcome is physical function measured by the Western Ontario and McMaster Universities Osteoarthritis Index Physical Function Subscale (WOMAC-PF). Physical function is also measured by performance-based tests. Secondary outcomes include performance-based tests and physical activity assessed by a patient-reported survey and accelerometry-based physical activity monitors. Exploratory outcomes include adherence, co-interventions, attrition, and adverse events including number of falls. Linear mixed models will be fitted to compare the changes in outcome across groups. Logistic regression will identify patient characteristics that predict functional recovery in the exercise groups. Instrumental variable methods will be used to estimate the efficacy of the interventions in the presence of non-compliance. DISCUSSION: Results will inform recommendations on exercise programs to improve physical function and activity for patients at the later stage post TKR and help tailor interventions according with patients' characteristics. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT02237911.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".