Is there a role for rehabilitation streaming following total knee arthroplasty? Preliminary insights from a randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: To determine whether total knee arthroplasty recipients demonstrating comparatively poor mobility at entry to rehabilitation and who received supervised therapy, had better rehabilitation outcomes than those who received less supervision. DESIGN: Retrospective analysis of randomized trial data. PATIENTS: Total knee arthroplasty participants randomized to supervised (n = 159) or home-based therapy (n = 74). METHODS: Participants were dichotomized based on mean target 6-min walk test (6MWT) pre-therapy (second post-surgical week). Absolute and change in 6MWT and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain and Function subscales amongst low performers in the supervised (n = 89) and unsupervised (n = 36) groups were compared, as were high performers in the supervised (n = 70) and unsupervised (n = 38) groups. RESULTS: Low performers in the unsupervised compared with the supervised group demonstrated significantly poorer 6MWT scores (absolute δ = 8.5%, p = 0.003; change δ = 8.1%, p = 0.007) when therapy ceased (10 weeks post-surgery). No differences in 6MWT were observed between the high performing subgroups or in the recovery of WOMAC subscales between any subgroups. CONCLUSION: Individuals manifesting comparatively poor mobility at the commencement of physiotherapy may recover their mobility, but not perceived function, more quickly if streamed to supervised therapy.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".