Efficacy of continuous passive motion following total knee arthroplasty: a metaanalysis.
Bibliographic record
Abstract
OBJECTIVE: The objective of this metaanalysis is to examine the effectiveness of continuous passive motion (CPM) following total knee arthroplasty (TKA). METHODS: This metaanalysis used the methodology proposed by the Cochrane Collaboration. RESULTS: This review of 14 studies (952 patients) found significant improvements in active knee flexion and analgesic use 2 weeks postoperatively with the use of CPM and physiotherapy (PT) compared to PT alone. In addition, length of hospital stay and need for knee manipulations were significantly decreased in the CPM group. Not enough data were available to compare the degree of knee flexion applied or number of hours of application of CPM. However, significant results were not found for other comparisons such as short term CPM application versus longterm CPM application and wide treatment range versus small treatment range for the outcomes of active knee flexion, passive knee flexion and extension, presence of a fixed flexion deformity, use of analgesic, or total knee range of motion. CONCLUSION: CPM combined with PT may offer beneficial results for patients post-TKA. However, the potential benefits will need to be carefully weighed against the inconvenience and expense of CPM. More research is necessary to assess the differences in effectiveness with different characteristics of application such as total duration of treatment and intensity of CPM interventions.
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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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.039 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".