Effects of Aquatic Therapy and Land-Based Therapy versus Land-Based Therapy Alone on Range of Motion, Edema, and Function after Hip or Knee Replacement: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
PURPOSE: To determine whether aquatic therapy in combination with land-based therapy improves patient outcomes after hip or knee arthroplasty compared with land-based therapy alone. METHODS: For this systematic review, six online databases (MEDLINE, CINAHL, AMED, EMBASE, Cochrane, and PEDro) were searched from the earliest date available until September 2013. Controlled trials published in English in a peer-reviewed journal that compared aquatic therapy in combination with land-based therapy with land-based therapy alone were included; trial quality was assessed using the PEDro scale. Data were presented as standardized mean differences (SMDs), their associated 95% CIs, and meta-analyses. RESULTS: Three small trials of moderate quality were included in the qualitative analysis. Meta-analysis of two of these studies found moderate-quality evidence that aquatic therapy in combination with land-based therapy improves functional outcomes (SMD=0.53; 95% CI, 0.03-1.03), knee range of motion (measured in knee or hip arthroplasty; SMD=0.78; 95% CI, 0.27-1.29), and edema (SMD=-0.66; 95% CI, -1.16 to -0.15) compared with land-based therapy alone. The results for improved functional outcomes were not considered clinically significant. CONCLUSIONS: It is not possible to draw confident conclusions from this review because of the small number of studies of limited quality and the modest differences found. Further studies of sound methodological quality are required to confirm the results. Economic analysis alongside randomized controlled trials is needed to examine the cost-effectiveness of these clinical outcomes.
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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 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.042 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".