Effectiveness of balance exercises in the acute post-operative phase following total hip and knee arthroplasty: A randomized clinical trial
Bibliographic record
Abstract
OBJECTIVES: To determine the effectiveness of balance exercises in the acute post-operative phase following total hip arthroplasty or total knee arthroplasty. METHODS: Patients who had total hip arthroplasty (n = 30) or total knee arthroplasty (n = 33) were seen in their residence 1-2 times per week for 5 weeks. At the first post-operative home visit, patients were randomly assigned to either typical (TE, n = 33) or typical plus balance (TE + B, n = 30) exercise groups. The TE group completed seven typical surgery-specific joint range-of-motion and muscle strengthening exercises, while the TE + B group completed the typical exercises plus three balance exercises. Patients were assessed before and 5 weeks after administering the rehabilitation program using four outcome measures: (1) the Berg Balance Scale, (2) the Timed Up and Go test, (3) the Western Ontario McMaster Universities Osteoarthritis Index, and (4) the Activities-specific Balance Confidence Scale. RESULTS: Post-intervention scores for all four outcome measures were significantly improved (p < 0.01) over baseline scores. Patients who participated in the TE + B group demonstrated significantly greater improvement on the Berg Balance Scale and the Timed Up and Go tests (p < 0.01). CONCLUSION: Balance exercises added to a typical rehabilitation program resulted in significantly greater improvements in balance and functional mobility compared to typical exercises alone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".