Bibliographic record
Abstract
Purpose: This study was done to analyze the effects of rehabilitation therapy(RT) on knee muscle strength(KMS) in the elderly with total knee arthroplasty(TKA) through meta-analysis of randomized or non-randomized studies published or unpublished in domestic and foreign country between 1980 and 2012. Methods: From electronic database 767 studies were retrieved, of which 18 studies met the inclusion criteria. The data basis included Medline, CINAHL, KERIS, National Library of Korea, National Assembly Library, Korean Society of Nursing Science, Korean Society of Adult Nursing, Korean Academy of Fundamentals of Nursing, Korean Academic Society of Nursing Education, Korean Society of Muscle and Joint Health web sites. Words for the search were ‘TKA’ or ‘TKA and rehabilitation’ or ‘TKA and KMS’. The data were analyzed characteristics, effect size, effect variables and measurement tools of RT for KMS using the RevMan 5.3 program of the Cochrane library. Results: Type of RT was exercise therapy(range of motion exercise, aerobic exercise and machine-based exercise etc) or non-exercise therapy(education program, electric muscle stimulation, imagination therapy, musical therapy, massage etc). Effect variables for KMS were flexion, extension, ROM, peak torque, muscle strength and muscle function etc. Measurement tools were CPM(Contineous Passive Motion) machine, dynamometer, goniometer, knee isokinetic(KI), HSS(Hospital for Special Surgery), KSS(Knee Society Scale), LS(Lysholm Scale) and WOMAC(Western Ontario and McMaster Universities Osteoarthritis Index). Total effect size of RT on KMS was significant. Effect sizes of RT on KMS were significant for dynamometer, KI and KSS but not significant for CPM machine, goniometer, HSS, LS and WOMAC. Conclusion: The results of this study suggest that RT is effective for KMS in the elderly with TKA and dynamometer/KI/KSS are safe tools for KMS measurement. But there’s need to statement completely contents of RT and be careful for selection of KMS measurement tools.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".