A specific arm-interval exercise program could improve the health status and walking ability of elderly patients after total hip arthroplasty: a pilot study
Bibliographic record
Abstract
OBJECTIVE: To investigate the influence of an arm-interval exercise program for the upper limbs on health status and walking ability in elderly patients after total hip arthroplasty. DESIGN: A randomized controlled investigation. After surgery, a control group started a general rehabilitation program, and a training group combined it with an arm-interval exercise program. SUBJECTS: Fourteen patients (age 75.1 +/- 4.8 years) were randomly assigned to the control group (n = 7) and the training group (n = 7). METHODS: A Western Ontario and MacMaster University (WOMAC) Osteoarthritis Index was completed and an incremental exercise test on an arm crank ergometer was also performed 1 month before (T(-1)) and 2 months after surgery (T2). Moreover, a 6-minute walk test was performed at T2. RESULTS: Both groups significantly improved all dimensions of WOMAC, except in WOMAC physical function subscale in the control group. The training group covered a significantly longer distance in the walking test than the control group and also presented significantly higher VO2 peak value at T2. Correlation analyses indicate that VO2 peak value and the distance covered in the 6-minute walking test were significantly associated with functional status. After calculating the ratio distance covered/score at WOMAC physical function, we observed a significantly higher ratio value in the training group than in the control group. CONCLUSION: Preliminary results indicate that the improvement in physical fitness and functional status of the training group seems to be associated with better health status.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".