Cardiorespiratory Responses to Rehabilitation in Older Adults Following Hip Fracture
Bibliographic record
Abstract
Patients with hip fracture are unable to do vigorous exercise with their lower body thus it is necessary to consider upper body exercise during their rehabilitation programs. It is important to establish methods of assessing aerobic fitness in order to accurately prescribe aerobic exercise for training purposes. Arm exercise testing provides an estimate of aerobic capacity in people with lower extremity dysfunction where true maximal heart rate and oxygen uptake may not be attainable with standard leg exercise testing. PURPOSE: To determine the effect of in-patient rehabilitation on cardiovascular function (VO2peak) in patients following hip fracture. METHODS: Incremental exercise tests to volitional exhaustion were carried out on a custom-built arm crank ergometer within 48 h of admission and again 48 h before discharge. Data were collected on four patients with hip fracture (age 80 ± 7 y, range 62–84 y) who attended physiotherapy and occupational therapy sessions 5 times/week during rehabilitation (length of stay = 24 ± 4 days). RESULTS: The change in VO2peak between admission and discharge (+22.4%) was significant (p = .037). On discharge, there were significant correlations (p<01) between VO2peak and the clinical outcome measures (Timed Up and Go test, Berg Balance Scale, 2-minute walk, 10-minute walk). CONCLUSIONS: Preliminary results indicate that standard rehabilitation therapy produces an increase in aerobic capacity as measured by upper arm ergometry. Further testing evaluating the influence of an upper body exercise program on cardiovascular function in conjunction with standard rehabilitation is warranted.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".