The Feasibility of performing resistance exercise with acutely ill hospitalized older adults
Bibliographic record
Abstract
BACKGROUND: For older adults, hospitalization frequently results in deterioration of mobility and function. Nevertheless, there are little data about how older adults exercise in the hospital and definitive studies are not yet available to determine what type of physical activity will prevent hospital related decline. Strengthening exercise may prevent deconditioning and Pilates exercise, which focuses on proper body mechanics and posture, may promote safety. METHODS: A hospital-based resistance exercise program, which incorporates principles of resistance training and Pilates exercise, was developed and administered to intervention subjects to determine whether acutely-ill older patients can perform resistance exercise while in the hospital. Exercises were designed to be reproducible and easily performed in bed. The primary outcome measures were adherence and participation. RESULTS: Thirty-nine ill patients, recently admitted to an acute care hospital, who were over age 70 [mean age of 82.0 (SD= 7.3)] and ambulatory prior to admission, were randomized to the resistance exercise group (19) or passive range of motion (ROM) group (20). For the resistance exercise group, participation was 71% (p = 0.004) and adherence was 63% (p = 0.020). Participation and adherence for ROM exercises was 96% and 95%, respectively. CONCLUSION: Using a standardized and simple exercise regimen, selected, ill, older adults in the hospital are able to comply with resistance exercise. Further studies are needed to determine if resistance exercise can prevent or treat hospital-related deterioration in mobility and function.
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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 | 0.002 | 0.007 |
| 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) | 0.002 | 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".