Relationship between frailty and discharge outcomes in subacute care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: To determine whether level of frailty can predict length of stay, discharge destination, level of participation in physiotherapy, and degree of physical improvement with physiotherapy in older, subacute hospital patients. METHOD: The Edmonton Frail Scale (EFS) was administered to 75 older people in a subacute hospital setting. Relationships between EFS score and a range of other measures, including participation in physiotherapy, Elderly Mobility Scale, discharge destination and length of stay, were examined. RESULTS: Level of frailty did not predict length of stay (rho=-0.13, P=0.24), discharge destination (t=-1.32, P=0.19), raw change on the Elderly Mobility Scale (rho=0.06, P=0.61) or rate of change on the Elderly Mobility Scale (r=-0.001, P=0.98). In addition, participants with a high level of frailty were more likely to achieve a satisfactory level of participation in physiotherapy sessions than those with low frailty (OR 1.43, P=0.02). CONCLUSION: Level of frailty measured with the EFS was not a useful predictor of rehabilitation and discharge outcomes for older people in subacute care. These results do not support the routine use of the EFS to measure frailty in subacute care. WHAT IS KNOWN ABOUT THIS TOPIC? In a community-dwelling population, level of frailty has been found to predict poor outcomes from surgery, falls, fractures, disability, need for residential care and mortality. However, little is known about the impacts of frailty in a subacute setting, nor how frailty could best be measured in this setting. WHAT DOES THIS PAPER ADD? The use of the EFS as a predictive tool was not supported by the results of this exploratory study. WHAT ARE THE IMPLICATIONS FOR PRACTITIONERS? Alternative frailty measures may be more suitable than the EFS for patients in a subacute setting.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it