Home-Based Multidisciplinary Rehabilitation following Hip Fracture Surgery: What Is the Evidence?
Bibliographic record
Abstract
Objective. To determine the effects of multidisciplinary home rehabilitation (MHR) on functional and quality of life (QOL) outcomes following hip fracture surgery. Methods. Systematic review methodology suggested by Cochrane Collboration was adopted. Reviewers independently searched the literature, selected the studies, extracted data, and performed critical appraisal of studies. Summary of the results of included studies was provided. Results. Five studies were included. Over the short-term, functional status and lower extremity strength were better in the MHR group compared to the no treatment group (NT). Over the long-term, the MHR group showed greater improvements in balance confidence, functional status, and lower extremity muscle strength compared to NT group, whereas the effect on QOL and mobility was inconsistent across the studies. Several methodological issues related to study design were noted across the studies. Conclusion. The MHR was found to be more effective compared to the NT in improving functional status and lower extremity strength in patients with hip fracture surgery. Results of this review do not make a strong case for MHR due to high risk of bias in the included studies. Further research is required to accurately characterize the types of disciplines involved in MHR and frequency and dosage of intervention.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".