Using the Barthel Index to Assess Activities of Daily Living after Musculoskeletal Tumour Surgery: A Single-centre Observational Study
Bibliographic record
Abstract
OBJECTIVE: The objective of the current study was to find the factors affecting the activities of daily living, as evaluated by the Barthel Index, at the end of rehabilitation after musculoskeletal tumour surgery. Further, we evaluated whether the Barthel Index correlates with functional scores that are specific to musculoskeletal tumours at final follow-up. METHODS: The activities of daily living of 190 patients who underwent postoperative rehabilitation after surgery to treat musculoskeletal tumours were evaluated at the end of the program using the Barthel Index. Functional evaluation at the time of final follow-up observation was evaluated using the Musculoskeletal Tumour Society Score and the Toronto Extremity Salvage Score. RESULTS: The post-rehabilitation Barthel Index was significantly lower in elderly patients aged more than 60 years and in those with malignant tumours and tumours larger than 10 cm. Malignancy and large tumour size were risk factors for a low Barthel Index. There was significant correlation between the Musculoskeletal Tumour Society Score/Toronto Extremity Salvage Score at final functional evaluation and the Barthel Index at the end of rehabilitation. CONCLUSION: The Barthel Index is a simple method to assess the activities of daily living and can potentially predict disease-specific health-related quality of life at final functional evaluation after musculoskeletal tumour surgery.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".