Physical functioning, pain and quality of life after amputation for musculoskeletal tumours
Bibliographic record
Abstract
Patients who have limb amputation for musculoskeletal tumours are a rare group of cancer survivors. This was a prospective cross-sectional survey of patients from five specialist centres for sarcoma surgery in England. Physical function, pain and quality of life (QOL) outcomes were collected after lower extremity amputation for bone or soft-tissue tumours to evaluate the survivorship experience and inform service provision. Of 250 patients, 105 (42%) responded between September 2012 and June 2013. From these, completed questionnaires were received from 100 patients with a mean age of 53.6 years (19 to 91). In total 60 (62%) were male and 37 (38%) were female (three not specified). The diagnosis was primary bone sarcoma in 63 and soft-tissue tumour in 37. A total of 20 tumours were located in the hip or pelvis, 31 above the knee, 32 between the knee and ankle and 17 in the ankle or foot. In total 22 had hemipelvectomy, nine hip disarticulation, 35 transfemoral amputation, one knee disarticulation, 30 transtibial amputation, two toe amputations and one rotationplasty. The Toronto Extremity Salvage Score (TESS) differed by amputation level, with poorer scores at higher levels (p < 0.001). Many reported significant pain. In addition, TESS was negatively associated with increasing age, and pain interference scores. QOL for Cancer Survivors was significantly correlated with TESS (p < 0.001). This relationship appeared driven by pain interference scores. This unprecedented national survey confirms amputation level is linked to physical function, but not QOL or pain measures. Pain and physical function significantly impact on QOL. These results are helpful in managing the expectations of patients about treatment and addressing their complex needs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".