Functional outcomes after single quadriceps muscle resection in patients with soft tissue sarcoma of the anterior compartment of the thigh
Bibliographic record
Abstract
BACKGROUND: Soft tissue sarcoma (STS) occurs most commonly in the anterior compartment of the thigh. Limb salvage surgery is the mainstay of treatment, however, resections frequently involve muscle sacrifice. This study determines the impact of a single quadriceps muscle sacrifice on daily living functions. This is to assist clinical decision-making relating to when a functional reconstruction should be offered over simple soft tissue coverage for these defects. METHODS: Patients who underwent single quadriceps resection as part of the management of STS between 2010 and 2020 were selected. Three functional tests were performed: Time Up and Go (TUG), Timed Up and Down Stairs (TUDS) and Toronto Extremity Salvage Score (TESS). The results were compared with age/sex matched healthy reference values and literature cohorts of lower limb STS patients. Correlations between the tests and age and follow-up duration were determined by the Spearman's test. RESULTS: The mean TESS, TUG and TUDS results of the 13 patients were 89.6%, 9.8 and 1.01 s/step, respectively. These scores were either similar or significantly better than the comparator values. The TESS score showed no statistical significance compared with patients with no muscle resection. TUG and TUDS scores showed significant positive correlation with each other (ρ = 0.885, P = <0.01) and with age (ρ = 0.646, P = 0.017 and ρ = 0.567, P = 0.043, respectively). CONCLUSION: This is the largest documented case series of single quadriceps resection for STS. The study suggests that this group of patients does not show a functional deficit and therefore does not require functional reconstruction.
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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 | 0.001 |
| 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) | 0.001 | 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".