Short-term morbidity following primary closure, skin grafting and flap reconstruction after surgical resection of extremity soft-tissue sarcomas: Pushing the limits of limb preservation
Bibliographic record
Abstract
INTRODUCTION: Understanding short-term morbidity following extremity soft-tissue sarcoma (ESTS) treatment remains complex due to diverse findings and the absence of a standardized wound complication assessment. This retrospective cohort study evaluated short-term morbidity following primary closure, skin grafting, and flap reconstruction. MATERIALS AND METHODS: All ESTS patients treated in a sarcoma center in the Netherlands from 1-1-2010 until 1-8-2022 were included. Short-term morbidity, defined as a wound complication following surgery, was assessed by the Toronto Sarcoma Flap Score (TSFS). The TSFS is an ordinal scale, where 0 indicates the absence of complications, while 10 signifies reconstructive failure necessitating amputation. Hospital stay duration and readmission rates were also analyzed. RESULTS: Limb preservation was achieved in 128 (97.7 %) of 131 patients. Wound complications occurred in 43 (44.3 %) of patients with primary closure, 8 (57.1 %) with skin grafting and 16 (80.0 %) with flap reconstruction, p = 0.01. Patients undergoing flap reconstructions had higher TSFSs (6 [IQR 7], versus 0 [IQR 3] for primary closure and 3 [IQR 6] for skin grafting), longer duration of hospital stays (14 [IQR 18] days versus 4 [IQR 3] days for primary closure and 5 [IQR 7] days for skin grafting, p < 0.01) and were more frequently readmitted (40.0 %, versus 17.5 % for primary closure and 21.4 % for skin grafting, p = 0.09). CONCLUSION: High limb preservation rates were achieved. Reconstructive surgery allows for the closure of extensive soft-tissue defects following ESTS resection, but it adds to surgical complexity. Patients undergoing flap reconstruction seem to be at a higher risk of short-term morbidity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".