Superficial Soft-Tissue Sarcomas Rarely Require Advanced Soft-Tissue Reconstruction following Resection
Bibliographic record
Abstract
Objective: Soft-tissue sarcomas are most frequently located deep within myofascial compartments. Superficial soft-tissue sarcomas (S-STS) are relatively less common and may be managed differently than deep sarcomas because generous resection margins are often possible without sacrificing critical structures. We sought to investigate the frequency and types of soft-tissue reconstructive procedures that are required following excision of S-STS. Methods: We reviewed 457 consecutively treated patients with S-STS with a minimum 2-year follow-up from our prospectively maintained database between 1989 and 2009. Results: Mean follow-up was 10.5 years (range, 2–23). Four hundred twenty-one tumors (91%) were excised with negative margins, 38 (8.3%) had microscopically positive margins, and three (0.7%) had grossly positive margins. One patient required an amputation. In 271 (58%) patients, the wounds were closed primarily. In comparison, 93 patients (20%) required a rotation flap, 70 (15%) required a split-thickness skin graft, and 23 (5%) underwent a free tissue transfer (ie, advanced reconstructive procedure). The overall complication rate was 12%, although 43% of patients undergoing free tissue transfer developed complications ( P = 0.04). An unplanned excision before referral to our center was a risk factor for local recurrence ( P = 0.03) when residual tumor was recovered in the reexcision specimen pathologically. Conclusions: Although concern about the morbidity associated with a free tissue transfer (ie, advanced reconstructive procedure) may potentially limit the adequacy of resection in some patients with S-STS, the results of this study showed that the majority of patients had complete excisions with negative margins and primary closure. Obtaining a negative margin when excising a known or suspected S-STS rarely requires an advanced reconstructive procedure and almost never results in loss of limb.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.004 | 0.001 |
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".