Comparison of xenogeneic acellular dermal matrix and skin grafts in reconstruction of postoperative defects of hypopharyngeal cancer
Bibliographic record
Abstract
Successful reconstruction after tumor resection facilitates rapid recovery and retention of good quality of life, and this is important for a successful operation. This study aimed to analyze and compare the application and efficacy of xenogeneic acellular dermal matrix (xeno-ADM) and abdominal skin graft in hypopharynx reconstruction.This is a retrospective cohort study that included 25 patients with posterior hypopharyngeal wall cancer who underwent partial hypopharyngectomy with laryngeal preservation. The patients were divided into 2 groups according to the repair materials used. Eleven patients were treated with xeno-ADM, and 14 patients with abdominal skin grafts for repairing hypopharyngeal mucosal defects. The intraoperative data, postoperative recovery time of eating function, graft contraction, infection and pharyngeal fistula rate, and 1-year survival rate of the 2 groups were analyzed and compared.Compared with skin grafts group (23.1 ± 5.8 days), the recovery time of eating function in xeno-ADM group was shorter (17.3 ± 6.4 days), (P = .026). Also the number of postoperative hospitalization days were less in the xeno-ADM group (18.5 ± 6.7 days) than in the skin grafts group (24.1 ± 5.6 days) (P = .035). Besides, no significant differences were observed in other comparisons between the 2 groups. Also no obvious rejection and severe graft contraction were observed in both the groups. All patients were successfully decannulated.Both xeno-ADM and abdominal skin grafts demonstrated good effects in the reconstruction of hypopharynx, but the recovery time of eating function in patients with xeno-ADM was faster, which may be due to rapid epithelialization. In addition, it avoids trauma of donor sites.
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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) | 0.000 | 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".