Preventive Effect of Human Acellular Dermal Matrix on Post-thyroidectomy Scars and Adhesions
Bibliographic record
Abstract
BACKGROUND: Acellular dermal matrix (ADM) has been used for antiadhesion formation along with wound healing in various surgical fields. OBJECTIVE: The aim is to assess the efficacy of ADM implantation in the prevention of postoperative scars and adhesions after conventional, open, total thyroidectomy. MATERIALS AND METHODS: Forty-four patients with papillary thyroid carcinoma undergoing thyroidectomy were randomly assigned to the study (ADM implantation) or control group (without ADM). Global photographic assessment, Vancouver scar scale (VSS), objective scar assessment, and swallowing impairment index were assessed at baseline, immediately after surgery, and at 1 and 2 months after surgery. RESULTS: Nineteen control and 20 study group participants completed the study. The mean VSS score of the study group was significantly lower than the controls at both 1 month (3.06 ± 1.25 vs 4.41 ± 1.54, respectively) and 2 months (2.76 ± 1.56 vs 4.35 ± 1.58, respectively) after surgery. Scar quality measures (mean melanin and erythema indexes) were significantly lower in the study group compared with controls. Study group participants had significantly lower swallowing impairment scores than controls. The mean postoperative hospitalization of both groups was not significantly different. CONCLUSION: Acellular dermal matrix-assisted implants appear to improve post-thyroidectomy scar and swallowing impairments without delays in operation time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".