Fine sutures combined with local flaps in the cosmetic repair of surgical defects of basal cell carcinoma of the head and face: a single-centre retrospective clinical study
Bibliographic record
Abstract
OBJECTIVE: To explore the effect of fine suturing combined with local flaps in the cosmetic repair of surgical defects associated with basal cell carcinoma (BCC) of the head and face. METHODS: A total of 46 patients with basal cell carcinoma of the head and face who were admitted to Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi) from January 2018 to June 2024 were retrospectively analysed. The patients were divided into a combined group and a control group, with 23 patients in each group. Each patient underwent extended tumour resection combined with intraoperative frozen section examination to ensure negative tumour boundaries. In the combined group, fine suturing and local flap transplantation were used to repair the defects; in the control group, traditional skin grafting was used to repair the defects. The perioperative indicators, postoperative scars, and patient satisfaction were compared between the two groups. RESULTS: The perioperative indicators of operation time and healing time were shorter than those of the control group (P < 0.05), and the incidence of adverse reactions was lower than that of the control group (P < 0.05). The Vancouver scar scale (VSS) score of the combined group was lower than that of the control group after follow-up for 6 months to 2 years, and patient satisfaction was higher (P < 0.05). CONCLUSION: Fine suturing combined with local flaps manifests a significant cosmetic effect in the repair of surgical defects of BCC of the head and face, which can reduce scar formation and improve patient satisfaction.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".