Blunt Dissection of the Axillary Flap through Double Mini-Incisions on Both Sides of the Axilla to Prevent Postoperative Hematoma
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to investigate the clinical effect of treating axillary osmidrosis by trimming the apocrine glands under direct vision after blunt dissection of the axillary flap through double mini-incisions on both sides of the axilla to prevent postoperative hematoma. METHODS: The clinical data of 108 patients with axillary osmidrosis were retrospectively analyzed. Treatment involved blunt dissection of the axillary flap through double mini-incisions and trimming of the apocrine glands under direct vision. The surgical duration, hematoma incidence, flap necrosis rate, incision healing rate, incision Vancouver Scar Scale score, comfort level, axillary odor cure rate, and satisfaction rating were all analyzed statistically. RESULTS: The average surgical duration was 72.45 ± 5.71 minutes. The cure rate of axillary osmidrosis was 100%. Postoperative complications, including delayed incision healing 12 days after surgery (1 patient), a small hematoma (2 patients), and local flap necrosis (1 patient), were minor. No infection, malodor, or recurrence was observed. The visual analog scale scores were 8.53 ± 0.89 for patient comfort, 8.87 ± 0.98 for patient satisfaction, and 0.84 ± 0.99 for the incision. CONCLUSIONS: This retrospective study demonstrated that trimming of apocrine glands after blunt dissection of the axillary flap through double mini-incisions on both sides of the axilla effectively controlled bleeding. This approach significantly reduces the complication rate of axillary osmidrosis surgery and ensures the complete trimming of apocrine glands, eradicating axillary odor and maintaining a good appearance.
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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) | 0.002 | 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".