A Comparison of 3 Minimally Invasive Surgeries for Treating Axillary Osmidrosis
Bibliographic record
Abstract
BACKGROUND: Axillary osmidrosis is a common cause of physical and social discomfort. Although many treatments are available, there is still room for improvement. OBJECTIVE: For treatments of axillary osmidrosis 3 minimally invasive surgical methods of nasal endoscope-assisted suction cutting device, liposuction combined with subcutaneous curettage, and small incision trimming method are compared for the clinical efficacy, advantages and disadvantages. METHODS: Two hundred fifty-one axillary osmidrosis patients treated respectively with nasal endoscope-assisted suction cutting device, Liposuction with curettage, or small incision trimming method are investigated and the surgical outcomes and complications are analyzed. RESULTS: The effective rate is higher in the endoscopic group compared to the trimming and liposuction with curettage group ( P < 0.025). The postoperative Vancouver Scar Scale and total complication rate in the trimming group are significantly higher than those in the endoscopic and liposuction groups ( P < 0.025). The Hyperhidrosis Disease Severity Scale and overall satisfaction rate was superior in the endoscopic group compared to both liposuction with curettage and trimming groups. CONCLUSIONS: Liposuction with curettage has fewer complications and is safer, but with a lower cure rate. The small incision trimming method provides a more thorough treatment but with a higher complication rate. Relatively, nasal endoscope-assisted suction cutting device ensures thorough removal with fewer complications, making it a more recommended method.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".