Axillary Hyperhidrosis: A 5-Year Review of Treatment Efficacy and Recurrence Rates Using a New Arthroscopic Shaver Technique
Bibliographic record
Abstract
BACKGROUND: Axillary hyperhidrosis is a chronic condition characterized by excess axillary perspiration. This results in considerable patient morbidity, with no consistently efficacious medical or surgical treatment method described in the literature. METHODS: All cases of axillary hyperhidrosis over a 5-year period were reviewed retrospectively. Data were gathered by a chart review and telephone interview. Inclusion criteria included primary hyperhidrosis, failed conservative therapy, no prior surgical therapy, surgical management using a new arthroscopic shaver technique (R.L.B.-S.), and 6 months of postoperative follow-up. The technique used was consistent between surgeons. Sweating severity was assessed using a subjective numerical rating scale ranging from 1 to 10. Patient demographics, symptom history, results, and complications were analyzed. RESULTS: Average follow-up for 50 patients meeting the inclusion criteria was 28 months. The subjective severity scale demonstrated severity of 9.8 of 10 preoperatively and 2.3 of 10 postoperatively. Three patients (6 percent) reported mild recurrence of symptoms (4.6 of 10), which was not severe enough to seek further treatment. The average follow-up of those patients was 18.5 months. An overall subjective satisfaction of 96 percent was found, with a treatment success rate of 94 percent. Complications were minimal and self-limiting. The average time away from employment was 3.9 days and the average surgical operating room time was 46 minutes. CONCLUSIONS: The authors' new arthroscopic shaver technique is efficacious, with no significant morbidity, a 96 percent satisfaction rate, a subjectively measured 75 percent reduction of sweat, and a recurrence rate of only 6 percent. For cases of primary hyperhidrosis affecting the axilla not amenable to conservative treatment, the authors recommend an arthroscopic shaver technique as the first-line treatment of choice.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".