Surgical Interventions in Advanced Hidradenitis Suppurativa: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Hidradenitis suppurativa (HS) is a chronic, immune-mediated skin disorder affecting intertriginous areas, frequently leading to painful nodules, abscesses, sinus tracts, and scarring. In patients with moderate-to-severe disease (Hurley Stages II and III), surgical intervention is frequently required to achieve durable disease control. OBJECTIVE: To compare and evaluate the surgical interventions employed in Hurley Stage II and III HS by evaluating recurrence rates, postoperative complications, and patient-centred outcomes across different operative modalities. METHODS: A comprehensive search of MEDLINE and EMBASE identified studies reporting surgical outcomes in Hurley Stage II and III HS. English-language studies describing postoperative recurrence, complications, and patient-centred outcomes stratified by surgical intervention were included. Of 647 studies screened, 136 studies were included. RESULTS: A total of 136 studies were included (5,646 procedures). Primary closure had the highest recurrence (38.0%) and complication rates (29.4%). Wide excision (n = 1923) showed moderate recurrence (17.2%) and the highest cosmetic dissatisfaction. Laser-assisted surgery had the lowest complication rate (2.2%) and recurrence rate (5.7%). Flaps and grafts showed higher complication rates but fewer recurrences than primary closure. CONCLUSION: Surgical outcomes in advanced HS vary by intervention. Primary closure is associated with the highest rates of recurrence and complications, while wide excision and laser-assisted surgery may offer improved disease control. These findings support individualized surgical planning in Stage II and III HS.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".