A New Perspective on Isotretinoin Treatment of Hidradenitis Suppurativa: A Retrospective Chart Review of Patient Outcomes
Bibliographic record
Abstract
BACKGROUND: Hidradenitis suppurativa (HS) is a disease characterized by the development of painful, deep-seeded nodules and abscesses. Treatment guidelines include a combination of lifestyle, surgical, and medical interventions. Isotretinoin has not been included in the treatment guidelines due to the limited number of studies and conflicting reports of efficacy. OBJECTIVES: The purpose of this study is to evaluate the clinical response to isotretinoin in HS patients and to determine whether there is a particular patient population that may benefit more from this treatment. METHODS: A retrospective chart review was conducted on all HS patients treated with isotretinoin within the years of 2014-2016. Sex, age, weight, history of acne, Hurley stage, and treatment dose and duration were extracted from patient charts. RESULTS: Of the 25 patients included in the study, 32% (8/25) had no response, 32% (8/26) showed partial response, and 36% (9/25) demonstrated complete response to isotretinoin treatment. Complete response was seen only in Hurley stage I and II patients. Hurley III patients made up 50% of the non-responders. Those with any sort of treatment response were more likely to be female, younger, weigh less, and have a higher prevalence of acne compared to non-responders. LIMITATIONS: This is a retrospective chart review with a small sample size of 25 patients. CONCLUSIONS: Physicians should consider isotretinoin as a potential treatment for HS, as it may be beneficial in patients with mild and moderate disease and patients who are female, younger, weigh less, and have a personal history of acne.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".