Characteristics and treatment pathways in pediatric and adult hidradenitis suppurativa: An examination using real world data
Bibliographic record
Abstract
Background: Hidradenitis suppurativa (HS) is a chronic, debilitating, inflammatory disease. Contemporaneous real-world data can be used to elucidate the clinical treatment of pediatric patients and how treatment strategies compare with adult hidradenitis suppurativa patients. Objective: The objective of this study is to evaluate clinical and treatment characteristics of pediatric and adult HS patients. Methods: HS adult and pediatric patients were identified in 3 the United States administrative claims databases during the study period between 2016 to 2021. Patients were required to have 2 diagnostic codes for HS and have at least 365 days of prior observation time to the first HS diagnosis. Results: Pediatric and adult HS treatments were similar. The proportions of subjects treated with topical and oral antibiotic or oral antibiotic alone or topical medication alone or surgery alone covered 90% of the treated pediatric subjects and 91% of treated adult subjects. The remaining proportion of subjects received other treatment combinations. Limitations: The databases represent subjects with commercial or government insurance coverage and thus do not necessarily represent the broader US population. The databases do not capture information about medications obtained without insurance. Conclusions: Although subtle differences exist, this study confirms that topical and systemic therapeutic treatment of HS in adults and adolescents is very similar.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".