Prevalence, Age of Onset, Age at Diagnosis, and Family History of Hidradenitis Suppurativa in Pediatric Populations: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
INTRODUCTION: Hidradenitis suppurativa (HS) is a chronic inflammatory skin condition characterized by recurrent nodules and abscesses in intertriginous areas, ultimately resulting in scarring and formation of sinus tracts. HS significantly impacts quality of life and can also affect pediatric populations. We aimed to determine the prevalence, family history, age of onset, and age at diagnosis of HS in pediatric populations. METHODS: A random-effects meta-analysis of observational studies was conducted following MOOSE guidelines. Five databases were searched through May 2024. RESULTS: Thirty seven observational studies were included, representing 6941 patients from 13 countries. The weighted mean age was 14.7 years (range: 4-18). Ethnoracial distribution included White (36.5%), Black (38.3%), Hispanic (13.9%), Asian (0.8%), Indigenous (0.2%), Middle Eastern (0.7%), multiracial (1.2%), and unspecified populations (8.4%). Among studies reporting severity, 42.5% had Hurley Stage I, 46.3% Stage II, and 11.2% Stage III. The prevalence of HS in pediatric populations was 0.03% (95% CI [0.0001, 0.0005]), with 38% of patients having a family history of HS (95% CI [0.30, 0.45]). Pediatric-onset HS predominantly affects females (78%, 95% CI [0.76, 0.80]). The average age of onset of HS in pediatric populations was 11.3 years (95% CI [10.15, 12.39]), but diagnosis typically occurred at 14.0 years (95% CI [12.65, 15.28]), indicating a delay in diagnosis. Female predominance of HS was associated with earlier age of onset and age at diagnosis, while no significant correlations between family history, age of onset, or age at diagnosis were identified. CONCLUSION: This study highlights the characteristics of pediatric-onset HS and emphasizes the need for earlier detection to expedite diagnosis and initiation of treatment.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.028 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".