Global Patterns of Comorbidities Among Patients With Hidradenitis Suppurativa: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disorder increasingly recognized as a systemic disease with diverse comorbidities. While several comorbid conditions are well documented, regional differences in prevalence remain unclear. OBJECTIVE: The aim of this study was to evaluate regional variation in major comorbidities among HS patients, including diabetes, hypertension, depression, smoking, thyroid disorders, acne, obesity, psoriasis, and inflammatory bowel disease. METHODS: We performed a meta-analysis of proportions using a generalized linear mixed model with a binomial distribution and logit link to compare the prevalence of HS-associated comorbidities across North America, Europe, and the Middle East/Asia. Analyses were stratified by adult and pediatric populations, with regional N-values incorporated. RESULTS: Significant regional differences were observed in metabolic, endocrine, and psychiatric comorbidities. North American patients had higher odds of diabetes compared to Europe (odds ratio [OR] 1.92) and hypertension compared to the Middle East/Asia (OR 2.99). Depression and thyroid disorders were more common in North America (OR 3.46 and 2.32) and Europe (OR 3.19 and 4.01) compared to the Middle East/Asia. Smoking was more prevalent in Europe compared to North America (OR 0.28) and the Middle East/Asia (OR 2.26). Among pediatric patients, anxiety (OR 0.05) and depression (OR 0.16) were more common in North America, while smoking was more frequent outside North America (OR 12.67). CONCLUSIONS: Regional variation in comorbidity prevalence likely reflects differences in lifestyle, diet, sociocultural norms, healthcare literacy, and access to care. Recognizing these patterns may support earlier identification, guide preventive efforts, and inform individualized management strategies in HS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".