Practical Guidelines for Managing Patients With Hidradenitis Suppurativa: An Update
Bibliographic record
Abstract
Hidradenitis suppurativa (HS) is a chronic, inflammatory skin disease that is characterized by the formation of comedones, papules, nodules, abscesses and sinus tracts in the axillary, inframammary, groin, and gluteal areas. Up to 3.8% of the Canadian population has HS, though due to a lack of awareness of HS, many patients are initially misdiagnosed and do not receive adequate treatment early on in the disease course. Once a diagnosis of HS is made, developing an effective management plan can be a dilemma for many providers. There is significant variability in response to any given therapy within the HS patient population and many HS patients have other medical comorbidities which must be taken into consideration. The aim of this review is to provide a practical approach for all healthcare providers to diagnose and manage HS and its associated comorbidities. A sample electronic medical record template for HS management was developed by the Canadian Hidradenitis Suppurativa Foundation Executive Board and is intended for use in clinical settings. This will help to increase collaboration between primary healthcare providers, dermatologists, and other medical specialists and ultimately improve the quality of care that HS patients receive.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".