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Record W4405738575 · doi:10.1016/j.jaad.2024.11.071

North American clinical practice guidelines for the medical management of hidradenitis suppurativa in special patient populations

2024· article· en· W4405738575 on OpenAlexaff
Raed Alhusayen, Serena Dienes, Megan Lam, Afsáneh Alavi, Ali Alikhan, Maria Aleshin, Emad Bahashwan, Steve Daveluy, Noah Goldfarb, Amit Garg, Wayne Gulliver, Tarannum Jaleel, Alexa B. Kimball, Mark G. Kirchhof, Joslyn S. Kirby, Joi Lenczowski, Hadar Lev‐Tov, Michelle A. Lowes, Irene Lara‐Corrales, Robert G. Micheletti, Martin M. Okun, Lauren A.V. Orenstein, Susan Poelman, Vincent Piguet, Martina L. Porter, Barry I. Resnik, Cathryn Sibbald, Vivian Y. Shi, Christopher J. Sayed, Se Mang Wong, Andrea L. Zaenglein, Hélène Veillette, Jennifer L. Hsiao, Haley B. Naik

Bibliographic record

VenueJournal of the American Academy of Dermatology · 2024
Typearticle
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsUniversité LavalWomen's College HospitalUniversity of CalgaryCentre hospitalier de l'Université LavalUniversity of British ColumbiaHospital for Sick ChildrenOttawa HospitalUniversity of OttawaMemorial University of NewfoundlandUniversity of TorontoSunnybrook HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsHidradenitis suppurativaMedicineDermatologyClinical PracticeMEDLINEFamily medicineInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Hidradenitis suppurativa (HS) affects different patient populations that require unique considerations in their management. However, no HS guidelines for these populations exist. OBJECTIVE: To provide evidence-based consensus recommendations for patients with HS in 7 special patient populations: (i) pregnancy, (ii) breastfeeding, (iii) pediatrics, (iv) malignancy, (v) tuberculosis infection, (vi) hepatitis B or C infection, and (vii) HIV disease. METHODS: Recommendations were developed using the Grading of Recommendations Assessment, Development, and Evaluation system to ascertain level of evidence and selected through a modified Delphi consensus process. RESULTS: One hundred eighteen expert consensus statements are provided for the management of patients with HS across these 7 special patient populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0110.004

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.

Opus teacher head0.099
GPT teacher head0.474
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations10
Published2024
Admission routes1
Has abstractno

Explore more

Same venueJournal of the American Academy of DermatologySame topicHidradenitis Suppurativa and TreatmentsFrench-language works237,207