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Record W4416958197 · doi:10.1016/j.jdrv.2025.12.001

Topical steroid withdrawal and steroid phobia: Navigating this diagnostic dilemma

2025· article· en· W4416958197 on OpenAlexafffund
K. Blakely, Natalie Cunningham, R. Zeinab, Ashraf Abu-Fares

Bibliographic record

VenueJAAD reviews. · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsUniversity of OttawaBausch Health (Canada)Dalhousie UniversityFIRST Robotics Canada
FundersBausch Health
KeywordsAdverse effectAction (physics)DilemmaClinical trialTopical steroidSteroid useMedical literature

Abstract

fetched live from OpenAlex

Topical corticosteroids (TCSs) have been in use for decades as a first-line therapy for many chronic inflammatory skin conditions. While many of their potential adverse effects are well known, more recently a phenomenon known as topical steroid withdrawal (TSW) has been increasingly recognized. TSW appears to be a rare condition associated with long-term, inappropriate use of high-potency TCSs, mainly on the face, and is more commonly reported by women than men. The symptoms of TSW, including burning pain, skin redness and edema, overlap with many other skin conditions. This, along with the lack of high-quality evidence and agreed-upon diagnostic criteria, is hindering our understanding of the condition. Proposed mechanisms of action for TSW include "rebound" vasodilation, mediated by nitric oxide, and complex 1-mediated oxidation of NAD+, but evidence is limited. When used appropriately, TCSs can be a safe and effective treatment, but "steroid phobia" is a growing problem, fueled by a vast amount of low-quality, inaccurate information available online. Healthcare providers need to listen to their patients' concerns, and consider all possible diagnoses, encouraging their patients to consult professional, evidence-based advice. Large, prospective clinical trials are needed so consensus on definition and diagnostic criteria can be defined.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.354
Teacher spread0.332 · 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 teacher head, not a consensus.

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

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

Citations1
Published2025
Admission routes2
Has abstractyes

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