Cessation of Long-term Topical Steroids in Adult Atopic Dermatitis: A Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Although there is much interest in social media about topical steroid withdrawal, little is known about what happens to people who cease long-term topical steroid use. OBJECTIVE: The aim of this study was to examine outcomes in adults with a history of atopic dermatitis who were concerned about topical steroid withdrawal and decided to stop using topical steroids. METHODS: Twenty-four participants were recruited from an Australian online support group, and they were emailed a series of questionnaires over 2 years. RESULTS: Stopping topical steroid use had a large impact on the participants' quality of life for many months. Overall, participants' incidence and severity of symptoms decreased over the study period, and their Dermatology Quality of Life index scores improved. The majority reported their skin symptoms either had resolved or had only a small effect on their lives 2 years later. However, individuals' quality of life scores fluctuated, and in every questionnaire, large ranges in scores were seen, demonstrating that the experiences of participants differed considerably. CONCLUSIONS: Counseling patients who are considering discontinuing long-term use of topical steroids regarding their prognosis is difficult as outcomes vary. However, many will improve significantly over the first 2 years.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".