Systemic immunosuppressive therapy for inflammatory skin diseases in children: Expert consensus‐based guidance for clinical decision‐making during the COVID‐19 pandemic
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: The COVID-19 pandemic has raised questions about the approach to management of systemic immunosuppressive therapies for dermatologic indications in children. Change to: Given the absence of data to address concerns related to SARS-CoV-2 infection and systemic immunosuppressive therapies in an evidence-based manner, a Pediatric Dermatology COVID-19 Response Task Force (PDCRTF) was assembled to offer time-sensitive guidance for clinicians. METHODS: A survey was distributed to an expert panel of 37 pediatric dermatologists on the PDCRTF to assess expert opinion and current practice related to three primary domains of systemic therapy: initiation, continuation, and laboratory monitoring. RESULTS: Nearly all respondents (97%) reported that the COVID-19 pandemic had impacted their decision to initiate immunosuppressive medications. The majority of pediatric dermatologists (87%) reported that they were pausing or reducing the frequency of laboratory monitoring for certain immunosuppressive medications. In asymptomatic patients, continuing therapy was the most popular choice across all medications queried. The majority agreed that patients on immunosuppressive medications who have a household exposure to COVID-19 or test positive for new infection should temporarily discontinue systemic and biologic medications, with the exception of systemic steroids, which may require tapering. CONCLUSIONS: The ultimate decision regarding initiation, continuation, and laboratory monitoring of immunosuppressive therapy during the pandemic requires careful deliberation, consideration of the little evidence available, and discussion with families. Consideration of an individual's adherence to COVID-19 preventive measures, risk of exposure, and the potential severity if infected must be weighed against the dermatological disease, medication, and risks to the patient of tapering or discontinuing therapies.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".