Management of Atopic Dermatitis during the COVID-19 Pandemic: Key Questions and Review of the Current Evidence
Bibliographic record
Abstract
Since the outbreak of COVID-19, management of atopic dermatitis (AD) has been widely discussed. Key issues include the risk of COVID-19 infection and related outcomes in AD patients, the efficacy and safety of COVID-19 vaccination in AD populations, and management of AD in the COVID-19 pandemic. Recent studies have shown that patients with AD have a slightly increased risk of COVID-19 infection but are not associated with a worse outcome than the non-AD population. COVID-19 vaccination is generally effective and safe in patients with AD. However, temporary discontinuation of certain systemic immunomodulatory agents after vaccination is suggested. During the pandemic, continuation of all immunomodulating agents is suggested, but these agents should be paused when patients with AD are infected with COVID-19 until recovery. Further studies are warranted to investigate the long-term interaction between AD and COVID-19 to aid clinical decisions during the pandemic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".