Severe Acute Respiratory Syndrome Coronavirus 2 and the Use of Biologics in Patients With Psoriasis
Bibliographic record
Abstract
Coronavirus disease (COVID-19), a respiratory disease caused by a novel coronavirus designated severe acute respiratory syndrome coronavirus 2, has rapidly spread worldwide and has been recognized as a pandemic by the World Health Organization. Patients with altered immunologic function are at higher risk of acquiring COVID-19. In patients with psoriasis, inhibition of select pro-inflammatory cytokines through the use of biologic agents has been shown to be an effective treatment option. Pro-inflammatory cytokines have key immunomodulatory effects and are known to be involved in the hosts' immune response to a variety of viral infections. Though little is currently known about the role of inflammatory cytokines in COVID-19, early reports have shown patients with severe disease to have elevated serum levels of select inflammatory cytokines such as tumor necrosis factor alpha. This review will summarize key information that is currently known about COVID-19, the role of select cytokines in viral defense, and important considerations for patients with psoriasis using biologic agents during this pandemic. Currently, there is insufficient evidence to discontinue biologic therapy in patients with psoriasis who have not tested positive for COVID-19. The decision to pause biologic therapy should be considered on a case-by-case basis in patients in higher risk populations, and should take into account individual risk and benefit. Until more is known about the impact of biologic therapy on COVID-19 outcomes, we recommend patients with psoriasis who test positive for COVID-19 be instructed to discontinue or postpone biologic treatment until they have recovered from infection.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".