Vesiculobullous and Other Cutaneous Manifestations of COVID-19 Vaccines: a Scoping and Narrative Review
Bibliographic record
Abstract
As coronavirus disease (COVID-19) vaccines continue to be administered, dermatologists play a critical role in recognizing and treating the cutaneous manifestations (CM) associated with the vaccines. Adverse cutaneous reactions of COVID-19 vaccines reported in the literature range from common urticarial to rare vesiculobullous reactions. In this study, we performed a (1) scoping review to assess the occurrences of vesicular, papulovesicular, and bullous CMs of COVID-19 vaccines and their respective treatments, and (2) a narrative review discussing other common and uncommon CMs of COVID-19 vaccines. Thirty-six articles were included in the scoping review, and 66 articles in the narrative review. We found that vesicular, papulovesicular, and bullous lesions are infrequent, reported mostly after the first dose of Moderna or Pfizer vaccines. Eleven of the 36 studies reported vesicular reactions consistent with activation or reactivation of the herpes zoster virus. Most vesicular and bullous lesions were self-limited or treated with topical corticosteroids. Other CMs included injection-site, urticarial or morbilliform reactions, vasculitis, toxic epidermal necrolysis, and flaring of or new-onset skin diseases such as psoriasis. Treatments for CMs included topical or oral corticosteroids, antihistamines, or no treatment in self-limited cases. Although most CMs are benign and treatable, the data on the effect of systemic corticosteroids and immunosuppressive therapies on the immunogenicity of COVID-19 vaccines is limited. Some studies report reduced immunogenicity of the vaccines after high-dose corticosteroids use. Physicians may consult local guidelines where available when recommending COVID-19 vaccines to immunosuppressed patients, and when using corticosteroids to manage the CMs of COVID-19 vaccines.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".