Pfizer/BioNTech‐associated perniosis in two young adults with re‐challenge evidence
Bibliographic record
Abstract
The employment of novel mRNA delivery with Pfizer/BioNTech (BNT162b2) and Moderna (mRNA-1273) SARS-CoV-2 vaccines has cultivated close scrutiny for adverse events. The novel immunogenic nature of the SARS-CoV-2 virus and its peculiar cutaneous clinical sequelae has further compounded this behaviour. Authors of the American Academy of Dermatology (AAD) and the International League of Dermatological Societies (ILDS) recently published a registry demonstrating a breadth of cutaneous reactions related to the mRNA vaccines.1 Unsurprisingly, the most frequent is local injection site reactions, seen also in Bogdanov et al.,2 but the degree of atypical adverse events, such as erythromelalgia in 6%,1 is striking. Chilblains, or perniosis, are an infrequent reaction in this registry of 414 patients; it was seen eight times as frequently in Pfizer/BioNTech vaccination (8.8%) than amongst patients who received Moderna (1.1%). In contrast, in the setting of natural infection from a registry of 716 patients from 31 countries, up to 18% and 33% of patients with either a confirmed or suspected natural infection, respectively, developed a pernio-like reaction; in the setting of natural infection in this registry, and it was the second most common COVID-19-associated dermatologic manifestation.3 We report two cases of Pfizer/BioNTech vaccine-associated chilblains in previously healthy patients, both with re-challenge evidence and negative viral nasopharyngeal detection. The 31- and 33-year-old men developed lower extremity dorsal acral and periungual pruritus as well as slight tenderness with erythema and oedema at days 5 and 7 following their first vaccine dose. In both cases, the erythema, pruritus and slight tenderness subsided almost entirely by the second dose (28 days later). However, 24-h following their second dose, both had a recurrence of symptoms; in one case, this proceeded to the point of ulceration (Fig. 1). Natural resolution was achieved within 6 weeks in both patients with no residual skin or neurovascular changes. The Naranjo Algorithm was used to score the probability of an adverse drug reaction, which yielded a score of 6 (probable) in both cases.4 The morphological findings in vaccine-induced chilblains appear indistinguishable from idiopathic perniosis and that associated with autoimmune connective tissue disease (AiCTD) with accompanying histologic lymphocytic vasculitis.5 Both the Pfizer/BioNTech and Moderna (mRNA-1273) vaccines encode spike protein antigens with a very high degree of similarity between the generated antibody responses targeted at epitopes from the receptor-binding domain.6 While both cases reported here were secondary to the Pfizer/BioNTech vaccine, as well as those reported by McMahon et al.1 (n = 2) and Lesort et al.7 (n = 1), we suspect that this cutaneous adverse event is not limited to Pfizer/BionTech, but instead represents a phenomenon of immunogenic response; further work is needed to better understand the pathogenesis and relevance to systemic immunity. In conclusion, we report two cases of SARS-CoV-2 perniosis associated with mRNA Pfizer/BioNTech vaccine, which recurred with re-challenge and were self-limited. Vaccine-related perniosis appears to be an indolent cutaneous reaction, which abates in short term, but further documentation and awareness are needed to understand the natural history in larger case numbers. The patients in this manuscript have given written informed consent to the publication of their case details. None. None. Not applicable, and no new data were generated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".