Erythema Multiforme and Epidermal Necrolysis following COVID-19 Vaccines: A Systematic Review
Bibliographic record
Abstract
The outbreak of COVID-19 pandemic has raised urgent vaccine development to prevent viral transmission. Cutaneous adverse events such as erythema multiforme (EM), Stevens-Johnson syndrome (SJS), and toxic epidermal necrolysis (TEN) have been observed following COVID-19 vaccination. In this systematic review, we aimed to investigate the clinical features and outcomes of EM/SJS/TEN following COVID-19 vaccination. A comprehensive literature search was conducted in PubMed, Embase, Web of Science, and Cochrane databases up to July 3, 2022. We included studies reporting patients who developed EM, SJS, or TEN following COVID-19 vaccination. A total of 47 studies involving 90 patients with EM and 16 patients with SJS/TEN were reviewed and outlined. EM predominantly occurred after the messenger ribonucleic acid vaccines (70.4%), mostly after the first (47.5%) and second doses (42.4%), with delayed onsets ranging from 1 day to 30 days. SJS/TEN were observed following either the first (55.6%)- or second-dose (33.3%) vaccination, with onset times ranging from 6 hours to 14 weeks. Three EM cases and 1 SJS case showed recurrence upon reexposure to the same vaccines. No mortality was reported. Most patients exhibited improvement or resolution after treatment, with resolution times ranging from 6 days to 8 weeks. In conclusion, EM and epidermal necrolysis, including SJS and TEN, have emerged as potential cutaneous adverse events following COVID-19 vaccine administration. Further research is warranted to elucidate the pathogenesis and casual relationship between COVID-19 vaccines and EM/SJS/TEN.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".