<scp>COVID</scp>‐19 associated severe mucocutaneous blistering eruptions: A case series
Bibliographic record
Abstract
Mucocutaneous eruptions are associated with numerous infectious processes and can present as erythema multiforme (EM), reactive infectious mucocutaneous eruption (RIME), Stevens Johnson syndrome (SJS), or toxic epidermal necrolysis (TEN). Limited reports have detailed the association of these eruptions with SARS-CoV-2 infection. We present a series of eight cases of severe mucocutaneous blistering eruptions associated with SARS-CoV-2 infection. A retrospective case series was performed at six tertiary medical centers from March 1, 2020 to August 1, 2022. Inclusion criteria were met with a clinical diagnosis of EM, RIME, SJS, or TEN and a positive SARS-CoV-2 test (rapid antigen or polymerase chain reaction) less than 4 weeks prior to onset of dermatologic manifestation. Data was collected at time of each patient encounter. Eight patients met criteria with six pediatric patients (<18 years of age) having a median age of 15 years and two adult patients (>18 years of age) having a median age of 36 years. Patients were found to have a clinical diagnosis of RIME in 85.7% of cases. Oral mucosal involvement was the most common clinical finding (100%), followed by ocular (50.0%), urogenital (50.0%), and skin (37.5%) involvement. Evaluation did not reveal any additional infectious triggers in four patients. Evidence of possible concurrent or previous infectious triggers were identified in four patients. This case series highlights the development of severe mucocutaneous eruptions in association with COVID-19 infection, as well as the potential contributing role of concurrent or prior infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".