Lessons From the First Wave of the Pandemic: Skin Features of COVID-19 Can Be Divided Into Inflammatory and Vascular Patterns
Bibliographic record
Abstract
This review examines the clinical, morphological, and systemic factors related to coronavirus disease 2019 (COVID-19) cutaneous manifestations. The EMBASE, Medline, and Pubmed Central databases were searched from February 1, 2020 until April 25, 2020, using the search words "(COVID-19 OR SARS-CoV-2 OR coronavirus-19) AND (skin OR cutaneous OR dermatologic)". Cutaneous manifestations of COVID-19 were included. The cutaneous manifestations can be classified into 2 types. Patients with inflammatory reactions consisted of morbilliform, varicella-like, urticarial eruptions, and vesiculobullous manifestations. These manifestations were mainly found on the trunk, limbs, and faces of patients and had mainly positive COVID-19 polymerase chain reaction findings (97.7%). Furthermore, there were 516 patients with acral vascular lesions: chilblains, livedo lesions, cutaneous small-vessel vasculitis, and other noninflammatory purpura. These were often nonpruritic (88%) and not seen in severe disease (88.7%). The cutaneous lesions have potential for early diagnosis of COVID-19 and prevention of disease transmission. The implications of COVID-19 in the field of dermatology continue to evolve as more clinical data becomes available.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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 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".