Chilblain-Like Lesions (CLL) Coinciding With the SARS-CoV-2 Pandemic in Children: A Systematic Review
Bibliographic record
Abstract
Chilblain-like lesions (CLL) coinciding with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection have been described in the literature. Available reviews of the literature suggest that CLL are associated with younger age, an equal sex ratio, negative testing for SARS-CoV-2, and mild to no extracutaneous manifestations (ECM) associated with COVID-19 infection. This systematic review aims to provide a summary of reports of CLL associated with the early SARS-CoV-2 pandemic in children to clarify the prevalence, clinical characteristics, and resolution outcomes of these skin findings. Sixty-nine studies, published between May 2020 and January 2022, met inclusion criteria and were summarized in this review, representing 1,119 cases of CLL. Available data showed a slight male predominance (591/1002, 59%). Mean age was 13 years, ranging from 0 to 18 years. Most cases had no ECM (682/978, 70%). Overall, 70/507 (14%) of patients tested positive for COVID-19 using PCR and/or serology. In the majority the clinical course was benign with 355/415 (86%) of cases resolving, and 97/269 (36%) resolving without any treatment. This comprehensive summary of pediatric CLL suggests these lesions are rarely associated with COVID-19 symptoms or test positivity.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".