Chilblain-Like Lesions (CLL) Associated With COVID-19 (“COVID Toes”): A Systematic Review
Bibliographic record
Abstract
Reports of chilblain-like lesions (CLL) coinciding with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been described in the literature, but this phenomenon has not been critically summarized. The aim of this paper is to summarize reports of CLL coinciding with SARS-CoV-2 infection to clarify the prevalence, clinical relevance, and prognostic value of these lesions. A literature search was conducted using the Embase, Pubmed, and Scopus databases from December 2019 to June 16, 2020 using the search terms ("COVID-19" OR "coronavirus" OR "2019-nCoV" OR "SARS-CoV-2") AND ("chilblain-like" OR "COVID toes" OR "acral"). Papers that described skin changes in patients with suspected or confirmed COVID-19 were included. A total of 31 papers were summarized, representing 813 cases of CLL. Available data suggests an equal gender distribution, mean age of 21 years, and median age of 14 years. Mild extracutaneous symptoms were reported in 53% of cases and 47% were asymptomatic. CLL occurred an average of 16 days after extracutaneous symptoms. Patients with CLL were positive for SARS-CoV-2 in 15% of cases. Lesions were mainly described as asymptomatic and/or pruritic erythematous to violaceous acral macules and plaques. Partial or complete resolution occurred in 85% of cases in a mean of 13 days. The most common histologic findings were perivascular and perieccrine superficial and deep lymphocytic infiltrates. Although a causal relationship between CLL and SARS-CoV-2 has not been confirmed, the temporal association and 15% positive SARS-CoV-2 rate in affected individuals should not be ignored.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".