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Record W4321498656 · doi:10.1177/12034754231158074

Chilblain-Like Lesions (CLL) Coinciding With the SARS-CoV-2 Pandemic in Children: A Systematic Review

2023· review· en· W4321498656 on OpenAlexaff
Samantha Y. Starkey, Nadia Kashetsky, Joseph M. Lam, Jan Dutz, Ilya Mukovozov

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2023
Typereview
Languageen
FieldMedicine
TopicDermatological and COVID-19 studies
Canadian institutionsBC Children's HospitalMemorial University of NewfoundlandUniversity of British Columbia
Fundersnot available
KeywordsMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicCoronavirus disease 2019 (COVID-19)SerologyDermatologyCoronavirus2019-20 coronavirus outbreakPediatricsPathologyImmunologyDiseaseAntibody

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.231
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.120
GPT teacher head0.367
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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