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Record W3043952641 · doi:10.1002/art.41454

American College of Rheumatology Clinical Guidance for Multisystem Inflammatory Syndrome in Children Associated With SARS–CoV‐2 and Hyperinflammation in Pediatric COVID‐19: Version 1

2020· article· en· W3043952641 on OpenAlexaff
Lauren A. Henderson, Scott Canna, Kevin G. Friedman, Mark Gorelik, Sivia Lapidus, Hamid Bassiri, Edward M. Behrens, Anne Ferris, Kate F. Kernan, Grant S. Schulert, Philip Seo, Mary Beth F. Son, Adriana H. Tremoulet, Rae S. M. Yeung, Amy S. Mudano, Amy S. Turner, David R. Karp, Jay Mehta

Bibliographic record

VenueArthritis & Rheumatology · 2020
Typearticle
Languageen
FieldMedicine
TopicKawasaki Disease and Coronary Complications
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentChildhood Arthritis and Rheumatology Research AllianceCSL BehringSwedish Orphan BiovitrumEli Lilly and Company
KeywordsMedicineRheumatologyCoronavirus disease 2019 (COVID-19)Intensive care medicineInternal medicineTask forceInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

OBJECTIVE: To provide guidance on the management of multisystem inflammatory syndrome in children (MIS-C), a condition characterized by fever, inflammation, and multiorgan dysfunction that manifests late in the course of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and to provide recommendations for children with hyperinflammation during coronavirus disease 2019 (COVID-19), the acute, infectious phase of SARS-CoV-2 infection. METHODS: A multidisciplinary task force was convened by the American College of Rheumatology (ACR) to provide guidance on the management of MIS-C associated with SARS-CoV-2 and hyperinflammation in COVID-19. The task force was composed of 9 pediatric rheumatologists, 2 adult rheumatologists, 2 pediatric cardiologists, 2 pediatric infectious disease specialists, and 1 pediatric critical care physician. Preliminary statements addressing clinical questions related to MIS-C and hyperinflammation in COVID-19 were developed based on evidence reports. Consensus was built through a modified Delphi process that involved 2 rounds of anonymous voting and 2 webinars. A 9-point scale was used to determine the appropriateness of each statement (median scores of 1-3 for inappropriate, 4-6 for uncertain, and 7-9 for appropriate), and consensus was rated as low, moderate, or high based on dispersion of the votes along the numeric scale. Approved guidance statements were those that were classified as appropriate with moderate or high levels of consensus, as prespecified prior to voting. RESULTS: The ACR task force approved a total of 128 guidance statements addressing the management of MIS-C and hyperinflammation in pediatric COVID-19. These statements were refined into 40 final clinical guidance statements, accompanied by a flow diagram depicting the diagnostic pathway for MIS-C. CONCLUSION: Our understanding of SARS-CoV-2-related syndromes in the pediatric population continues to evolve. The guidance provided in this "living document" reflects currently available evidence, coupled with expert opinion, and will be revised as further evidence 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0210.015

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 head0.018
GPT teacher head0.284
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations536
Published2020
Admission routes1
Has abstractyes

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