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Record W4409319496 · doi:10.1093/ofid/ofaf224

Severe Parvovirus B19–Associated Myocarditis in Children in the Post–COVID-19 Era: A Multicenter Observational Cohort Study

2025· article· en· W4409319496 on OpenAlexaff
Neal Russell, James Hatcher, Tim Best, Judith Breuer, James Charlesworth, Peter Muir, Barry Vipond, Stéphane Paulus, Rohit Saxena, Jacob Simmonds, Stefania Vergnano, Peter G. Davis, Seilesh Kadambari

Bibliographic record

VenueOpen Forum Infectious Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicParvovirus B19 Infection Studies
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineObservational studyMyocarditisParvovirusCoronavirus disease 2019 (COVID-19)Cohort studyCohortPediatricsInternal medicineVirologyVirusDisease

Abstract

fetched live from OpenAlex

This study describes a cluster of severe parvovirus B19-associated myocarditis cases in children across England in the context of an increase in circulating virus. Cases were identified across 3 large children's centers. Eight cases presented from 1 January 2019 to 31 December 2023 as compared with 19 from 1 January 2024 to 31 August 2024. Almost all (n = 25, 93%) required intensive care, and 24 (88%) received inotropes and 4 (15%) extracorporeal membrane oxygenation. Myocarditis appears to be temporally associated and a late sequela of parvovirus B19, resulting in high rates of intensive care unit admission. Testing with serology and blood polymerase chain reaction should be part of a syndromic screen for all children with severe myocarditis.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.341
Teacher spread0.317 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations4
Published2025
Admission routes1
Has abstractyes

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