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Record W4361246749 · doi:10.1016/j.siny.2023.101431

Multisystem inflammatory disease in neonates (MIS-N) due to maternal COVID-19

2023· review· en· W4361246749 on OpenAlexaff
Viraraghavan Vadakkencherry Ramaswamy, Thangaraj Abiramalatha, Abdul K. Pullattayil, Daniele Trevisanuto

Bibliographic record

VenueSeminars in Fetal and Neonatal Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsQueen's University
FundersUniversità degli Studi di Padova
KeywordsMedicineIncidence (geometry)AsymptomaticDiseaseCohortPathophysiologyCoronavirus disease 2019 (COVID-19)PediatricsImmune systemSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CoronavirusAsymptomatic carrierImmunologyIntensive care medicineInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Multisystem inflammatory disease in neonates (MIS-N) is a disease of immune dysregulation presenting in the newborn period. Thouvgh its etiopathogenesis is proposed to be similar to multisystem inflammatory disease in Children (MIS-C), the exact pathophysiology is largely unknown as of present. The definition of MIS-N is contentious. The evidence for its incidence, the clinical features, profile of raised inflammatory markers, treatment strategies and outcomes stem from case reports, case series and cohort studies with small sample sizes. Though the incidence of MIS-N in severe acute respiratory syndrome caused by the coronavirus CoVID-2 (SARS-CoV-2) infected asymptomatic neonates is low, its incidence in symptomatic neonates is relatively higher. Further, amongst the neonates who are treated as MIS-N, the mortality rate is high. The review also evaluates the various other unresolved aspects of MIS-N from limited published literature and identifies knowledge gaps which could be areas of future research.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0020.001
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 head0.053
GPT teacher head0.381
Teacher spread0.328 · 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.

Study designOther design
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

Citations11
Published2023
Admission routes1
Has abstractyes

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