ArticleViruses2025
The Detection of COVID-19-Related Multivariate Biomarker Immune Response in Pediatric Patients: Statistical Aspects.
Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Association of IL-1β, IL-6, IL-8, IL-12, TNF-α, and IFN-α With Severe Pediatric COVID-19 and Multisystem Inflammatory Syndrome.Biomarker insights · 2026Article
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Authors and funding
9 authors.
Funding
Abstract
The development of new point-of-care diagnostic testing tools for the detection of infectious diseases such as COVID-19 are a key aspect of clinical care and research. Accurate predictive classification methods are required to correctly identify and treat patients. Here, the onset of multisystem inflammatory syndrome in children (MIS-C), a more serious form of COVID-19, was predicted in a pediatric population using a set of multivariate immunological biomarker expression values. A first-stage bivariate detection of statistically significant biomarkers was obtained from a chosen set of standard cytokines and chemokine biomarkers considered relevant to COVID-19-related infection and disease. To incorporate the observed correlation structure among the resulting set of significant biomarkers, dimension reduction was then applied in the form of principal components. A second-stage logistic regression model using a small number of the principal component variables provided a highly predictive classification model for MIS-C. The resulting model was shown to compare favorably with an artificial neural network-based predictive model.
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Registered trials
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