Towards Predicting Progression to Severe Dengue.


Journal

Trends in microbiology
ISSN: 1878-4380
Titre abrégé: Trends Microbiol
Pays: England
ID NLM: 9310916

Informations de publication

Date de publication:
06 2020
Historique:
received: 12 08 2019
revised: 04 11 2019
accepted: 09 12 2019
pubmed: 27 1 2020
medline: 26 5 2021
entrez: 27 1 2020
Statut: ppublish

Résumé

There is an urgent need for prognostic assays to predict progression to severe dengue infection, which is a major global threat. While the majority of symptomatic dengue patients experience an acute febrile illness, 5-20% progress to severe infection associated with significant morbidity and mortality. Early monitoring and administration of supportive care reduce mortality and clinically usable biomarkers to predict severe dengue are needed. Here, we review recent discoveries of gene sets, anti-dengue antibody properties, and inflammatory markers with potential utility as predictors of disease progression. Upon larger scale validation and development of affordable sample-to-answer technologies, some of these biomarkers may be utilized to develop the first prognostic assay for improving patient care and allocating healthcare resources more effectively in dengue endemic countries.

Identifiants

pubmed: 31982232
pii: S0966-842X(19)30318-X
doi: 10.1016/j.tim.2019.12.003
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

478-486

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

Auteurs

Makeda Robinson (M)

Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA.

Shirit Einav (S)

Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: seinav@stanford.edu.

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Classifications MeSH