Molecular Epidemiology and Clinical Features Analysis of Respiratory Adenovirus Infections Reveals Correlations between Genotype, Inflammatory Biomarkers, and Disease Severity.


Journal

BioMed research international
ISSN: 2314-6141
Titre abrégé: Biomed Res Int
Pays: United States
ID NLM: 101600173

Informations de publication

Date de publication:
2020
Historique:
received: 19 06 2020
revised: 24 09 2020
accepted: 10 10 2020
entrez: 4 11 2020
pubmed: 5 11 2020
medline: 11 5 2021
Statut: epublish

Résumé

Human adenoviruses (HAdVs) are commonly causing respiratory disease. We molecularly genotyped HAdV circulating in Chinese hospitalized children with respiratory infections and summarized the clinical profiles and common inflammatory biomarkers, so as to better determine their associations with disease severity. Children with respiratory single HAdV infection cases that occurred from December 2017 to March 2019 were enrolled for a cross-sectional study. Clinical/laboratory features based on the genotypes of respiratory HAdV infection were reviewed for comparative analysis. A total of 84 patients were enrolled, and HAdV types were identified from 82 patients. Species B (HAdV-7, 44%; HAdV-3, 43%, and HAdV-14, 5%) was the most common, followed by C (HAdV-2, 4% and HAdV-1, 1%) and E (HAdV-4, 1%). Severe HAdV infection and HAdV-7 infection groups were associated with significantly longer duration of fever and hospitalized days, higher morbidity of tachypnea/dyspnea, more pleural effusion, more respiratory rales, more frequently required mechanical ventilation, and significantly higher fatality rate. The elevated procalcitonin (PCT) and C-reactive protein (CRP) levels were significantly associated with severe HAdV infection. HAdV-7 and HAdV-3 were the most common types among children with respiratory adenovirus infection; vaccines against these two genotypes are in urgent need. PCT and CRP are significantly associated with the severity of HAdV infection.

Sections du résumé

BACKGROUND BACKGROUND
Human adenoviruses (HAdVs) are commonly causing respiratory disease. We molecularly genotyped HAdV circulating in Chinese hospitalized children with respiratory infections and summarized the clinical profiles and common inflammatory biomarkers, so as to better determine their associations with disease severity.
METHOD METHODS
Children with respiratory single HAdV infection cases that occurred from December 2017 to March 2019 were enrolled for a cross-sectional study. Clinical/laboratory features based on the genotypes of respiratory HAdV infection were reviewed for comparative analysis.
RESULTS RESULTS
A total of 84 patients were enrolled, and HAdV types were identified from 82 patients. Species B (HAdV-7, 44%; HAdV-3, 43%, and HAdV-14, 5%) was the most common, followed by C (HAdV-2, 4% and HAdV-1, 1%) and E (HAdV-4, 1%). Severe HAdV infection and HAdV-7 infection groups were associated with significantly longer duration of fever and hospitalized days, higher morbidity of tachypnea/dyspnea, more pleural effusion, more respiratory rales, more frequently required mechanical ventilation, and significantly higher fatality rate. The elevated procalcitonin (PCT) and C-reactive protein (CRP) levels were significantly associated with severe HAdV infection.
CONCLUSIONS CONCLUSIONS
HAdV-7 and HAdV-3 were the most common types among children with respiratory adenovirus infection; vaccines against these two genotypes are in urgent need. PCT and CRP are significantly associated with the severity of HAdV infection.

Identifiants

pubmed: 33145348
doi: 10.1155/2020/4357910
pmc: PMC7596535
doi:

Substances chimiques

Biomarkers 0
Procalcitonin 0
C-Reactive Protein 9007-41-4

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4357910

Informations de copyright

Copyright © 2020 Hui Dai et al.

Déclaration de conflit d'intérêts

All the authors have reviewed this manuscript and declared no conflict of interest.

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Auteurs

Hui Dai (H)

Department of Laboratory Medicine, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, China.
Department of Laboratory Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180 Guangdong, China.

Hongli Xi (H)

Division of Laboratory Science and Laboratory of Tumor and Virology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, Guangdong 510095, China.

Li Huang (L)

Division of Laboratory Science and Laboratory of Tumor and Virology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, Guangdong 510095, China.

Zhaohu Yuan (Z)

Department of Blood Transfusion, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180 Guangdong, China.

Yike Liao (Y)

Health Science Center, Peking University, Peking 100191, China.

Yongcai Tang (Y)

Department of Laboratory Medicine, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, China.
Department of Laboratory Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180 Guangdong, China.

Jun Liao (J)

Department of Laboratory Medicine, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, China.
Department of Laboratory Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180 Guangdong, China.

Ling Min (L)

Division of Laboratory Science and Laboratory of Tumor and Virology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, Guangdong 510095, China.

Zhiwu Yu (Z)

Division of Laboratory Science and Laboratory of Tumor and Virology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, Guangdong 510095, China.
Department of Laboratory Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180 Guangdong, China.

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Classifications MeSH