Literature DB >> 34103261

Clinical features and risk factors for severe influenza in children: A study from multiple hospitals in Shanghai.

Yu Shi1, Weiming Chen2, Mei Zeng3, Guomei Shen4, Chengjun Sun5, Gongbao Liu1, Hairong Gong2, Chuanqing Wang6, Mengmeng Ge7, Jin Xu8, Libo Wang9, Aizhen Lu10, Guoping Lu11, Xiaowen Zhai12.   

Abstract

BACKGROUND: The incidence and mortality of influenza in children had risen, but data are limited on children with severe influenza virus infection in China.
METHODS: We conducted a retrospective case-control study and collected the patients' clinical data. Clinical data including demography, clinical presentation, laboratory findings, radiologic findings, treatment and outcomes were collected. Children were clinically confirmed to have virus infection in Shanghai in three hospitals from June 2014 to June 2019.
RESULTS: During the study, 36,047 children were enrolled. Among them, 118 met the criteria for severe flu. Clinical symptoms such as fever, cough, gastrointestinal symptoms, coma and epilepsy were higher in the severe group. Complications such as pneumorrhagia, heart failure, septic shock, acute renal failure and influenza-associated encephalitis were higher in the severe influenza group than the death group. The laboratory findings including decreased hemoglobin, high alanine aminotransferase, high urea nitrogen and high lactate levels were risk factors for death in children with influenza.
CONCLUSION: Influenza-associated encephalopathy (IAE), acute respiratory distress syndrome (ARDS) were the common clinical manifestations and complications for the severe influenza, and delayed use of oseltamivir was found to be associated with fatality.
Copyright © 2021. Published by Elsevier B.V.

Entities:  

Keywords:  children; influenza; influenza-associated encephalitis; severe risks

Year:  2021        PMID: 34103261     DOI: 10.1016/j.pedneo.2021.05.002

Source DB:  PubMed          Journal:  Pediatr Neonatol        ISSN: 1875-9572            Impact factor:   2.083


  1 in total

1.  Using information technology to optimize the identification process for outpatients having blood drawn and improve patient satisfaction.

Authors:  Li-Feng Wu; Guo-Hua Zhuang; Qi-Lei Hu; Liang Zhang; Zhang-Mei Luo; Yin-Jiang Lv; Jian Tang
Journal:  BMC Med Inform Decis Mak       Date:  2022-03-10       Impact factor: 2.796

  1 in total

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