ArticleInternational journal of molecular sciences2019
Molecular Characterization of Influenza Strains in Patients Admitted to Intensive Care Units during the 2017-2018 Season.
Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Molecular epidemiological analysis of Influenza viruses in Influenza-like illness cases: a retrospective study in Chongqing Hi-Tech Zone, China (2021-2024).Virology journal · 2024Article
- Intra-species sialic acid polymorphism in humans: a common niche for influenza and coronavirus pandemics?Emerging microbes & infections · 2021Review
- [Health Technology Assessment (HTA) of the introduction of influenza vaccination for Italian children with Fluenz TetraJournal of preventive medicine and hygiene · 2021Article
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Authors and funding
13 authors at 4 institutions in 1 country.
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Abstract
This study aimed at assessing the frequency and the distribution of influenza virus types/subtypes in 172 laboratory-confirmed influenza-positive patients admitted to intensive care units (ICUs) during the 2017-2018 season in the Lombardy region (Northern Italy), and to investigate the presence of molecular pathogenicity markers. A total of 102/172 (59.3%) patients had influenza A infections (83 A/H1N1pdm09, 2 H3N2 and 17 were untyped), while the remaining 70/172 (40.7%) patients had influenza B infections. The 222G/N mutation in the hemagglutinin gene was identified in 33.3% (3/9) of A/H1N1pdm09 strains detected in the lower respiratory tract (LRT) samples and was also associated with more severe infections, whereas no peculiar mutations were observed for influenza B strains. A single-point evolution was observed in site 222 of A/H1N1pdm09 viruses, which might advantage viral evolution by favouring virus binding and replication in the lungs. Data from 17 paired upper respiratory tract (URT) and LRT samples showed that viral load in LRT samples was mostly higher than that detected in URT samples. Of note, influenza viruses were undetectable in 35% of paired URT samples. In conclusion, LRT samples appear to provide more accurate clinical information than URT samples, thus ensuring correct diagnosis and appropriate treatment of patients with severe respiratory infections requiring ICU admission.
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