Viral co-infections are associated with increased rates of hospitalization in those with influenza
Abstract
BACKGROUND: Influenza causes significant morbidity and mortality in the United States. Among patients infected with influenza, the presence of bacterial co-infection is associated with worse clinical outcomes; less is known regarding the clinical importance of viral co-infections. The objective of this study was to determine rates of viral co-infections in emergency department (ED) patients with confirmed influenza and association of co-infection with disease severity.
METHODS: Secondary analysis of a biorepository and clinical database from a parent study where rapid influenza testing was implemented in four U.S. academic EDs, during the 2014-2015 influenza season. Patients were systematically tested for influenza virus using a validated clinical decision guideline. Demographic and clinical data were extracted from medical records; nasopharyngeal specimens from influenza-positive patients were tested for viral co-infections (ePlex, Genmark Diagnostics). Patterns of viral co-infections were evaluated using chi-square analysis. The association of viral co-infection with hospital admission was assessed using univariate and multivariate regression.
RESULTS: The overall influenza A/B positivity rate was 18.1% (1071/5919). Of the 999 samples with ePlex results, the prevalence of viral co-infections was 7.9% (79/999). The most common viral co-infection was rhinovirus/enterovirus (RhV/EV), at 3.9% (39/999). The odds of hospital admission (OR 2.33, 95% CI: 1.01-5.34) increased…
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.