Predictors of Severity of Influenza-Related Hospitalizations: Results From the Global Influenza Hospital Surveillance Network (GIHSN)
Abstract
Background. The Global Influenza Hospital Surveillance Network (GIHSN) has since 2012 provided patient-level data on severe influenza-like-illnesses from >100 participating clinical sites worldwide based on a core protocol and consistent case definitions.
Methods. We used multivariable logistic regression to assess the risk of intensive care unit admission, mechanical ventilation, and in-hospital death among hospitalized patients with influenza and explored the role of patient-level covariates and country income level.
Results. The data set included 73 121 patients hospitalized with respiratory illness in 22 countries, including 15 660 with laboratory-confirmed influenza.
After adjusting for patient-level covariates we found a 7-fold increase in the risk of influenzarelated intensive care unit admission in lower middle-income countries (LMICs), compared with high-income countries (P =.01). The risk of mechanical ventilation and in-hospital death also increased by 4-fold in LMICs, though these differences were not statistically significant.
We also find that influenza mortality increased significantly with older age and number of comorbid conditions. Across all severity outcomes studied and after controlling for patient characteristics, infection with influenza A/H1N1pdm09 was more severe than with A/H3N2.
Conclusions. Our study provides new information on influenza severity in underresourced populations, particularly those in LMICs.