Influenza A infections: predictors of disease severity

Braz J Microbiol. 2024 Mar;55(1):75-86. doi: 10.1007/s42770-023-01186-w. Epub 2023 Dec 5.

Abstract

Influenza affects approximately 10% of the world's population annually. It is associated with high morbidity and mortality rates due to its propensity to progress to severe acute respiratory infection, leading to 10-40% of hospitalized patients needing intensive care. Characterizing the multifactorial predictors of poor prognosis is essential for developing strategies against this disease. This study aimed to identify predictors of disease severity in influenza A-infected (IFA-infected) patients and to propose a prognostic score. A retrospective cross-sectional study was conducted with 142 IFA-infected out- and inpatients treated at a tertiary hospital between 2010 and 2018. The viral subtypes, hemagglutinin mutations, viral load, IL-28B SNPs, and clinical risk factors were evaluated according to the patient's ICU admission. Multivariate analysis identified the following risk factors for disease severity: neuromuscular diseases (OR = 7.02; 95% CI = 1.18-41.75; p = 0.032), cardiovascular diseases (OR = 5.47; 95% CI = 1.96-15.27; p = 0.001), subtype (H1N1) pdm09 infection (OR = 2.29; 95% CI = 1.02-5.15; p = 0.046), and viral load (OR = 1.43; 95% CI = 1.09-1.88; p = 0.009). The prognosis score for ICU admission is based on these predictors of severity presented and ROC curve AUC = 0.812 (p < 0.0001). Our results identified viral and host predictors of disease severity in IFA-infected patients, yielding a prognostic score that had a high performance in predicting the IFA patients' ICU admission and better results than a viral load value alone. However, its implementation in health services needs to be validated in a broader population.

Keywords: IL-28B; Index; Influenza A; SARI; Score; Viral load.

MeSH terms

  • Cross-Sectional Studies
  • Humans
  • Influenza A Virus, H1N1 Subtype* / genetics
  • Influenza, Human* / complications
  • Influenza, Human* / epidemiology
  • Intensive Care Units
  • Patient Acuity
  • Retrospective Studies