Comparison of Chest Computed Tomography Findings in Patients with H1N1 and Coronavirus Disease-2019 Pneumonia

CT Differences between H1N1 and COVID-19 Pneumonia

Authors

  • Sadullah Şimşek Department of Radiology, Nusaybin State Hospital, Mardin, Türkiye
  • Cihan Akgül Özmen Department of Radiology, Dicle University Faculty of Medicine, Diyarbakır, Türkiye

Keywords:

COVID-19, pneumonia, CT, influenza virus, coronavirus

Abstract

Objective: In this study, we compared the differences between highresolution computed tomography (CT) features of two types of viral pneumonia associated with H1N1 virus and coronavirus disease-2019 (COVID-19).
Methods: A total of 25 patients with H1N1 pneumonia were compared with 150 patients with COVID-19 pneumonia. The findings were analyzed by IBM SPSS Statistics for Windows, version 22 (IBM Corp., Armonk, N.Y., USA). CT findings were compared between groups by chi-square test, and scale variables were compared using the t-test. Finally, significant findings for the H1N1 or COVID-19 groups were evaluated by logistic regression analysis.
Results: The median age of COVID-19 pneumonia patients was 54.6±15.9 years, and the median age of H1N1 pneumonia patients was 46.2±12.4 years (p<0.01). H1N1 pneumonia patients were younger than COVID-19 pneumonia patients. Based on the distribution pattern, diffuse pattern, peripheral pattern, and bronchopulmonary infiltration were observed more frequently in COVID-19 pneumonia (46.0%, 80.7%, 49.3%, respectively, p<0.05). Mediastinal lymphadenopathy and pleural effusion were observed more frequently in patients with H1N1 pneumonia (24% and 36%, respectively, p<0.05). Logistic regression analysis demonstrated that advanced age and a diffuseperipheral pattern indicated COVID-19 (p=0.031, p=0.029).
Conclusion: Most of the lesions caused by COVID-19 pneumonia are located in the peripheral region and near the pleura, whereas those caused by influenza virus pneumonia are far from the peripheral region.

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Published

26.06.2024

Issue

Section

Original Research