Clinical Characteristics and CT Findings in 148 Non-COVID-19 Influenza-Like Illness Cases: A Retrospective Control Study

• Main Authors: Weizheng Shuai (Author), Xuxin Chen (Author), Yi Shan (Author), Wenping Li (Author), Wei Ma (Author), Qiaohui Lu (Author), Dawei Li (Author)
• Format: Book
• Published: Frontiers Media S.A., 2021-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2565; 10.3389/fpubh.2021.616963
• Keywords: computerized tomography; influenza-like illness; influenza; respiratory tract infection; ground glass opacities; consolidation; Public aspects of medicine; RA1-1270
• Source: Frontiers in Public Health, Vol 9 (2021)

Background: This study was to collect clinical features and computed tomography (CT) findings of Influenza-Like Illness (ILI) cases, and to evaluate the correlation between clinical data and the abnormal chest CT in patients with the Influenza-Like Illness symptoms.Methods: Patients with the Influenza-Like Illness symptoms who attended the emergency department of The Six Medical Center of The PLA General Hospital from February 10 to April 1, 2020 were enrolled. Clinical and imaging data of the enrolled patients were collected and analyzed. The association between clinical characteristics and abnormal chest CT was also analyzed.Results: A total of 148 cases were enrolled in this study. Abnormalities on chest CT were detected in 61/148 (41.2%) patients. The most common abnormal CT features were as follows: patchy consolidation 22/61(36.1%), ground-glass opacities 21/61(34.4%), multifocal consolidations 17/61(27.9%). The advanced age and underlying diseases were significantly associated with abnormal chest CT.Conclusions: Abnormal chest CT is a common condition in Influenza-Like Illness cases. The presence of advanced age and concurrent underlying diseases is significantly associated with abnormal chest CT findings in patients with ILI symptoms. The chest CT characteristic of ILI is different from the manifestation of COVID-19 infection, which is helpful for differential diagnosis.