Imaging Features of Patients with Coronavirus Disease 2019 with/without Underlying Diseases

Abstract

Objective: To explore the imaging characteristics of patients with novel coronavirus pneumonia (COVID-19) combined with different underlying diseases. Materials and methods: COVID-19 was diagnosed in 153 patients at Beijing Shijitan Hospital, Capital Medical University, from November 16, 2022 to December 16, 2022, and data were retrospectively collected. All patients underwent chest CT scan from 1 to 14 days after onset and were divided into two groups based on the presence or absence of underlying diseases. Forty-three patients had underlying diseases, and 110 patients had none. We compared the differences between the two groups. Result: The comparison between the two groups showed statistically significant differences in age, cough, bilateral lung distribution, diffuse distribution, honeycomb-like changes in the lungs, patchy distribution, large patchy distribution, band distribution, crazy-paving sign, air bronchogram sign, traction bronchiectasis, and pleural effusion. Conclusion: Fever and cough are the most common clinical symptoms in patients with COVID-19. Chest CT showed multiple lesions in both lungs. The most common types of lesions were thickening of bronchovascular bundle and GGO. Patients with underlying diseases had more honeycomb-like changes, crazy-paving sign, air bronchogram sign, traction bronchiectasis, and pleural effusion than those without underlying diseases. Chest thin-slice CT scan provides a key reference for the early detection and diagnosis of the disease.

Keywords

• x-ray computer
• tomography
• covid-19
• underlying disease