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Updated: Dec 15, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Clinical and CT features of the COVID-19 infection: comparison among four different age groups
Wei Li1, Yijie Fang1, Jianwei Liao1
1Guangdong Provincial Key Laboratory of Biomedical Imaging, Department of Radiology, The Fifth Affiliated Hospital, Sun Yat-Sen University, 52 East Meihua Rd, New Xiangzhou, Zhuhai, Guangdong Province, China.
Purpose:
To compare and analyze the clinical and CT features of coronavirus disease 2019 (COVID-19) among four different age groups.
Methods:
97 patients (45 males, 52 females, mean age, 66.2 ± 5.0) with chest CT examination and positive reverse transcriptase-polymerase chain reaction test (RT-PCR) from January 17, 2020 to February 21, 2020 were retrospectively studied. The patients were divided into four age groups (children [0-17 years], young adults [18-44 years], middle age [45-59 years], and senior [≥ 60 years]) according to their age after the diagnosis was made based on PCR test and clinical symptoms.
Results:
Comorbidities such as hypertension, diabetes mellitus, and heart disease are more common in the senior group. Cluster onset (two or more confirmed cases in a small area) is more common in the children group and senior group. Older patients were found to have a higher incidence of the highest clinical classification (severe or critical) in these four groups. Senior patients have a higher incidence of large/multiple ground-glass opacity (GGO). Child patients are mostly negative for chest CT or with involvement of only one lobe of the lung; while in older patients, there was a higher incidence of involvement of four or five lung lobes. The frequency of lobe involvement was also found to have significant differences in the four age groups.
Conclusion:
The clinical and imaging features of patients in different age groups were found to be significantly different. A better understanding of the age differences in comorbidities, cluster onset, highest clinical classification, large/multiple GGO, numbers of lobes affected, and frequency of lobe involvement can be useful in the diagnosis of COVID-19 patients of different ages.
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