The clinical significance of CAD in patients with severe and critically-severe Omicron infections
ZHU Mingxin1, HUANG Jianliang1, XIA Mingkai1, PENG Bo1, LI Linjun3, ZHANG Jianhui1, WEN Fang4, HU Linlin1, LEI Mingsheng1,2
1. Zhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie 427000, China; 2. Jishou University Zhangjiajie College, Zhangjiajie 427000, China; 3. School of Public Health, Kunming Medical University, Kunming 650500, China; 4. Medical College of Jishou University, Jishou 416000, China
Abstract:Objective The purpose of this study is to investigate the clinical significance of computer-aided diagnosis (CAD) in patients with severe and critically-severe Omicron infections in Zhangjiajie. The study aims to provide additional references for the treatment of these patients. Method From December 2022 to January 2023, we collected various clinical data such as qSOFA score, laboratory test results, and lung CT scans from patients who were hospitalized with severe and critically-severe Omicron infections. Additionally, in this study, we utilized computer-aided diagnosis to segment and reconstruct the lung CT, enabling us to accurately calculate the proportion of inflammation. Our objective was to compare the clinical characteristics and inflammation proportion of severe and critically-severe, with the aim of identifying any potential differences and exploring the relationship between inflammation proportion and critical illness. Results A total of 116 severe and critically-severe patients were included in this study, The median age of the patients was 73.0(ranging from 65.0 to 84.0) years, and 60.3% (n=70) of patients were admitted to the ICU. Among the patients, 86.2% (n=100) patients had underlying diseases. proportion of inflammation, qSOFA score, C-reactive protein, and D-dimer were higher in critically-severe patients than in severe patients (P<0.05). The higher the proportion of inflammation, the easier it is to develop critical illness (r=0.24, P=0.009). The sensitivity, specificity and accuracy of inflammation proportion in the diagnosis of progress to critically-severe were 0.656, 0.745 and 0.638, the cutoff value was 31.46%. Conclusion Computer-aided diagnosis has a certain value in evaluating the condition of patients with severe COVID-19 pneumonia. The higher the proportion of inflammation, the greater the possibility of the disease progressing to critical illness, it is hypothesized that if the proportion of lung inflammation is equal to or greater than 31.46%, the patient is at a high risk of progressing to critical illness.
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