Technology and Health Care | 2021

Prediction and follow-up of risk factors for severe SARS-CoV-2 pneumonia and application of CT visual scoring

 
 
 
 
 
 
 
 
 
 
 
 

Abstract


BACKGROUND: The SARS-CoV-2 pneumonia infection is associated with high rates of hospitalization and mortality and this has placed healthcare systems under strain. Our study provides a novel method for the progress prediction, clinical treatment and prognosis of NCP, and has important clinical value for timely treatment of severe NCP patients. OBJECTIVE: To summarize the clinical features and severe illness risk factors of the patients with novel coronavirus pneumonia (NCP), in order to provide support for the progression prediction, clinical treatment and prognosis of NCP patients. MATERIALS AND METHODS: A total of 196 NCP patients treated in our hospital from January 25, 2020 to June 21, 2020 were divided into the severe group and the mild group. The clinical features of the two groups were analyzed and compared. The risk factors were explored by using multivariate logistic regression, and the receiver operating characteristic (ROC) curve was obtained. The correlations of the risk factors with the prognosis of NCP were investigated combined with the lung function test. RESULTS: The primary clinical symptoms of 196 cases of NCP included fever in 167 cases (85.2%) and cough in 121 cases (61.73%). The chest computed tomography (CT) scans of the 178 cases (90.81%) showed a typical ground-glass opacification. In 149 cases, the lymphocyte count was decreased, while the levels of creatine kinase (CK), lactate dehydrogenase (LDH), c-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and D-dimer (D-D) increased. 44 cases (22.45%) were found to be severely ill. The multivariate logistic regression analysis demonstrated that age, underlying disease, length of hospital stay, body mass index (BMI), LDH, chest CT visual score, absolute lymphocyte count (ALC) and CRP were risk factors for severe

Volume 29
Pages 153 - 164
DOI 10.3233/THC-218016
Language English
Journal Technology and Health Care

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