Author: Lijiao Zeng; Jialu Li; Mingfeng Liao; Rui Hua; Pilai Huang; Mingxia Zhang; Youlong Zhang; Qinlang Shi; Zhaohua Xia; Xinzhong Ning; Dandan Liu; Jiu Mo; Ziyuan Zhou; Zigang Li; Yu Fu; Yuhui Liao; Jing Yuan; Lifei Wang; Qing He; Lei Liu; Kun Qiao
Title: Risk assessment of progression to severe conditions for patients with COVID-19 pneumonia: a single-center retrospective study Document date: 2020_3_30
ID: 8n3q30hy_31
Snippet: We delineated the characteristics of a retrospective cohort of 338 adult patients collected at a single center from Shenzhen city of China, and developed a non-invasive method to evaluate the risk of progression to severe conditions. The independent predisposition factors of progression include old age, high BMI, fever, and co-existing hypertension or diabetes diseases. However, using age as a single prognostic factor could lead to erroneous resu.....
Document: We delineated the characteristics of a retrospective cohort of 338 adult patients collected at a single center from Shenzhen city of China, and developed a non-invasive method to evaluate the risk of progression to severe conditions. The independent predisposition factors of progression include old age, high BMI, fever, and co-existing hypertension or diabetes diseases. However, using age as a single prognostic factor could lead to erroneous results since young patients were not necessarily progression-free. Different from previous studies 4-6 , the severe group in this cohort has a significantly higher proportion of patients with fever symptom at admission (82.9% vs. 54.2%). Moreover, we identified, for the first time, that overweight is associated with disease severity. These findings benefit the risk assessment analysis as we showed that a model combining these indicators can substantially improve the prediction performance as compared to a model that only contains univariate predictor (mean time-dependent AUC= 0.824 versus 0.751).
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