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Aibin Wang, Guiju Gao, Sa Wang, Meiling Chen, Fang Qian, Weiming Tang, Yanli Xu, Rui Song, Liwei Zhuang, Xiaoyang Ma, Tianwei Zhao, Xiaodi Guo, Wei Li, Xudong Wang, Baoliang Li, Chun Hu, Zhihai Chen, Fujie Zhang
(Department of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland))
Med Sci Monit 2020; 26:e925974
Coronavirus disease 2019 (COVID-19) is a new infectious disease, and acute respiratory syndrome (ARDS) plays an important role in the process of disease aggravation. The detailed clinical course and risk factors of ARDS have not been well described.
MATERIAL AND METHODS: We retrospectively investigated the demographic, clinical, and laboratory data of adult confirmed cases of COVID-19 in Beijing Ditan Hospital from Jan 20 to Feb 29, 2020 and compared the differences between ARDS cases and non-ARDS cases. Univariate and multivariate logistic regression methods were employed to explore the risk factors associated with ARDS.
RESULTS: Of the 130 adult patients enrolled in this study, the median age was 46.5 (34-62) years and 76 (58.5%) were male. ARDS developed in 26 (20.0%) and 1 (0.8%) death occurred. Fever occurred in 114 patients, with a median highest temperature of 38.5 (38-39)°C and median fever duration of 8 (3-11) days. The median time from illness onset to ARDS was 10 (6-13) days, the median time to chest CT improvement was 17 (14-21) days, and median time to negative nucleic acid test result was 27 (17-33) days. Multivariate regression analysis showed increasing odds of ARDS associated with age older than 65 years (OR=4.75, 95% CL1.26-17.89, P=0.021), lymphocyte counts [0.5-1×10⁹/L (OR=8.80, 95% CL 2.22-34.99, P=0.002); <0.5×10⁹/L(OR=36.23, 95% CL 4.63-2083.48, P=0.001)], and temperature peak ≥39.1°C (OR=5.35, 95% CL 1.38-20.76, P=0.015).
CONCLUSIONS: ARDS tended to occur in the second week of the disease course. Potential risk factors for ARDS were older age (>65 years), lymphopenia (≤1.0×10⁹/L), and temperature peak (≥39.1°C). These findings could help clinicians to predict which patients will have a poor prognosis at an early stage.