1. Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study
- Author
-
Zhi Yuan Sun, Long Jiang Zhang, Xiao Xue Liu, Feng Chen, Can Zhang, Rong Hua Tian, Kai Xu, Peng Peng Xu, Bin Fan, Jiang Tao Wang, Guang Ming Lu, Li Na Zhang, Ji Chan Shi, Fei Xia, Rong Pin Wang, Li Qi, Song Luo, Jing Zhong, Qi Rui Zhang, Bing Wan, Wei Zhang, Juan Zhu, Meng Jie Lu, Zi Yue Zu, Wen Hui Fan, Zhi Han Yan, Wen Chen, Chang Sheng Zhou, and Xi Ming Wang
- Subjects
Male ,Medicine (miscellaneous) ,Comorbidity ,Kaplan-Meier Estimate ,030204 cardiovascular system & hematology ,Theranostic Nanomedicine ,law.invention ,0302 clinical medicine ,law ,Risk Factors ,Clinical endpoint ,Medicine ,030212 general & internal medicine ,Hospital Mortality ,Child ,Pharmacology, Toxicology and Pharmaceutics (miscellaneous) ,Aged, 80 and over ,Hazard ratio ,Age Factors ,Middle Aged ,Thorax ,Prognosis ,Intensive care unit ,Child, Preschool ,Female ,Coronavirus Infections ,Research Paper ,Adult ,medicine.medical_specialty ,China ,Adolescent ,Pneumonia, Viral ,03 medical and health sciences ,Betacoronavirus ,Young Adult ,Internal medicine ,Humans ,Risk factor ,Mortality ,Adverse effect ,Pandemics ,Aged ,Proportional Hazards Models ,Retrospective Studies ,business.industry ,Proportional hazards model ,SARS-CoV-2 ,COVID-19 ,Infant ,Retrospective cohort study ,Pneumonia ,medicine.disease ,Coronavirus ,business ,Tomography, X-Ray Computed - Abstract
Background: The risk factors for adverse events of Coronavirus Disease-19 (COVID-19) have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods: This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results: Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR], 6.734; 95% CI; 3.239-14.003, p < 0.001), leukocytosis (HR, 9.639; 95% CI, 4.572-20.321, p < 0.001), lymphopenia (HR, 4.579; 95% CI, 1.334-15.715, p = 0.016) and CT severity score > 14 (HR, 2.915; 95% CI, 1.376-6.177, p = 0.005) on admission, while older age (HR, 2.231; 95% CI, 1.124-4.427, p = 0.022), ≥ 2 comorbidities (HR, 4.778; 95% CI; 2.451-9.315, p < 0.001), leukocytosis (HR, 6.349; 95% CI; 3.330-12.108, p < 0.001), lymphopenia (HR, 3.014; 95% CI; 1.356-6.697, p = 0.007) and CT severity score > 14 (HR, 1.946; 95% CI; 1.095-3.459, p = 0.023) were associated with increased odds of composite adverse outcomes. Conclusion: The risk factors of older age, multiple comorbidities, leukocytosis, lymphopenia and higher CT severity score could help clinicians identify patients with potential adverse events.
- Published
- 2020