Yun Yang1,2, Xiao-Fei Zhu2,3, Jian Huang1, Cui Chen1,2, Yang Zheng4,5, Wei He6,7, Ling-Hao Zhao1,7, Qian Gao1,2, Xuan-Xuan Huang1,2, Li-Juan Fu1,2, Yu Zhang1,2, Yan-Qin Chang8,9, Huo-Jun Zhang10, Zhi-Jie Lu11,12. 1. The Third Affiliated Hospital of Second Military Medical University, 225 Changhai Road, Shanghai, 200438, China. 2. The Guanggu Branch of the Women and Children's Hospital of Hubei Province, Wuhan, 430070, China. 3. The First Affiliated Hospital of Second Military Medical University, Shanghai, 200438, China. 4. 904 Hospital of PLA Joint Logistic Support Force, Wuxi, 215000, Jiangsu, China. 5. Tongji Taikang Hospital, Wuhan, 430050, China. 6. 924 Hospital of PLA Joint Logistic Support Force, Guilin, 541002, Guangxi, China. 7. Huoshen Mountain Hospital, Wuhan, 430113, China. 8. The Third Affiliated Hospital of Second Military Medical University, 225 Changhai Road, Shanghai, 200438, China. changyanqin1018@163.com. 9. Huoshen Mountain Hospital, Wuhan, 430113, China. changyanqin1018@163.com. 10. The First Affiliated Hospital of Second Military Medical University, Shanghai, 200438, China. chyyzhj@163.com. 11. The Third Affiliated Hospital of Second Military Medical University, 225 Changhai Road, Shanghai, 200438, China. luzhijieehbh@126.com. 12. The Guanggu Branch of the Women and Children's Hospital of Hubei Province, Wuhan, 430070, China. luzhijieehbh@126.com.
Abstract
BACKGROUND: To develop an effective model of predicting fatal outcomes in the severe coronavirus disease 2019 (COVID-19) patients. METHODS: Between February 20, 2020 and April 4, 2020, consecutive confirmed 2541 COVID-19 patients from three designated hospitals were enrolled in this study. All patients received chest computed tomography (CT) and serological examinations at admission. Laboratory tests included routine blood tests, liver function, renal function, coagulation profile, C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and arterial blood gas. The SaO2 was measured using pulse oxygen saturation in room air at resting status. Independent high-risk factors associated with death were analyzed using Cox proportional hazard model. A prognostic nomogram was constructed to predict the survival of severe COVID-19 patients. RESULTS: There were 124 severe patients in the training cohort, and there were 71 and 76 severe patients in the two independent validation cohorts, respectively. Multivariate Cox analysis indicated that age ≥ 70 years (HR = 1.184, 95% CI 1.061-1.321), panting (breathing rate ≥ 30/min) (HR = 3.300, 95% CI 2.509-6.286), lymphocyte count < 1.0 × 109/L (HR = 2.283, 95% CI 1.779-3.267), and interleukin-6 (IL-6) > 10 pg/ml (HR = 3.029, 95% CI 1.567-7.116) were independent high-risk factors associated with fatal outcome. We developed the nomogram for identifying survival of severe COVID-19 patients in the training cohort (AUC = 0.900, 95% CI 0.841-0.960, sensitivity 95.5%, specificity 77.5%); in validation cohort 1 (AUC = 0.811, 95% CI 0.763-0.961, sensitivity 77.3%, specificity 73.5%); in validation cohort 2 (AUC = 0.862, 95% CI 0.698-0.924, sensitivity 92.9%, specificity 64.5%). The calibration curve for probability of death indicated a good consistence between prediction by the nomogram and the actual observation. The prognosis of severe COVID-19 patients with high levels of IL-6 receiving tocilizumab were better than that of those patients without tocilizumab both in the training and validation cohorts, but without difference (P = 0.105 for training cohort, P = 0.133 for validation cohort 1, and P = 0.210 for validation cohort 2). CONCLUSIONS: This nomogram could help clinicians to identify severe patients who have high risk of death, and to develop more appropriate treatment strategies to reduce the mortality of severe patients. Tocilizumab may improve the prognosis of severe COVID-19 patients with high levels of IL-6.
BACKGROUND: To develop an effective model of predicting fatal outcomes in the severe coronavirus disease 2019 (COVID-19) patients. METHODS: Between February 20, 2020 and April 4, 2020, consecutive confirmed 2541 COVID-19patients from three designated hospitals were enrolled in this study. All patients received chest computed tomography (CT) and serological examinations at admission. Laboratory tests included routine blood tests, liver function, renal function, coagulation profile, C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and arterial blood gas. The SaO2 was measured using pulse oxygen saturation in room air at resting status. Independent high-risk factors associated with death were analyzed using Cox proportional hazard model. A prognostic nomogram was constructed to predict the survival of severe COVID-19patients. RESULTS: There were 124 severe patients in the training cohort, and there were 71 and 76 severe patients in the two independent validation cohorts, respectively. Multivariate Cox analysis indicated that age ≥ 70 years (HR = 1.184, 95% CI 1.061-1.321), panting (breathing rate ≥ 30/min) (HR = 3.300, 95% CI 2.509-6.286), lymphocyte count < 1.0 × 109/L (HR = 2.283, 95% CI 1.779-3.267), and interleukin-6 (IL-6) > 10 pg/ml (HR = 3.029, 95% CI 1.567-7.116) were independent high-risk factors associated with fatal outcome. We developed the nomogram for identifying survival of severe COVID-19patients in the training cohort (AUC = 0.900, 95% CI 0.841-0.960, sensitivity 95.5%, specificity 77.5%); in validation cohort 1 (AUC = 0.811, 95% CI 0.763-0.961, sensitivity 77.3%, specificity 73.5%); in validation cohort 2 (AUC = 0.862, 95% CI 0.698-0.924, sensitivity 92.9%, specificity 64.5%). The calibration curve for probability of death indicated a good consistence between prediction by the nomogram and the actual observation. The prognosis of severe COVID-19patients with high levels of IL-6 receiving tocilizumab were better than that of those patients without tocilizumab both in the training and validation cohorts, but without difference (P = 0.105 for training cohort, P = 0.133 for validation cohort 1, and P = 0.210 for validation cohort 2). CONCLUSIONS: This nomogram could help clinicians to identify severe patients who have high risk of death, and to develop more appropriate treatment strategies to reduce the mortality of severe patients. Tocilizumab may improve the prognosis of severe COVID-19patients with high levels of IL-6.
Entities:
Keywords:
Nomogram; Prediction; Severe COVID-19; Survival
Authors: Yan-Rong Guo; Qing-Dong Cao; Zhong-Si Hong; Yuan-Yang Tan; Shou-Deng Chen; Hong-Jun Jin; Kai-Sen Tan; De-Yun Wang; Yan Yan Journal: Mil Med Res Date: 2020-03-13