Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study

Zhang, Shuai; Guo, Mengfei; Duan, Limin; Wu, Feng; Hu, Guorong; Wang, Zhihui; Huang, Qi; Liao, Tingting; Xu, Jing; Ma, Yanling; Lv, Zhi; Xiao, Wenjing; Zhao, Zilin; Tan, Xingyi; Meng, Daquan; Zhang, Shujing; Zhou, Enbo; Yin, Zhengrong; Wang, Geng; Wang, Xuan; Zhang, Jianchu; Chen, Jianguo; Zhang, Yu; Jin, Yang

doi:10.1186/s13054-020-03123-x

Cited by 60 publications

(69 citation statements)

References 30 publications

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“…However, one common limitation is that in most previous studies, NLR or PLR was included in the generalized linear models as a continuous variable, with the assumption that there was a linear association between NLR/PLR and the dependent outcomes. Even in some prediction model [ 4 ], researchers only focused on the impact of higher NLR/PLR value while the effect of low NLR/PLR was ignored. However, in most cases, extremely low NLR or PLR represented low neutrophil and platelet, which, according to clinical experience, was also associated with poor outcomes.…”

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confidence: 99%

Predictive value of neutrophil to lymphocyte and platelet to lymphocyte ratio in COVID-19

2020

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confidence: 99%

Predictive value of neutrophil to lymphocyte and platelet to lymphocyte ratio in COVID-19

2020

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“…Previous studies have shown several prediction models with different parameters [2,26,32,33]. Compared with other studies, the predictive effect of age, panting, and lymphopenia has been described in previous reports, while the main feature of this study is the analysis of the prognostic value of IL-6 in severe COVID-19 patients for the rst time.…”

Section: Discussionmentioning

confidence: 81%

Nomogram for Prediction of fatal outcome in Patients with Severe COVID-19: A Multicenter Study

Yang

Zhu

Huang

et al. 2020

Preprint

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Background & Aims: To develop an effective model of predicting fatalOutcome in the severe coronavirus disease 2019 (COVID-19) patients.Methods: Between February 20, 2020 and April 4, 2020, consecutive COVID-19 patients from three designated hospitals were enrolled in this study. 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 IL-6 >10pg/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 interleukin-6 (IL-6) receiving tocilizumab was 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.

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“…Previous studies have shown several prediction models with different parameters [2,25,31,32]. Compared with other studies, the prediction effect of age, panting, and lymphopenia has been described in previous reports, while the main feature of this study is analysis of the prognostic value of IL-6 in severe COVID-19 patients for the rst time.…”

Section: Discussionmentioning

confidence: 84%

Nomogram for Prediction of fatal outcome in Patients with Severe COVID-19: A Multicenter Study

Yang

Zhu

Huang

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Background & Aims: To develop an effective model of predicting fatalOutcome in the severe coronavirus disease 2019 (COVID-19) patients.Methods: Between February 20, 2020 and April 4, 2020, consecutive COVID-19 patients from three designated hospitals were enrolled in this study. 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 IL-6 >10pg/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 0.698-0.924], sensitivity 77.3%, specificity 73.5); in validation cohort 2 (AUC 0.862, [95% CI 0.763-0.961], 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 interleukin-6 (IL-6) receiving tocilizumab was 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.

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Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study

Cited by 60 publications

References 30 publications

Predictive value of neutrophil to lymphocyte and platelet to lymphocyte ratio in COVID-19

Predictive value of neutrophil to lymphocyte and platelet to lymphocyte ratio in COVID-19

Nomogram for Prediction of fatal outcome in Patients with Severe COVID-19: A Multicenter Study

Nomogram for Prediction of fatal outcome in Patients with Severe COVID-19: A Multicenter Study

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