A Predicting Nomogram for Mortality in Patients With COVID-19

Frontiers in Public Health

article

Deng Pan¹  Dandan Cheng²  Yiwei Cao¹  Chuan Hu³  Fenglin Zou⁴  Wencheng Yu¹  Tao Xu¹ 

[1] Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Qingdao University;Department of Hematology, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology;Department of Joint Surgery, Affiliated Hospital of Qingdao University;Department of Biliary-Pancreatic Surgery, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology

关键词: nomogram;    predict;    mortality;    COVID-19;    patients;   

DOI  :  10.3389/fpubh.2020.00461

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Background: The global COVID-19 epidemic remains severe, with the cumulative global death toll reaching more than 207,170 as of May 2, 2020 ( 1 ). Purpose: Our research objective is to establish a reliable nomogram to predict mortality in COVID-19 patients. The nomogram can help us distinguish between patients who are at high risk of death and need close attention. Patients and Methods: For the single-center retrospective study, we collected 21 cases of patients who died in the critical illness area of the Optical Valley Branch of Tongji Hospital, Huazhong University of Science and Technology, from February 9 to March 10. Additionally, we selected 99 patients discharged during this period for analysis. The nomogram was constructed to predict the mortality for COVID-19 patients using the primary group of 120 patients and was validated using an independent cohort of 84 patients. We used multivariable logistic regression analysis to construct the prediction model. The nomogram was evaluated for calibration, differentiation, and clinical usefulness. Results: The predictors included in the nomogram were c-reactive protein, PaO 2 /FiO 2 , and cTnI. The areas under the curves of the nomogram were 0.988 (95% CI: 0.972–1.000) and 0.956 (95% CI, 0.874–1.000) in the primary and validation groups, respectively. Decision curve analysis suggests that the nomogram may have clinical usefulness. Conclusion: This study provides a nomogram containing c-reactive protein, PaO 2 /FiO 2 , and cTnI that can be conveniently used to predict individual mortality in COVID-19 patients. Next, we will collect as many cases as possible from multiple centers to build a more reliable nomogram to predict mortality for COVID-19 patients.

【 授权许可】

CC BY