Clinical Features Predicting Mortality Risk in Older Patients with COVID-19

Abstract

Background: Since December 2019, the cumulative number of coronavirus disease-2019 (COVID-19) deaths in China has reached 3,321. More than 90% of these cases were ages 60 and older. By April 1, 2020, the worldwide death toll reached 44,228 and continues to increase as of writing. However, information on the clinical features predicting the mortality risk in older individuals with COVID-19 is limited.Objective : To explore the clinical features that may be utilized in predicting mortality risk in older patients with COVID-19. Methods: A retrospective analysis of 118 older patients with COVID-19 admitted to the Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China from January 12 to February 26, 2020. The main results of epidemiological, demographic, clinical, and laboratory tests on admission were collected and compared between dying and discharged patients. Results: No difference in major symptoms was observed between dying and discharged patients, whereas variations in vital signs and results of laboratory tests were observed. Among these indicators, NLR, albumin, lactate dehydrogenase, urea nitrogen, and D-dimer show greater differences and have better regression coefficients (β) when using hierarchical comparisons in a multivariate logistic regression model. Predictors of mortality based on better regression coefficients (β) included NLR (OR=31.2, 95% CI 6.7–144.5, p<0.0001), albumin (OR=0.0, 95% CI 0.0–0.2, p<0.0001), lactate dehydrogenase (OR=73.4, 95% CI 11.8–456.8, p<0.0001), urea nitrogen (OR=12.0, 95% CI 3.0–48.4, p=0.0005), and D-dimer (OR=13.6, 95% CI 3.4–54.9, p=0.0003). According to the above indicators, a predictive NLAUD score was calculated on the basis of a multivariate logistic regression model to predict mortality. This model showed a sensitivity of 0.889, specificity of 0.984, and a better predictive ability than CURB-65 (AUROC = 0.955 vs. 0.703, p < 0.001). Conclusions: The levels of NLR, albumin, lactate dehydrogenase, urea nitrogen, and D-dimer can be used for early identification of severely sick older patients with COVID-19. We designed an easy-to-use clinically predictive tool for stratifying these patients and providing guidance to make further clinical decisions. Funding Statement: The National Natural Science Foundation of P. R. China supported this study (No.81701376). Declaration of Interests: The authors declare that they have no competing interests. Ethics Approval Statement: This study has been reviewed by the institutional review committees of the relevant centers. In this retrospective study, the ethics committee agreed to exempt patients from signing informed consent forms.