Jing Zhou1,2, Lili Huang3, Jin Chen4, Xiaowei Yuan5, Qinhua Shen5, Su Dong6, Bei Cheng7,8, Tang-Meng Guo7,8. 1. Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 2. Department of Breast and Thyroid Surgery, People's Hospital of Dongxihu District Wuhan City and Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China. 3. Department of Clinical Laboratory Medicine, People's Hospital of Dongxihu District Wuhan City and Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China. 4. Department of Information Center, People's Hospital of Dongxihu District Wuhan City and Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China. 5. Department of Medical Services Division, People's Hospital of Dongxihu District Wuhan City and Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China. 6. Department of Science Education, People's Hospital of Dongxihu District Wuhan City and Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China. 7. Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 8. Institute of Gerontology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract
BACKGROUND: Since December 2019, the cumulative number of coronavirus disease 2019 (COVID-19) deaths worldwide has reached 1,013,100 and continues to increase as of writing. Of these deaths, more than 90% are people aged 60 and older. Therefore, there is a need for an easy-to-use clinically predictive tool for predicting mortality risk in older individuals with COVID-19. OBJECTIVE: To explore an easy-to-use clinically predictive tool 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 12 January to 26 February 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. Among the results of laboratory tests, neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase, albumin, urea nitrogen and D-dimer (NLAUD) 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 < .0001), lactate dehydrogenase (OR = 73.4, 95% CI 11.8-456.8, p < .0001), albumin (OR < 0.1, 95% CI <0.1-0.2, p < .0001), urea nitrogen (OR = 12.0, 95% CI 3.0-48.4, p = .0005), and D-dimer (OR = 13.6, 95% CI 3.4-54.9, p = .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 < .001). Bootstrap validation generated the similar sensitivity and specificity. CONCLUSIONS: We designed an easy-to-use clinically predictive tool for early identification and stratified treatment of older patients with severe COVID-19.
BACKGROUND: Since December 2019, the cumulative number of coronavirus disease 2019 (COVID-19) deaths worldwide has reached 1,013,100 and continues to increase as of writing. Of these deaths, more than 90% are people aged 60 and older. Therefore, there is a need for an easy-to-use clinically predictive tool for predicting mortality risk in older individuals with COVID-19. OBJECTIVE: To explore an easy-to-use clinically predictive tool 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 12 January to 26 February 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. Among the results of laboratory tests, neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase, albumin, ureanitrogen and D-dimer (NLAUD) 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 < .0001), lactate dehydrogenase (OR = 73.4, 95% CI 11.8-456.8, p < .0001), albumin (OR < 0.1, 95% CI <0.1-0.2, p < .0001), ureanitrogen (OR = 12.0, 95% CI 3.0-48.4, p = .0005), and D-dimer (OR = 13.6, 95% CI 3.4-54.9, p = .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 < .001). Bootstrap validation generated the similar sensitivity and specificity. CONCLUSIONS: We designed an easy-to-use clinically predictive tool for early identification and stratified treatment of older patients with severe COVID-19.
Authors: Rashid Nadeem; Aju Rafeeq; Anas A Aga; Ayesha Siddiqua; Ekta Sharma; Doaa Anwer; Mohd Kafeel Khan; Mohamed Abdulla Mohammed Hussein; Yusra Omar Alshaikh SayedAhmed; Farooq Ahmad Dar Journal: Cureus Date: 2022-07-18