Direct antiglobulin test type, red blood cell distribution width, and estimated glomerular filtration rate for early prediction of in-hospital mortality of patients with COVID-19 - Fei Chen; Jing Wang; Xinhong Jin; Bin Li; Yili Ying; Yufen Zheng; Guoguang Lu; Jun Li; Bo Shen (Computational and Structural Biotechnology Journal)
Objective: This study aimed to investigate the correlation between COVID-19 and the direct antiglobulin test (DAT) and establish an in-hospital mortality risk predictive model based on the DAT type, which can be used for the early prediction of inpatients with COVID-19. Methods: In this study, 502 patients admitted to our hospital who underwent DAT testing from January 29 to February 8, 2023, were included (252 DAT-positive and 250 DAT-negative). Among them, 241 cases of COVID-19 were screened(171 DAT-positive and 70 DAT-negative), clinical and laboratory indicators were compared between DAT-positive and DAT-negative groups. Univariate and multivariate logistic regression analysis, the Kaplan-Meier survival curve and receiver operating curves were used to explore the relation between the DAT type and in-hospital mortality of patients with COVID-19. Results: The proportion of confirmed COVID-19 cases was higher in the DAT-positive group than in the DAT-negative group (67.9 % vs. 28.0 %, P < 0.05). Patients with COVID-19 in the DAT-positive group had higher age-adjusted Charlson comorbidity index scores, red blood cell distribution width (RDW), lactate dehydrogenase, prothrombin time, D-dimer, creatinine, and high-sensitive cardiac troponin T levels than the negative group (P < 0.05), In contrast, hemoglobin and estimated glomerular filtration rate (eGFR) levels were lower in the DAT-positive group. The DAT-positive group also had a higher red blood cell usage volume and in-hospital mortality rate than the DAT-negative group. The mortality rate of patients with COVID-19 with both IgG and C3d positive was higher than that of the other groups. Multivariate logistic regression analysis showed that RDW and eGFR were associated with mortality in patients with COVID-19. The combined predictive model of DAT type, RDW, and eGFR showed an area under the curve of 0.782, sensitivity of 0.769, and specificity of 0.712 in predicting in-hospital mortality risk in patients with COVID-19. Conclusion: The established predictive model for in-hospital mortality risk of patients with COVID-19 based on DAT type, RDW, and eGFR can provide a basis for timely intervention to reduce the mortality rates of patients with COVID-19. This model is accessible at https://jijijiduola.shinyapps.io/0531// for research purposes.