Abstract
Background: This study aimed to explore the predictive value of a clinical biochemistry-based nomogram in COVID-19.Methods: The plasma or serum concentrations/levels of carcinoembryonic antigen (CEA) and other biomarkers, e.g., C-reactive protein (CRP), white blood cell (WBC), interleukin-6 (IL-6), ferritin (Fer), procalcitonin (PCT), lymphocyte percentage (L%), D-dimer (D2), and neutrophils percentage (Neu%), were assessed in 314 hospitalized patients with confirmed COVID-19. The area under the curve was used to estimate the diagnostic and prognostic value for COVID-19. Cox and logistic regression analyses were used to estimate the independent prognostic risk factors for the survival of patients with COVID-19.Results: Receiver operating characteristic (ROC) curves were used to determine the area under the curve (AUC) values for CEA, IL-6, CRP, PCT, Fer, D-dimer levels and L%, Neu%, and WBC to assess disease classification. The critical values for these markers to predict severe disease type were then determined. The hazard ratio of prognosis for risk of COVID-19 identified CEA, WBC, CRP, PCT, Fer, D-dimer, Neu%, and L% as independent prognostic factors. For the nomogram of overall survival (OS), the C-index was 0.84, demonstrating a good discriminative performance.Conclusions: An OS nomogram for the clinical diagnosis and treatment of COVID-19 was constructed using biomarkers. These data will be useful for the diagnosis, management, and therapy of COVID-19.
Highlights
Coronavirus disease 2019 (COVID-19) has become a worldwide threat to human health
Receiver operating characteristic (ROC) curves were used to determine the area under the curve (AUC) values for carcinoembryonic antigen (CEA), IL-6, C-reactive protein (CRP), PCT, Fer, D-dimer levels and L%, Neu%, and white blood cell (WBC) to assess disease classification
- According to the hazard ratio for prognosis, we identified high risk factors for patient overall survival (OS)
Summary
Coronavirus disease 2019 (COVID-19) has become a worldwide threat to human health. It is caused by infection with a virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1]. Our previous study noted that the carcinoembryonic antigen (CEA) level is an independent prognostic marker for COVID-19 [6]. We aimed to explore the value of all the above markers to diagnose and predict the prognosis of COVID-19. We aimed to use these factors to construct and validate a nomogram to predict the overall survival (OS) of patients with COVID-19. This study aimed to explore the predictive value of a clinical biochemistry-based nomogram in COVID-19
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