Predictive value of serum creatinine and total bilirubin for long-term death in patients with ischemic heart disease: A cohort study

Author:

Seyiti Zulihuma,Yang Long,Kasimujiang Abudushalamu,Dejite Tuohutasheng,Shan Xue-FengORCID,Gao Xiao-Ming

Abstract

Background Ischemic heart disease (IHD) has a high mortality in the population. Although serum creatinine (Cr) and serum total bilirubin (TBil) are rapid and readily available biomarkers in routine blood tests, there is a lack of literature on the prognostic value of combined Cr and TBil tests for IHD. This study aimed to evaluate a combined equation based on Cr and TBil to predict the long-term risk of death in IHD and to find indicators sensitive to the prognosis of IHD patients. Method In this study, 2625 patients with IHD were included, and the combined value and combined equations of Cr and TBil were obtained by logistic regression analysis based on Cr and TBil collected at the time of admission. Patients were divided into four groups according to the quartiles of the combined value. COX proportional hazard regression model was used to analyze the risk factors for long-term death in IHD patients. Receiver operating characteristic (ROC) curves were used to evaluate the prognostic effect of Cr, TBil and combined value on long-term death events. Results Logistic regression analysis was performed for long-term death events with Cr and TBil as independent variables, and the logit regression model was Logit(P) = 0.0129×TBil+0.007×Cr-0.417. Multifactorial Cox regression analysis showed that high values of the equation were independent risk factors for long-term death events (all-cause death: HR 1.457, 95% CI 1.256–1.689, P<0.001; cardiovascular death: HR 1.452, 95% CI 1.244–1.695, P<0.001). Combined Cr and TBil value are more valuable in predicting long-term death (AUC: 0.609, 95% CI 0.587–0.630, P<0.001). Conclusion Combined Cr and TBil assay is superior to single biomarkers for predicting long-term death in patients with IHD. High values of the equation are independent predictors of long-term death and can be used to identify patients at high risk for IHD.

Funder

the National Natural Science Foundation of China

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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