Comparison Of Serum Ceramide Risk Score And GRACE Score In The Diagnosis Of Acute Coronary Syndrome Based On Lasso Regression

Objectives:To explore the serum ceramide risk score,GRACE score combined with Lasso regression based diagnostic efficacy for acute coronary syndromes for comparison and to construct a noninvasive risk prediction model.Methods:120 patients with ACS who were hospitalized in our department of cardiovascular,First Affiliated Hospital of Anhui University of Science and Technology(First People’s Hospital of Huainan)from October 2021 and February 2022.Quantitative analysis of four ceramides in serum was performed by high performance liquid chromatography tandem mass spectrometry to delineate the risk level.Univariate analysis was used for initial screening of potential factors influencing coronary heart disease,and P<0.1 was set to enter the subsequent Lasso regression analysis.The AUC values of Lasso score,GRACE score,and Ceramide Risk Score were calculated and compared separately using multivariate logistic regression analysis,and this was used to assess the predictive efficacy of the three scores for coronary heart disease.Results:The results of univariate analysis suggested that age,albumin b-cox,GRACE score,apolipoprotein A,creatine kinase,and ceramide score Cer(d18:1/16:0),Cer(d18:1/18:0),and Cer(d18:1/16:0)/Cer(d18:1/24:0)were statistically significant.The variables that finally entered the model after further screening by Lasso were GRACE score,albumin b-cox,apolipoprotein A,creatine kinase,lactate dehydrogenase,Cer(d18:1/16:0),and Cer(d18:1/18:0).The diagnostic efficacy of the Score,GRACE score,and ceramide risk score was compared using multiple logistic regression analysis to calculate the diagnostic efficacy of patients with or without ACS,respectively.After the analysis,it was found that the AUC value of the variable Score was 0.763,which was greater than the ceramide score(AUC=0.596)and GRACE score(AUC=0.715).Conclusions:The serum ceramide risk score combined with GRACE score and other constructs of the above predictive models have better diagnostic efficacy for acute coronary syndromes.Figure[2]table[6]reference[147]...