Predictive Value Analysis Of Inflammation Indexes-based Screening Model On Diagnosing Acute Coronary Syndrome

Objective: to set up a screening model based on lab inflammation indexes focusing on acute coronary syndrome(ACS)first diagnosis patients,to provide early risk analysis for high risk groups and clinical reference for early intervention in ACS patients.Methods: Retrospectively collect the lab results of patients during September 2015 and August 2017,including: ACS group with 85 cases,stable coronary angina disease(s CAD)group with 110 cases and normal control group with 54 cases.The lab indexes include five Inflammatory indexes of Myelolipin related phospholipase A2(LP-PLA2),Serum myeloperoxidase(MPO),Hypersensitive C-reactive protein(hs-CRP),Neutrophils/lymphocyte ratio(NLR),Platelet/lymphocyte ratio(PLR),and five biochemical indexes of Homocysteine level(HCY),Serum total cholesterol(TC),Triglyceride(TG),High density lipoprotein cholesterol(HDL-C),Low density lipoprotein cholesterol(LDL-C).Based on the above indexes,the screening and diagnosis model is established and statistical analysis is conducted.The model outputs are compared with clinical diagnoses.Results: 1.Comparing the indexes of the three groups,TC and HDL-C indexes show no significance between groups(p>0.05);Lp-PLA2,MPO,hs-CRP,NLR,PLR,HCY,TG,LDL-C show statistical significance(p<0.05)between ACS group and the two other groups;Lp-PLA2,MPO,PLR indexes show statistical significance(p<0.05)between s CAD group and the normal group.2.Lp-PLA2?MPO?hs-CRP?NLR?PLR?HCY?LDL-C indexes of the positive cases show statistical significance between groups(p<0.05).3.Using single index to diagnose s CAD,the largest two area coverage under ROC curve are LDL-C(0.544)and TC(0.527);using single index to diagnose ACS,the largest three area coverage under ROC curve are MPO(0.779),PLA2(0.751),hs-CRP(0.714);as to the cutoff value of single index,LDL(80.41 %)shows the highest sensitivity indiagnosing ACS,MPO(85.28%)takes the highest specificity,and MBO(0.4528)takes the highest Youden index.4.Using progressive method to do the Logistic regression analysis,Hcy,LDL,PLA2,MPO,hs-CRP and NLR 6 indexes form the ACS screening and predication model.The model formula is also established.Applying the model on ROC curve analysis in ACS diagnosis,the area under curve is 0.924.With cutoff value of 0.3482,the model predicating ACS sensitivity reaches 90.88%,specificity 86.05%,and Youden index 0.7693.5.With the ACS predication model cutoff value of 0.3482,the model accuracy is compared with the clinical diagnosis results,74 of 85 ACS patients show positive,11negative;102 of 122 non-ACS patients show negative,20 positive.6.With the ACS predication model cutoff value of 0.3482,consistency analysis of kappa coefficient between model outputs and clinical diagnoses reaches 0.813.Conclusion: 1.the ACS screening and predictive model based on 6 indexes is highly sensitive to high risk group.2.For the patients with coronary disease,the model can inform the formation and development of unstable plaque of coronary artery,or it may also indicate the occurrence of ACS.