Analysis Of The Value Of Cardiodynamicsgram In Early Diagnosis Of Patients With Acute Coronary Syndrome

Research BackgroundThe incidence of Acute Coronary Syndromes(ACS)is increasing year by year in China,which accounts for the first coronary syndromes of the total deaths of urban and rural residents.With the continuous improvement of the treatment of ACS,the mortality of ACS has decreased.However,the rate of sudden cardiac death did not decrease significantly.Studies have shown that the high mortality rate of sudden cardiac death is mainly due to the lack of effective early diagnosis(early warning)technology and ability.In recent years,artificial intelligence technology has developed rapidly in the medical field,and great progress has been made in improving the diagnosis of cardiovascular diseases by electrocardiogram(ECG).The previous research results show that the sensitivity and specificity of cardiodynamicsgram(CDG)in detecting myocardial ischemia when ECG is normal or roughly normal is significantly better than ECG,and it is easy to capture the early weak dynamic signal changes of cardiac electrical activity caused by myocardial ischemia.However,its efficacy in early diagnosis of ACS needs to be futher studied.ObjectiveEarly and rapid identification and diagnosis of ACS is the key to improve the survival rate and prognosis of patients with ACS.For this reason,this study explored the value of CDG,a kind of ECG based on deterministic learning combined with machine learning,in the early diagnosis of ACS patients,and compared it with conventional ECG.MethodsPatients with chest pain as the main initial symptoms in the The People’s Hospital of Baoan Shenzhen from October 2021 to September 2022 were included.The basic clinical data(age,sex,past history,personal history and clinical examination results)were collected.According to the diagnostic criteria of the guidelines for Emergency Rapid diagnosis and treatment of Acute Coronary Syndrome(2019),the patients were divided into ACS group and non-ACS group.SPSS26.0 version software was used to process the relevant data,χ2test was used to analyze the counting data,t test and Mann-Whitney test were used to analyze the measurement data.Draw the receiver operating characteristic curve(ROC)to determine the sensitivity,specificity,positive predictive value(PPV)and negative predictive value(NPV)of CDG,ECG and CDG combined with ECG in early diagnosis of ACS.The difference was statistically significant(P<0.05).ResultsAccording to the diagnostic criteria of the guidelines for Emergency Rapid diagnosis and treatment of Acute Coronary Syndrome(2019),430 patients were divided into ACS group(n=215)and non-ACS group(n=215).There were significant differences in sex,hypertension,diabetes,hyperlipidemia,atherosclerosis and smoking history between the two groups.The sensitivity,specificity,accuracy,PPV,NPV and Youden index of CDG were 93.9%,83.3%,84.9%,93.2%,88.6%and 0.772,respectively;ECG was 82.9%,64.2%,69.9%,79.3%,71.6%,0.433;CDG combined ECG was 74.4%,94.0%,92.5%,78.6%84.2%,0.684.ROC curve analysis showed that the area under ROC curve(AUC)of CDG,ECG and CDG combined ECG were 0.886,0.716 and 0.933,respectively,and the 95%confidence intervals(95%CI)were[0.852～0.914],[0.693～0.778]and[0.905-0.955],respectively.There was significant difference in AUC among the three groups.ConclusionCDG has high sensitivity,specificity,PPV,NPV and AUC in early diagnosis of ACS,and it is significantly better than ECG.The specificity of CDG combined with ECG was higher than that of CDG alone,but the sensitivity decreased accordingly.In short,combined with the results of the study,CDG is expected to become an important means for early diagnosis of ACS patients in emergency department.