DIAGNOSTIC ABILITY OF ACUTE MYOCARDIAL INFARCTION SYMPTOMS INDUCED BY INTENSE EXERCISE BASED ON HUMAN SURFACE ELECTROCARDIOGRAM

Abstract

Background: Acute myocardial infarction (AMI) is a serious cardiovascular emergency with a high incidence and mortality rate worldwide, and the risk is significantly increased especially after participation in vigorous physical activity. Although biomarkers such as electrocardiogram (ECG), Holter (Holter), brain natriuretic peptide (BNP), and systemic inflammatory response Index (SIRI) each have advantages in the diagnosis of AMI, application alone can lead to false positive or false negative results. The aim of this study was to evaluate the combined application of these indicators in the diagnosis of AMI in the context of intense exercise. Purpose: To evaluate the diagnostic ability of the combined application of ECG, holter ECG and serum biomarkers, so as to provide a more accurate diagnostic strategy for the clinic, especially for AMI caused by intense exercise. Method: A total of 70 patients with acute myocardial infarction (AMI) who were admitted to Taizhou Cancer Hospital from October 2022 to October 2023 (all caused by intense physical exercise) and 50 non-AMI control patients with atypical chest pain symptoms and no coronary artery abnormalities were selected. ECG testing, Holter monitoring, BNP and SIRI testing were performed separately, and a comprehensive evaluation was conducted through a combination of indicators. Finally, the condition of coronary artery lesions was confirmed through coronary angiography and image interpretation methods to verify diagnostic accuracy. Results The research results showed that there were significant differences in the detection rate of fQRS waves among patients with different types of coronary artery lesions: 7.36% in patients with single vessel lesions, 73.71% in patients with double vessel lesions, and 83.37% in patients with triple vessel lesions (P<0.05). The SDNN, SDANN, RMSSD, and PNN50 of the study group were significantly lower than those of the control group, while serum BNP and SIRI were significantly higher than those of the control group (P<0.05). Multivariate logistic regression analysis showed that SDNN (β=0.710, OR=2.034, P<0.05), SDANN (β=0.725, OR=2.062, P<0.05), RMSSD (β=0.742, OR=2.108, P<0.05), PNN50 (β=0.679, OR=1.988, P<0.05), BNP (β=0.850, OR=2.355, P<0.05), and SIRI (β=0.568, OR=1.765, P<0.05) were all independent risk factors for poor prognosis. ROC curve analysis showed that the combined detection of electrocardiogram indicators with BNP and SIRI levels achieved an AUC of 0.975 in the diagnosis of AMI, significantly better than single indicators, with sensitivity and specificity close to 0.9 (P<0.001). Conclusion: The combination of ECG, Holter, BNP, and SIRI can significantly improve the diagnostic accuracy of AMI, especially in patients after strenuous physical exercise. Studies have confirmed that heart rate variability and serum markers are independent risk factors for poor prognosis of AMI. This comprehensive diagnostic strategy helps to identify and manage patients with exercise-induced AMI earlier and more accurately in clinical practice.