Relationship between demographic and clinical factors with electrocardiography deviation as a prognostic factor in acute coronary syndrome patients

Background: Acute coronary syndrome (ACS) is one of the causes of disability and death. Levels of Uric acid, blood glucose, and dyslipidemia are the risk factors for the disease, but their role in electrocardiographic changes has not been studied. Based on this, this study aimed to investigate the relationship between some demographic and clinical characteristics with electrocardiographic changes. Methods: This cross-sectional study was performed on 484 patients with Acute Coronary Syndrome admitted to Shahroud Imam Hossein Hospital from the beginning of January to the end of June 2018. In this study, the relationship between demographic, clinical and laboratory variables in patients with the acute coronary syndrome with STE, STD, Dynamic changes and inverted T waves were investigated. The required information was extracted from the Patients' records using the researcher-made checklist. Statistical analysis of data was conducted by using descriptive tests for estimating mean and frequency and statistical-analytical tests including chi-square and ANOVA were performed by SPSS software version 22. Results: The results show that the proportion of STD deviations in women with ACS was 12.6% higher than in men, but the proportion of STE and Dynamic changes in men was 10.4% and 12.2% higher than women, respectively. The proportion of STD, STE, inverted T and Dynamic changes in people with hyperlipidemia was 67.8%, 77.6%, 64.7% and 75.8%, respectively. The proportion of STD, STE, inverted T and Dynamic changes in patients with hypertension were 0.12%, 5.1%, 11.2%, and 19.1%, respectively that there was a difference with patients without high blood pressure. Between addiction, fasting blood sugar and LDL with STD; Between History of heart disease, history of angiography, hypertension, creatinine and WBC with STE; and between creatinine and fasting blood sugar statistically significant differences were observed. Conclusion: There were significant correlations between electrocardiogram changes, gender, addiction, hypertension, creatinine, LDL level, fasting glucose and white blood cell count.