Assessment of Risk Factors in Patients With Myocardial Infarction

Abstract

Background:Coronary artery diseases (CAD) are one of the important health problems in the world, although considerable progresses have been made to decrease the mortality, they are still the first cause of death in many countries. Hence, the necessity of examining effective factors and risk factors on CAD can be one of the most important health priorities in many countries like Iran.Objective:This study was performed to assess the risk factors in patients with myocardial infarction (MI) in Zahedan.Materials and Methods:This is a cross sectional study in which 213 patients were examined. They had been diagnosed to have heart failure. Data gathering took 18 months. Data gathering tool was a designed checklist which was filled up by an experienced nurse during interview. Obtained results were recorded in files and analyzed in SPSS 21.Results:Results showed that 70% of patients were women and only 30% were men. 48% of them were illiterate and patients mean age was 58.3. SD had been 12.6. The mean of pain onset time till referring to hospital was 11 hours with SD of 2.1. 17% of patients (coronary artery diseases history), 25.5% (hypertension history), 26% (diabetes history), 15.5% (cholesterol history), 13% (smoking) and 3% have reported CABG history. The majority of people who referred had inferior MI (40.4%). 67.1% normal rhythm, 2.8% atrial fibrillation and 16% had ventricular tachycardia. Statistical tests showed a significant correlation between sex and the mean of referring time (p<0.05) but the relation between age and referring time was not significant.Conclusion:Effective risk factors on MI were recognized in this study. Some of them such as age, sex and education cannot be modified but many are controllable such as hypertension, diabetes, cholesterol, and smoking and on time referring after pain onset. Having considered the results of this study health promotion for society and especially vulnerable people can be provided by omitting or reducing risk factors.

Predictive factors for myocardial infarction in pre-hospital emergency care

“…Scientific research conducted over the years into predictive factors for AMI have shown that age and gender are two of the main predictors [7][8][9][10]. In their study into demographic risk factors related to the occurrence of myocardial infarction, Duan et al [7] showed that myocardial infarction is more prevalent among men than women, and that this risk increases considerably above the age of 50.…”

“…The odds ratios (OR) were calculated for the following, which are also considered to be AMI predictors: GCS 9-12 points OR=3.442 (CI 95%) and swelling OR=3.572 (CI 95%). Kiani et al [10] analyzed risk factors for patients with myocardial infarction treated in hospital. They demonstrated a statistically significant dependency for sinus rhythm, atrial fibrillation, ventricular tachycardia atrioventricular blocks.…”

Association between PM2.5 and risk of hospitalization for myocardial infarction: a systematic review and a meta-analysis

“…In recent years, the prevalence of MI has been increased in both developed and developing countries [14,15]. Research evidences indicate that such risk factors as age, sex, and family history cannot be modulated, but some of the risk factors such as ambient air pollution and unhealthy life style are to a great extent preventable [16][17][18]. Considering the fact that the age for onset of the first MI has been decreasing and that MI is multifactorial in nature, its fundamental function remains unknown [19].…”

Cannabis Use Is an Independent Predictor for Acute Myocardial Infarction Related Hospitalization in Younger Population

“…The demographic characteristics examined in the study population included age group (15e18 years and 19e22 years), gender (male or female), and race (white, Black, Hispanic, Asian, Native American, and other). Based on the current literature [22,23], we identified suspected risk factors for AMI and comorbid substance use as well as psychiatric disorders using ICD-9-CM diagnosis codes and CCS codes, respectively.…”