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Annals of Saudi Medicine. 2005; 25 (2): 134-139
in English | IMEMR | ID: emr-69792

ABSTRACT

The importance of pathophysiological mechanisms involved in onset of acute myocardial infarction [AMI] differs with age, gender, and risk profiles. Diversity in the triggering of cardiovascular events has been observed, particularly between men and women. Therefore, we investigated the relationship between age, gender, and risk factors and location of AMI and the presence of Q waves in ECG. Data was obtained from a chart review of 2958 patients with first AMI: 770 [26%] patients with non-Q-wave AMI and 2188 [74%] patients with Q-wave AMI. Four clinical groups were formed by predetermined criteria [anterior Q-wave, anterior non-Qwave, inferior Q-wave, inferior non-Q-wave]. A logistic regression was performed to assess independent predictors of AMI type and site. Key findings were: 1] inferior non-Q-wave AMI was more frequent in young women [P<0.001]; 2] inferior Q-wave AMI was more common in young men [P<0.001]; 3] anterior non- Q-wave AMI was more common in older men [P<0.001]. Multivariate analysis revealed that independent predictors of anterior non-Q-wave AMI were age over 65 [P=0.002], male gender [P=0.04] and hypercholesterolemia [P=0.0003], and that predictors of inferior Q-wave AMI were male gender [P<0.0001], smoking [P=0.04] and diabetes [P=0.049]. In the gender-subgroup analyses, age <45 years [P=0.04], hypecholesterolemia [P=0.02] and smoking [P=0.01] were independent predictors of inferior Q-wave AMI whereas age >65 years [P<0.0001] and smoking [P=0.0003] were predictors of anterior non-Q-wave AMI in men. In women, age <45 years [P<0.0001] and smoking [P=0.02] were independent predictors of non-Q-wave AMI and hypercholesterolemia [P=0.02] was a predictor of inferior Q-wave AMI. The link between particular types and the site of AMI and age, gender and risk factors suggest that the importance of pathophysiological mechanisms for onset of AMI differs according to sex and age subgroup


Subject(s)
Humans , Male , Female , Risk Factors , Coronary Angiography , Logistic Models
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