Background: Clopidogrel is an antiplatelet drug that is widely prescribed for cardiovascular disease. In cardiac surgery, it is used in patients after coronary artery bypass grafting (CABG) to prevent coagulation disorders. The irrational use of this drug can lead to bleeding and require surgical exploration along with increased therapeutic cost. Therefore, it is essential to study the pattern of clopidogrel use in hospitals. Methods: This study was conducted for a 6-month period to evaluate clopidogrel adherence to American Heart Association/American College of Cardiology (AHA / ACC) Guidelines in patients after coronary artery bypass grafting (CABG) surgery. Patients’ data were recorded in the pre-designed questionnaire, which included demographic data, past medical history, drug history along with the indications of clopidogrel use. Data analysis was performed by SPSS 16 software. Results: A total of 120 patients with a mean age of 61.3 ± 8.9 years old were recruited in to this study. Male to female ratio was 3 times. The main risk factors in patients with ischemic heart disease were male gender (74.2%), hypertension (80%), and smoking (47.5%). In addition to clopidogrel, most of the patients received aspirin (95.8%), followed by heparin (31.7%), and warfarin (5%) or enoxaparin (2.5%). The clopidogrel indications were non ST-elevation myocardial infarction / unstable angina (33.3%), acute ST-elevation myocardial infarction (20.8%), recent myocardial infarction or stroke (3.3%), and CABG off-pump (30%). In 70.8% of cases, the administration of clopidogrel was consistent with AHA / ACC standard guidelines and most of the irrational cases belonged to the usage of the drug after on-pump CABG surgery. Conclusion: The results showed that the rates of adherence to clopidogrel use with the AHA/ACC guidelines for patients who underwent CABG surgery was relatively good, but required further improvement.
Predicting Likelihood for Coronary Artery Bypass Grafting After Non–ST-Elevation Myocardial Infarction: Finding the Best Prediction Model
