Abstract

BackgroundDespite the importance of CAD for women, there is persistent perception that CAD is a man’s disease. Contributing to this notion is the observation of differences in incidence rates according to age; the incidence of CAD in women is lower than men, but rises steadily after fifth decade. The distribution of CAD risk factors varies between men and women across age ranges and failure to consider these differences may have contributed to the belief that women are at lower risk of CAD compared with men. In addition, women are more likely to have symptoms considered atypical compared with men. There is an urgent need to better understand the presentation of cardiac symptoms in women, in order to facilitate diagnosis and treatment, to initiate aggressive risk factor intervention and to improve the quality of life. MethodsWe studied clinical and angiographic profile of women undergoing coronary angiogram over a period of 6 years at Nanavati Hospital, Mumbai. The objectives were to examine the distribution of risk factor and coronary angiographic patterns of CAD in women. ResultsIt was observed that coronary artery disease is most commonly involving females between the age 60 to 80 years. Raised LDL-C was found to be most common risk factor involved in development of coronary artery disease in females. Most common presentation of CAD in women is unstable angina or non-ST segment elevation MI. Most common coronary angiography finding was single vessel disease. ConclusionThough coronary artery disease is late to present in women it significantly hamper quality of life. The clinical presentation of coronary artery disease in women varies from asymptomatic to severe unstable angina to myocardial infarction. Stress testing and 2D-ECHO helps to some extent for prediction of coronary artery disease but false positive as well as false negative test results are not negligible. Coronary angiography is the conclusive test to determine spectrum and characterization of coronary artery anatomy in women. As this study is based on experience at single center, various biases may be possible. Widespread data collection involving multiple center and multiple operators will be helpful.

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