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Classification and regression tree analysis in acute coronary syndrome patients

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DOI: 10.4236/wjcd.2012.23030    3,833 Downloads   7,311 Views   Citations


Objectives: The objectives of this study are to use CART (Classification and regression tree) and step-wise regression to 1) define the predictors of quality of life in ACS (acute coronary syndrome) patients, using demographics, ACS symptoms, and anxiety as independent variables; and 2) discuss and compare the results of these two statistical approaches. Back- ground: In outcome studies of ACS, CART is a good alternative approach to linear regression; however, CART is rarely used. Methods: A descriptive survey design was used with 100 samples recruited. Result and Conclusions: Anxiety is the most significant predictor and also a stronger predictor than symptoms of ACS for the quality of life. The anxiety level patients experienced at the time heart attack occurred can be used to predict quality of life a month later. Furthermore, the majority of ACS patients experienced a moderate to high level of anxiety during a heart attack.

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The authors declare no conflicts of interest.

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Tung, H. , Chen, C. , Lin, K. , Chou, N. , Lee, J. , Clinciu, D. and Lien, R. (2012) Classification and regression tree analysis in acute coronary syndrome patients. World Journal of Cardiovascular Diseases, 2, 177-183. doi: 10.4236/wjcd.2012.23030.


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