%0 Journal Article
%T Classification and regression tree analysis in acute coronary syndrome patients
%A Heng-Hsin Tung
%A Chiang-Yi Chen
%A Kuan-Chia Lin
%A Nai-Kuan Chou
%A Jyun-Yi Lee
%A Daniel L. Clinciu
%A Ru-Yu Lien
%J World Journal of Cardiovascular Diseases
%P 177-183
%@ 2164-5337
%D 2012
%I Scientific Research Publishing
%R 10.4236/wjcd.2012.23030
%X 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.
%K CART
%K Stepwise Regression
%K Acute Coronary Syndrome
%K Anxiety
%K Quality of Life
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=21239