Classification and regression tree analysis in acute coronary syndrome patients

Heng-Hsin Tung^1,2*, Chiang-Yi Chen³, Kuan-Chia Lin¹, Nai-Kuan Chou³, Jyun-Yi Lee⁴, Daniel L. Clinciu^5,6, Ru-Yu Lien^1,7

¹National Taipei University of Nursing and Health Science, Taipei City.
²Tungs’ Taichung MetroHabor Hospital, Taichung.
³National Taiwan University Hospital, Taipei City.
⁴Cardiovascular Department, Mackay Memorial Hospital, Taipei City.
⁵Feng Chia University, Taichung.
⁶Taipei Medical University, Taipei City.
⁷Nursing Department, Taipei Veterans General Hospital, Taipei City.

DOI: 10.4236/wjcd.2012.23030                

Abstract

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.

Keywords

CART; Stepwise Regression; Acute Coronary Syndrome; Anxiety; Quality of Life

Conflicts of Interest

The authors declare no conflicts of interest.

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