Predictive model for quality of life in patients with recurrent coronary artery disease

Abstract

Background: The aims of this study were to construct and verify a model that explains the quality of life in patients with recurrent coronary artery disease. Methods: Participants were 212 patients with recurrent coronary artery disease undergoing percutaneous coronary intervention. Data were collected through structured questionnaires from 21 December 2016–30 April 2017, and were analyzed using SPSS 23.0 and AMOS 23.0. Results: The model’s fit indices were adequate. Type D personality, symptom experience, and resilience had a direct effect on quality of life, while type D personality, cardiac function status, social support, and resilience had an indirect effect on quality of life. Type D personality, cardiac function status, social support, symptom experience, and resilience explained 55% of the total variance in quality of life. Thus, type D personality, cardiac function status, social support, symptom experience, and resilience affected the quality of life in patients with recurrent coronary artery disease. Conclusions: Systematic and integrated intervention programs considering factors related to quality of life may be useful for improving quality of life for patients with recurrent coronary artery disease.