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.