Establishment of a predictive model of post-percutaneous coronary intervention depression in patients with coronary heart disease and its effect analysis

Abstract

Objective To screen the risk factors of depression in patients with coronary heart disease(CHD) after percutaneous coronary intervention(PCI), and to construct a predictive model of depression in patients with CHD after PCI and to analyze its diagnostic efficacy. Methods A total of 3 048 patients with CHD who were treated in our hospital from April 2015 to January 2019 were selected as the study subjects. 967 patients with depression after PCI were selected as depression group. 967 patients without depression after PCI were randomly selected as CHD group according to 1:1 ratio. Univariate and multivariate logistic regression analysis were used to analyze the risk factors of depression in patients with CHD after PCI, and to construct a predictive model of depression in patients with CHD after PCI. The ROC curve was used to analyze the diagnostic efficacy of a predictive model of depression in patients with CHD after PCI. Results Of 3 048 patients with CHD, 967 (31.73%) suffered from depression after PCI. There were significant differences in age, sex, type D personality, smoking history, NYHA classification, number of stents implanted, solitary living, emergency PCI, Gensini score and education level between the two groups (P<0.05). Logistic regression analysis showed that age, type D personality, NYHA grade, solitude and education were risk factors for depression after PCI. The area under ROC curve of depression model after PCI in CHD patients was 0.961 (95% CI: 0.910-0.987), the sensitivity and specificity were 96.00% and 90.82% respectively. Conclusion The model constructed in this study can predict the risk of depression in patients with CHD after PCI and is more effective. Key words: Coronary heart disease; Percutaneous coronary intervention; Depression; Risk factors; Diagnostic efficacy