Algorithm of anxiodepressive disorders detection in patients with coronary heart disease in general clinical practice

Abstract

Aim. To estimate a diagnostic algorithm for anxiodepressive disorders (ADD) in coronary patients in general therapeutic practice. Material and methods. A total of 163 coronary patients were examined using Seattle, Moriski and Green, Hospital questionnaires for anxiety and depression. Patients with clinical and subclinical anxiety and/or depression by Hospital testing responded to Hamilton anxiety and depression questionnaire. An analysis of clinical, anamnestic and socioeconomic parameters was made to create a multifactor model for ADD detection in coronary patients basing on the method of multiple logistic regression. Results. A model of ADD dependence Z = -3.446 [presence or absence of anxiety and/or depression in the past]-2.451[presence or absence of stress for a year] - 2.452 [drinking alcohol or rejection of alcohol] + 0.071 [the disease perception in percent from Seattle angina questionnaire]. In certain combination of responses (presence or absence of parameters) and digital result in 7 combinations the patients can be diagnosed to have ADD. Conclusion. The diagnostic algorithm proposed helps ADD detection in coronary patients in general therapeutic practice without participation of psychotherapists and medical psychologists.

Keywords

• coronary heart disease
• depression
• anxiety
• algorithm
• diagnosis