On the development of a systemic (biopsychosocial) prediction model for cardiovascular disease. Part II

The authors have attempted to design and verify a model of comprehensive (medical, social and psychological) prognosis in cardiovascular disease, which would cover aspects of patients’ illness, treatment and life functioning. A multidisciplinary set of methods was used to realise the aim. The study included 437 patients suffering from coronary heart disease or chronic heart failure, both of ischaemic and non-ischaemic etiology, who were referred for cardiovascular surgery, and who had undergone surgical intervention. Part II of the article presents the results of the 3 final stages of the study. These are the following: 5) The studied indicators were divided into the following subgroups: “Current state factors” (reflecting the patients’ current psychological state, characterising their cognitive and emotional-affective spheres) and “Baseline factors” (reflecting relatively stable characteristics of the disease, socio-behavioural and personal features of the patients). 6) A new factor analysis was performed, resulting in 11 secondary factors: 5 in the group of “Current state factors” (“Psychological well-being”, “Quality of life in the face of cardiac disease”, “Reduced non-verbal cognitive functions due to anxiety”, “Positive mood and cognitive state”, “State of mnestic function”) and 6 in the group of “Baseline factors” (“Non-constructive behaviour in the face of disease”, “Occupational motives and severity of cardiovascular disease”, “Psychosocial risk factors for coronary heart disease”, “Patient motivation, tension and severity of chronic heart failure”, “Social support and resilience”, “Adherent behaviour and rational thinking”). 7) We used mathematical modelling and a neural network to determine the prognostic value of the above factors and to construct a systematic prediction model that will be capable of predicting the value of all “Current state factors” at any given time (days after surgery) with an accuracy of up to 80%. In the future, we plan to design a model for the “Baseline factors”. The identification of prognostically relevant patients’ characteristics at the stage of preparation for cardiac surgery can help to optimise psychological help for the patient during this time and individualise the postoperative rehabilitation programme.