Smoking remains one of the most aggressive risk factors for cardiovascular disease (CVD), as smokers have been shown to have twice the risk of cardiovascular (CVD) mortality than non-smokers. Accordingly, quitting smoking in people even in the elderly is useful. Data from a metaanalysis showed that the increased CV risk in patients who got rid of this habit decreased over time. Another study found a directly proportional relationship between smoking and CVD: the more cigarettes smoked and the longer the history of smoking, the higher the risk of myocardial infarction (MI).
The authors of a meta-analysis of 12 cohort studies suggested that smoking cessation is closely related to a reduction in overall mortality. It was found that in patients who did not give up smoking after an MI, mortality increased significantly and amounted to 20%. The scientific results of another retrospective American study Partners YOUNGMI Registry showed that smoking cessation in young patients (< 50 years old) who underwent MI was reliably walking, therapeutic gymnastics (ThG), laser therapy for the associated with a decrease in total mortality and mortality from CV diseases by approximately 70-80%. And this, in turn, confisms the critical importance of smoking cessation in young patients after MI. Another convincing result was obtained in a 15-year follow-up of patients who underwent coronary bypass surgery. A study found that patients who smoked within 1 year after surgery had a risk of subsequent MI and reoperation more than twice as high as patients who quit smoking after surgery. Patients who continued to smoke 5 years after surgery had an even higher risk of MI and reoperation compared with patients who quit smoking after surgery and patients who had never smoked. It was also found that the risk of MI was similar among non-smokers and those who managed to quit smoking after surgery. In a meta-analysis of 20 studies, it was found that the effect of smoking cessation was prognostically more favorable than lowering cholesterol, in which the latter sometimes the greatest attention is focused.
Despite the fact that smoking necessity cessation in the process of cardiorehabilitation (CR) has been proven, little is known among the participants of CR about the factors associated with the patients’ refusal to quit smoking. That is why researchers have begun to study predictors of smoking cessation in order to improve and increase the effectiveness of cardiorehabilitation programs. The results of many studies have established variables that influence the process of quitting smoking, namely: the degree of tobacco dependence (number of cigarettes smoked per day, smoking history), number of previous attempts to quit smoking, gender, age, marital status and level of depression. However, the obtained scientific results of such studies are contradictory and require additional study to accurately determine the factors that are associated with the successful cessation of smoking by smoking patients after an acute coronary event at the stage of active completion of CR programs.
AIM
To establish socio-psychological and clinical predictors of smoking cessation at the stage of health-resort rehabilitation in patients who have recently suffered an acute coronary event.
MATERIALS AND METHODS
68 patients aged 42-68 years (average age 56.70±6.1 years) who underwent a cardiorehabilitation program in the rehabilitation department after heart diseases of the „Morshinkurort” health-resort complex after a recent heart attack (no more than 28 days ago) were examined. Depending on the smoking habit, all patients were divided into two groups. T he first (I) group included smoking patients who gave up smoking during the CR process (n=38, average age 57.10±6.73 years), the second (II) group – smokers who continued to smoke during the health-resort treatment (n=30, average age 56.58±5.74 years). The measures of the rehabilitation program were carried out according to the recommendations of the ESC working group on cardiorehabilitation and physical training. The CR program included dosed therapeutic walking, therapeutic gymnastics (ThG), laser therapy for the cubital vein, and optimal medical therapy (OMT). In order to quit smoking, all smoking patients were given individual counseling using the “5As” strategy, unmotivated smokers - the “5R” strategy in accordance with Order 746 dated 09/26/2012 “On the approval of Methodological recommendations for medical workers of health care institutions on providing medical and preventive care for persons who want to get rid of tobacco addiction”. The length of stay of all cardiac rehabilitation patients in the rehabilitation department was 24 days.
All CR participants were interviewed using the Fagerstman test to assess the degree of nicotine addiction. The smoking index (SI) was calculated according to the formula: (SI)=Ch*C/20, where Ch is the number of cigarettes smoked (per day), C is the smoking experience (years). All patients were also subjected to anthropometric measurements of body weight (m) using medical scales and height (h) to calculate BMI according to the formula: BMI = m/h2, where m is body weight (kg), h is height (m). The level of depression and anxiety was assessed using the HADS scale (The Hospital Anxiety and Depression Scale). All rehabilitation patients underwent biochemical blood analysis, echocardiography and physical stress tests at the start of the cardiorehabilitation process.
We also used the primary data of rehabilitation patients to conduct the study: age, sex, presence of concomitant diseases, cardiovascular risk and marital status. In the course of the study, all of the above indicators were used to synthesize a mathematical model for predicting the outcome of smoking cessation in patients with ACS using the binary logistic regression method. The conducted analysis made it possible to establish the factors affecting the outcome of smoking cessation and to calculate the probability of this event depending on the values of independent predictors.
RESULTS
During our calculations of binary logistic regression using the Wald exclusion method, 5 key parameters were determined that were statistically significant in terms of the influence on the process of smoking cessation in rehabilitation patients. T he coefficients of the selected binary logistic regression model are presented in the Table 1.
The logistic regression model we created was statistically significant (G = 54.036 at p (χ2) < 0.00000) and the obtained Hosmer-Lemeshov (HL) value, which was 9.264 at a significance level of p>0.05 (p = 0.320), indicated about the high consistency of our model. In the logistic model we created, the influence of indicators (SI, HADS-T, BMI, marital status and the presence of concomitant diseases) on smoking cessation was 58.79% (Table 2).