Predictive factors of cardiovascular changes depending on the type and intensity of physical activity in professional athletes

Abstract

Aim. To determine the early predictive factors of cardiovascular changes in professional athletes, depending on the type and intensity of physical activity.Material and methods. A total of 136 male athletes were examined. Of these, 116 were professional athletes (age, 22,07±4,1 years) as follows: freestyle wrestling, judo (n=30), cross-country skiing, biathlon (n=27), powerlifting (n=33), volleyball (n=26). Control group included 20 athletes (age, 17,95±1,5 years) with a history of training less than 3 years. All participants underwent electrocardiography (ECG), echocardiography, cycle ergometry (CE) with assessment of physical performance at a heart rate of 170 bpm (PWC170) and maximum oxygen consumption (MOC). When creating predictive models of early cardiovascular changes, we used logistic regression, stepwise regression and Wald statistics. Differences were considered significant at p<0,05.Results. Predictive models of logistic regression using ROC analysis showed high sensitivity and specificity, a high percentage of correct predictions using data from echocardiography — 86,8%, CE — 80,9%, ECG and other indicators — 83,1%. A stepwise algorithm was used to select prognostic factors determining early cardiovascular changes in young athletes, depending on the stage of sports training, the intensity and type of dynamic and/or static exercise: left ventricular posterior wall thickness (p=0,008), left ventricular mass (p=0,001), stroke volume (p=0,002), end-systolic volume (p=0,001), PWC170 (p=0,025), MOC (p=0,003), recovery time of heart rate (HR) (p=0,029) and blood pressure (p=0,032) after submaximal exercise on a cycle ergometer, body mass index (p=0,029), heart rate (p=0,034), office systolic blood pressure (p=0,009), intraventricular (bundle) block (p=0,046), left ventricular repolarization abnormalities (p=0,010), mild cardiac connective tissue anomalies (p=0,035).Conclusion. The early prognostic factors established by the logistic regression affect the characteristics and risk of cardiovascular changes in each group of young athletes. This demonstrates the need to develop individual medical support programs, further monitoring, evaluation, correction and prevention of identified disorders, taking into account the type of sports, intensity and exercise.