Abstract

Aim: To compare the results of distributing left ventricular (LV) remodeling patterns according to two classifications and identify their advantages and disadvantages. Materials and methods. The study involved 2019 patients, aged from 18 to 94 years with a mean of 57.6 ± 16.4 years, 51 % males, apparently healthy and with cardiovascular and respiratory system pathology. Echocardiography was performed using an Esaote MyLab Seven device (Italy) according to generally accepted standards. The distribution of patients according to four classic LV remodeling patterns and according to the classification proposed by W. Gaasch and M. Zile was studied. Statistical analysis was performed using Statistica for Windows 13.0 (StatSoft Inc., USA; license No. JPZ804I382130ARCN10-J). Qualitative variables were given as absolute and relative frequency (n (%)). Results. The distribution of patients according to 4 classic LV remodeling patterns was as follows: 53.0 % had normal LV geometry; 10.2 % – concentric remodeling; 15.6 % – concentric hypertrophy; 21.2 % – eccentric hypertrophy. At the same time, in the group of normal LV geometry, 25.2 % of people had LV dilatation. When distributing the patients by remodeling patterns according to the W. Gaasch and M. Zile classification, the following data were obtained: 26.9 % of people had normal LV geometry, concentric remodeling – 10.2 %, concentric hypertrophy – 12.4 %, mixed hypertrophy – 3.1 %, physiological and dilated hypertrophy – 11.8 %, eccentric hypertrophy – 5.5 %, eccentric remodeling – 11.4 %. In addition, 3 more groups of patients were formed, who did not have a terminological definition based on the W. Gaasch and M. Zile classification and, in total, accounted for 18.6 % of the examined. Conclusions. The missing options of dilated left ventricle should be recognized as a limitation of the classic classifications of left ventricular remodeling patterns. The imposition of additional criteria covering the cavity dilatation in determining the left ventricular remodeling patterns improves the assessment of the patient’s prognosis and contributes to a more individual selection of pathogenetic therapy.

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