IJCS | Volume 31, Nº6, November / December 2018

635 Felix et al. RV function by 2D strain in left-sided valve disease Int J Cardiovasc Sci. 2018;31(6)630-642 Original Article The patients were classified into subgroups according to their predominant valve lesion as follows: (1) mitral stenosis (n = 11; 20.8%), (2) mitral regurgitation (n = 21; 39.6%), (3) aortic stenosis (n = 8; 15.1%), (4) aortic regurgitation (n = 9; 17%), and (5) combined lesions (n = 4; 7.5%).We defined combined lesions as the presence of two or more severe mitral and/or aortic valve lesions in the same patient. Of the four patients with combined lesions, two had severemitral stenosis and regurgitation, one had severe aortic stenosis and regurgitation and the other one had severe mitral regurgitation and aortic regurgitation. Table 2 - Two-dimensional, Doppler, 2D strain and three-dimensional parameters of the enrolled subjects Parameters Values (mean ± SD) LA (mm) 48.81 ± 9.96* RV (mm) 17 (16 - 20) ** LV EDD (mm) 57.34 ± 10.24* LV ESD (m) 36.21 ± 8.65* LVEF Teichholz (%) 67.0% (61.5 - 73.0%)** LVEF Simpson (%) 66 (61 - 72%)** RV basal (mm) 37 (31 - 41)** RV mid-cavity (mm) 27 (22 - 34)** RV apical-TV distance (mm) 60 (55 - 69)** Tricuspid Annulus (mm) 30.19 ± 4.32* PASP (mmHg) 40 (30 - 54)** RVFWS (%) -23.81 ± 6.77* RVGS (%) -21.42 ± 4.96* PSV (cm/sec) 11.91 ± 3.73* TAPSE (mm) 20.21 ± 5.92* FAC (%) 44.46 ± 13.3* RVEDF 3DE (ml) 80.4 (64.4 - 114.7)** RVESV 3DE (ml) 34.1 ml (25.6 - 54.1)** RVEF 3DE (%) 60 (42.5 - 63.4)** *Data are mean ± SD. **Data are median with interquartile range. FAC: fractional area change; LA: left atrium; LV EDD: left ventricular end diastolic dimension; LVEF: left ventricular ejection fraction; PASP: pulmonary artery systolic pressure; LV ESV: left ventricular end systolic dimension; PSV: peak systolic velocity of tricuspid annulus; RV: right ventricle; RVFWS: RV free wall longitudinal 2D strain; RVGS: RV global longitudinal 2D strain; TAPSE: tricuspid annular plane systolic excursion; TDI: tissue Doppler imaging; TV: tricuspid valve. The echocardiographic variableswere compared between these subgroups (ANOVA for multiple comparisons), and we found a significant difference between the groups in all the parameters, except for PSV (Figure 4). Patients with stenotic valve lesions had lower values of PSV compared with patients with regurgitant lesions. Patients with combined lesions had lower values of all conventional RV function parameters compared with the other groups. We observed lower absolute values of RVFWS, RVGS (less deformation) and higher PASP, and lower FAC and RVEF 3D in patients with mitral stenosis and patients with combined lesions. Dividing the patients into two categories according to their RVEF by 3DE, considering patients with RVEF ≥ 44% as preserved function (A), and patients with RVEF < 44% as RV systolic dysfunction (B), we found a total of 14 patients with RV dysfunction (27.4%), with significant difference between the groups for all variables: PSV (p = 0.005), TAPSE (p < 0.001), FAC (p < 0.001), PASP (p < 0.001), RVFWS (p < 0.001), RFGS (p < 0.001) (Figure 5). ROC curve analyses tested the clinical utility of all parameters for the diagnosis of RV dysfunction (determined by RVEF < 44% by 3DE), and established sensitivity (Se), specificity (Sp) and best cut-off values. The parameters with the largest areas under the curve (AUC) were: RVFWS (0.851), RVGS (0.872) and FAC (0.932), with best cut-off values of: -18.6% (Se: 86.5%, Sp: 79.6%), -20.1% (Se: 83.8%, Sp: 85.7%) and 41% (Se: 86,5%, Sp: 92,9%), respectively (Table 3). Intra- and interobserver variability analysis Reproducibility analysis showed excellent accordance between repeated measurements for the RV 2DS parameters by Bland-Altman analysis (Figure 6). Both RVFWS and RVGS showed high intraclass correlation coefficient (range, 0.97 - 0.98) with narrow confidence intervals (Table 4). Discussion There are few studies in literature focusing on RV function in left-sided VHD, most of which had limited number of patients and analyzed only conventional RV function parameters, without using 2DS parameters or 3DE. The great challenge in VHD is to detect early alterations in RV function, when subclinical disease may point to a worse clinical prognosis and contribute