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Introduction Myocardial strain quantification by speckle-tracking of the right ventricle (RV) and left atrium (LA) can be performed by manual or automatic methods. Purpose The objective of our study is to evaluate the degree of correlation between manual measurement method and automatic software used in our imaging laboratory, in a population of healthy individuals and patients with cardiac transthyretin amyloidosis (ATTR). Methods Fifty-seven individuals were included, 30 patients with ATTR and 27 healthy volunteers, who underwent a transthoracic echocardiogram (TTE) from January to December 2019. Classic echocardiographic parameters and myocardial deformation were obtained according to the ASE/ EACVI guidelines. Global and free wall longitudinal strain of the RV (RVGLS, RVFWLS) and LA global strain (LAGS) analysis were obtained using speckle-tracking with two different software: QLAB Philips 10.7 and AutoSTRAIN Tomtec. Measurements analysis was performed by two experienced echocardiographers. Correlation and reproducibility analysis was performed using Pearson correlation coefficient (PCC) and intraclass correlation coefficient (ICC), respectively. Results Seventy-two percent were male and average age was 63±20 years. Linear correlation of RVGLS, RVFWLS and LAGS measurements with both methods reached statistical significance (table). This correlation was stronger and more reliable in the case of the LAGS. The attached figure shows the correlation between the different software in both groups. Conclusions AutoSTRAIN Tomtec automatic measurement method had higher reliability and correlation comparing to manual measurements performed by QLAB 10.7, especially in LA measurements. The obtained results, the application speed and the less operator's dependence of this automatic software support its routine use for RV and LA strain quantification. Funding Acknowledgement Type of funding sources: None. Correlation and reproducibility resultsLinear regression lines

Funding Acknowledgements Type of funding sources: None. BACKGROUND Adequate measurement of the QT interval is of paramount importance in order to identify patients at higher risk for ventricular arrhythmias. Previous studies have described different methods to estimate baseline QT in patients with left bundle branch block (LBBB). However, the evidence regarding the assessment of QT interval in the setting of right bundle branch block (RBBB) is scarce. PURPOSE We aimed to analyze the feasibility and accuracy of the different formulas described for LBBB in the estimation of the QT interval in RBBB. METHODS We enrolled patients who underwent left sided electrophysiologic procedures. All patients were in sinus rhythm and had narrow QRS. Pacing was performed from the left atrial appendage for baseline measurements, and from the left aspect of the interventricular septum (selective capture of the left bundle was attempted) to measure RBBB QT and QRS. Pacing cycle length was 800 ms or slightly below patients´ intrinsic rhythm at both locations. Measurements were performed manually (using digital calipers) according to current recommendations and corrected using Bazett. Validated formulas for LBBB QT considered are described in table 1. RESULTS 50 patients (42 cryoballoon pulmonary veins isolation (PVI), 4 radiofrequency PVI, 4 concealed left accessory pathways). 70% were male. Mean age was 62 ± 11 years old. Left ventricle ejection fraction was 58 ± 10%. 66% and 60% of the patients were taking betablockers and antiarrhythmic drugs, respectively. Mean pacing cycle length was 707 ± 99 ms. Baseline measurements: QRS 95 ± 10, QT 391 ± 36, QTc 467 ± 39 ms. RBBB measurements: QRS 165 ± 21, QT 448 ± 46, QTc 531 ± 52 ms. Correlations between baseline and estimated QTc were good for all the formulas (table 1). Reliability analysis showed that both Yankelson and Wang methods had the highest intraclass correlation coefficients (ICC) when trying to estimate baseline QTc. CONCLUSIONS Previously described formulas for LBBB exhibit marked differences regarding reliability in the estimation of QTc interval in the setting of RBBB. According to our results, Yankelson’s method shows the most consistent agreement when estimating baseline QTc interval in patients with RBBB. Table 1.LBBB METHODFormula to estimate baseline QTcPearson’s R correlation coefficientCI (95%)Intraclass correlation coefficientCI (95%)YankelsonQTc - QRS + 95 (m) or 88 (f)0.805(0.632-0.977)0.882(0.788-0.934)Bogossian**QT - (QRS/2)0.813(0.644-0.982)0.756(-0.127-0.919)Wang**QT - (0.86*QRS - 71)0.801(0.627-0.974)0.834(0.465-0.930)Tang-Rabkin0.945*QTcRabkin - 260.722(0.521-0.923)0.711(0.019-0.885)RautaharjuQT - 155*(60/heart rate - 1) - 0.93*(QRS - 139) - 22 (m) or - 34 (f)0.780(0.599-0.961)0.105(-0.017-0.381)**Bogossian and Wang required additional HR correction (Bazett). Abstract Figure 1. Bland-Altman

Introduction Pulmonary hypertension (PH) is defined as mean pulmonary arterial pressure (mPAP) ≥25 mmHg at rest, measured by right heart catheterization (RHC). Purpose To describe classical and myocardial deformation echocardiographic parameters in patients with established PH and to identify prognostic variables Methods We prospectively enrolled 76 patients with mPAP ≥25 mmHg undergoing RHC between 2017 and 2018. All subjects underwent transthoracic echocardiography (TTE) according to the latest ASE/EACVI guidelines the same day of the RHC. Strain analysis was carried out by speckle-tracking echocardiography (QLAB 10.7, Philips). Clinical events during the follow-up were: acute heart failure hospitalization, cardiac transplant and all-cause mortality. Results Mean age was 59±12, 43.4% were women and 49 patients (64.5%) belonged to group 2 of PH. The median follow-up was 288 (ICR 92–534) days. Total number of events was 42 (55.3%, 9 deaths). Variables associated to events are shown in Table 1. All classic LV and RV systolic function and strain parameters were associated with a worse prognosis, being free-wall RV longitudinal strain (RVLS) the only one that remained as a prognostic factor in mutivariate analysis. Other variables associated with a worse prognosis were PCP>15 mmHg and NT-proBNP>1800, the latter being independent predictor of events. The attached figure shows event-free survival curves for the global population divided according to whether or not they belong to group II PH. Conclusions Our data highlight the prognostic value of free-wall RVLS and NT-proBNP in patients with established PH. NT-ProBNP was only useful in group II PH while free-wall RVLS identified patients with a higher risk of events in both groups, mainly in patients with heart disease Free event survival Curves Funding Acknowledgement Type of funding source: None