Correlation of strain parameters with probability of pulmonary hypertension
We performed a natural logarithmic transformation in variables with non-parametric distribution. Afterward, we assessed the correlation of both RV-FWS and RA-GS with sPAP using Pearson correlation analysis to obtain the correlation coefficient using our transformed variables. To evaluate the prediction capacity of RV-FWS with sPAP, we performed polynomic adjusted linear regression analysis to assess the association between both parameters. The R2 was reported to express the variability explained by both variables. As a second step, we adjusted these models for age, sex, and body surface area as these variables could modify the relationship of RV-FWS and sPAP. As a secondary analysis, we evaluated the association of sPAP with the right heart chamber fibrosis of our second cohort sample, using the methods previously described.