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.