Statistical Analysis
Baseline characteristics were presented as mean ±SD for continuous
variables and compared using the Student t -test, or percentages
for categorical variables differences compared using the chi-square
test. A p-value < 0.05 was defined as statistically
significant. Univariate and multivariate analysis based on the logistic
regression model were performed to determine the TTE parameters to
estimate the elevated LV filling pressure. Only variables with p
value< 0.05 in univariate analysis were entered into
multivariate analysis. Correlation between LV GLS and diastolic
parameters were analyzed using the Pearson correlation method.
Correlation of invasive LV filling pressure with LV GLS and diastolic
parameters were also analyzed using the Pearson correlation method.
Sensitivity, specificity, positive predictive value, and negative
predictive value of diastolic parameters and LV GLS were analyzed using
the Receiver operating characteristic (ROC) analysis based on the
Logistic regression method. LV GLS cut-off value was determined by ROC
analysis. All data were analyzed using JMP version 14.0 (SAS Institute
Inc., Cary, North Carolina)
Inter-observer and intra-observer variability . Images from 10
patients were randomly selected, and a second independent blinded
observer measured their images to assesses the inter-observer
variability. The first observer who measured all patients’ views
remeasured the same randomly selected 10 patients’ views at least 6
weeks apart from the first measurement. Inter-observer and
intra-observer variability were assessed using the Intra Class
Correlation Coefficient (ICC) method.