STATISTICAL ANALYSIS
Statistical analysis was done with SPSS software 25.0 (IBM Corp, Armonk,
NY, USA). Continuous variables have been presented as mean ± standard
deviation. Categorical variables have been presented as number and
percentages. Difference between continuous variables have been tested
using the unpaired student ‘t’ test, and between categorical variables
by using the Chi-square test and Fisher exact test. Statistical
significance was set at a probability level of less than 0.05.
Univariable followed by multivariable logistic regression analysis was
done to assess the independent predictors of inactive LAA in patients of
severe MS in sinus rhythm. Multivariable binary logistic regression
analysis was performed on variables which were significant on
univariable analysis (p<0.2) to identify the independent
predictors of inactive LAA.
Univariate followed by multivariate logistic regression analysis was
also done to assess the independent predictors of LA/LAA smoke and
thrombus.
Pearson correlation analysis was used to assess the association between
various factors which were independent predictors of LAAI. Receiver
operating characteristic curve (ROC) were constructed to assess the
optimal cut off value of the independent factors to predict inactive
LAA. The Youden index was applied to obtain the optimal cut-off point of
factors. The diagnostic indices- sensitivity, specificity, positive
predictive value, negative predictive value were determined for each
factor at optimal cut-off point.
Inter-observer variability in the measurement of LAAEV was expressed as
mean coefficient of variation ∑ [(observer 1-observer 2)/observer
1]/n and expressed as percentage. Interobserver variability in grading
SEC was determined as number of cases in which a discrepancy of grade
occurred, expressed as percentage of the total group.