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.