Computational protocol: Diagnostic utility of biomarkers of left ventricular stress in patients with aortic stenosis and preserved left ventricular ejection fraction

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Protocol publication

[…] Categorical variables were reported as the number of observations (N) and the corresponding percentage (%) and analyzed with the χ2 test or χ2 test with Yates’ adjustment.Normality of quantitative variables was tested using the Shapiro-Wilk test for normality. Because of the lack of normality for the majority of variables, they were presented as medians with interquartile range. Patients were divided into two subgroups: severe AS and non-severe AS. Differences between groups were analyzed using Student’s t-test (normal distribution) or Mann-Whitney U-test (not normal distribution).For significant quantitative variables receiver operating characteristic (ROC) curves were drawn and optimal decision thresholds were found using the Youden index. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated. Odds ratios (OR) with 95% confidence interval (CI) were also presented.Significant variables (p < 0.1) were analyzed using stepwise linear regression models. To assess correlations between sST2 and NT-proBNP with echocardiographic parameters of aortic stenosis severity, Spearman correlation coefficients were used. A p-value < 0.05 was considered statistically significant.Statistical calculations were performed with Statistica 10 PL (StatSoft Inc., USA) and SPSS v. 21 (SPSS Inc., USA) and R – project v. 3.0.2 (R Core Team, The R Foundation for Statistical Computing, Vienna, Austria). […]

Pipeline specifications

Software tools Statistica, SPSS
Application Miscellaneous
Organisms Homo sapiens
Diseases Aortic Valve Stenosis, Heart Valve Diseases