ABC | Volume 114, Nº1, January 2019

Original Article Otto et al. Aortic prosthesis mismatch in public health system Arq Bras Cardiol. 2020; 114(1):12-22 Table 7 – Formula for individual risk and coefficient of each variable for severe mismatch probability calculation (Definition #2) Parameter Estimate Intercept -5,54 Age < 60 1,75 Male gender 0,79 LVOT Diameter ≤ 2.1 2,25 BMI ≥ 25 Kg/m 2 1,12 Etiology of Aortic Valve Disease Congenital (bicuspid) 0,41 Etiology of Aortic Valve Disease Degenerative 1,10 Etiology of Aortic Valve Disease Rheumatic 2,15 Probability of severe PPM = 1 1 + e (–5.54+1.75age+0.79male+2.25LVOTdiam+1.12BMI+0.41EtiolCong+1.1Etioldeg+2.15EtiolRheum) Legend: PPM patient prosthesis mismatch; BMI: Body Mass Index; LVOT Diam: Left Ventricle Outflow Tract Diameter; Etiol Cong: Etiology Congenital; Etiol Deg: etiology degenerative; Etiol Rheum: Etiology Rheumatic. Observation:Todetermine theprobabilitiesbasedon theaboveequation,onemustuse thedesignmatrixonTable6, if thevariablepresent.Forexample: ifapatient is<60years old, one must replace the variable age by the value 1 and multiply it by the value of its coefficient. If it is older than or equal to 60, one should replace the variable age by zero. Area Under the Curve Area Std. Error a Asymptotic Sig. b Asymptotic 95% Confidence Interval Lower Bound Upper Bound 0.824 0.037 0.000 0.751 0.897 ROC Curve 1.0 1.0 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 Sensitivity 1 – Specificity 0.82 Figure 1 – ROC curve: accuracy of the multivariable model for prediction of severe PPM (Definition #2:) 20