Detailed Instructions: Given a passage classify if the passage has a definite objective/aim/goal or not. Output '1' if the passage has a defininte objective/aim/goal and output '0' if the passage does not have a definite objective/aim/goal.
Q: This study assesses the relationship between septal curvature and mean pulmonary artery pressure and indexed pulmonary vascular resistance in children with pulmonary hypertension. We hypothesized that septal curvature could be used to estimate right ventricular afterload and track acute changes in pulmonary hemodynamics.', 'Fifty patients with a median age of 6.7 years (range, 0.45-16.5 years) underwent combined cardiac catheterization and cardiovascular magnetic resonance. The majority had idiopathic pulmonary arterial hypertension (n=30); the remaining patients had pulmonary hypertension associated with repaired congenital heart disease (n=17) or lung disease (n=3). Mean pulmonary artery pressure and pulmonary vascular resistance were acquired at baseline and during vasodilation. Septal curvature was measured using real-time cardiovascular magnetic resonance. There was a strong correlation between mean pulmonary artery pressure and SCmin at baseline and during vasodilator testing (r=-0.81 and -0.85, respectively; P<0.01). A strong linear relationship also existed between pulmonary vascular resistance and minimum septal curvature indexed to cardiac output both at baseline and during vasodilator testing (r=-0.88 and -0.87, respectively; P<0.01). Change in septal curvature metrics moderately correlated with absolute change in mean pulmonary artery pressure and pulmonary vascular resistance, respectively (r=0.58 and -0.74; P<0.01). Septal curvature metrics were able to identify vasoresponders with a sensitivity of 83% (95% confidence interval, 0.36-0.99) and a specificity of 91% (95% confidence interval, 0.77-0.97), using the Sitbon criteria. Idiopathic pulmonary arterial hypertension subgroup analysis revealed 3 responders with SCmin values of 0.523, 0.551, and 0.568. If the middle value of 0.551 is taken as a cutoff, the approximate sensitivity would be 67% and the specificity would be 93%.
A:
0