Optimal combination of right ventricular functional parameters using echocardiography in pulmonary arterial hypertension

Abstract Aims Novel echocardiographic parameters of right ventricular (RV) function, including speckle‐tracking‐derived, three‐dimensional, and RV–pulmonary artery coupling parameters, have emerged for the evaluation of pulmonary arterial hypertension (PAH). The relative role of these parameters in the risk stratification of PAH patients is unclear. We compared the performance of multiple RV parameters and sought to establish an optimal model for identifying the risk profile of patients with PAH. Methods and results Comprehensive risk assessments were performed for 70 patients with PAH. The risk profile of every patient was determined based on the guideline recommendations. Conventional parameters, including fractional area change (FAC) and tricuspid annular plane systolic excursion (TAPSE), novel speckle‐tracking‐derived RV longitudinal strain (RVLS), and three‐dimensional RV ejection fraction (3D‐RVEF), were used to evaluate RV function. Pressure–strain loops were measured for the assessment of RV myocardial work, including RV global wasted work (RVGWW). RV–pulmonary artery coupling was assessed by indexing RV parameters to the estimated pulmonary artery systolic pressure (PASP). The median age was 34 (30–43) years, and 62 (88.6%) patients were female. Forty‐five patients were classified into the low‐risk group, while 25 patients were classified into the intermediate–high‐risk group. Most RV parameters could be used to determine the risk profile and exhibited significantly improved diagnostic performance after indexing to PASP (including FAC/PASP, TAPSE/PASP, and 3D‐RVEF/PASP). RVLS/PASP showed the best performance, with an area under the curve of 0.895. In multivariate analysis (Model 1), only RVGWW (>90.5 mmHg%), RVLS (> −16.7%), and TAPSE ( −0.275 [odds ratio (OR) 20.63, 95% confidence interval (CI) 4.62–92.11, P 90.5 mmHg% (OR 6.17, 95% CI 1.37–27.76, P = 0.018) independently identified a higher risk profile. The addition of RVGWW to two models determined incremental value in identification (continuous net reclassification improvement 1.058, 95% CI 0.639–1.477, P