Why the study?
Because pulmonary artery diastolic pressure correlates closely with pulmonary wedge pressure, researchers sought to evaluate whether an algorithm based on Doppler-estimated pulmonary artery diastolic pressure could estimate increased pulmonary wedge pressure in cardiac patients regardless of left ventricular ejection fraction.
Does an algorithm based on noninvasively estimated pulmonary artery diastolic pressure accurately predict increased pulmonary wedge pressure in cardiac patients?
Does an algorithm based on noninvasively estimated pulmonary artery diastolic pressure accurately predict increased pulmonary wedge pressure in cardiac patients?
An algorithm based on noninvasively estimated pulmonary artery diastolic pressure provides higher accuracy for predicting increased pulmonary wedge pressure than current ASE-EACVI recommendations.
Supports noninvasive PAWP estimation via PRG algorithm in cardiac patients; hypothesis-generating, requires prospective validation before practice change.
AIM: Pulmonary artery diastolic pressure (PADP) correlates closely with pulmonary wedge pressure (PAWP); therefore, we sought to evaluate whether an algorithm based on PADP assessment by the Doppler pulmonary regurgitation (PR) end-diastolic gradient (PRG) may aid in estimating increased PAWP in cardiac patients with reduced or preserved left ventricular (LV) ejection fraction (EF). METHODS AND RESULTS: Right heart catheterization, with estimation of PAWP, right atrial pressure (RAP), PADP, and Doppler echocardiography, was carried out in 183 patients with coronary artery disease (n = 63), dilated cardiomyopathy (n = 52), or aortic stenosis (n = 68). One-hundred and seventeen patients had LV EF <50%. We measured the pressure gradients across the tricuspid and pulmonary valves from tricuspid regurgitation (TRV) and PR velocities. Doppler-estimated PADP (e-PADP) was obtained by adding the estimated RAP to PRG. An algorithm based on e-PADP to predict PAWP, that included TRV, left atrial volume index, and mitral E/A, was developed and validated in derivation (n = 90) and validation (n = 93) subgroups. Both invasive PADP (r = .92, P < .001) and e-PADP (r = .72, P < .001) correlated closely with PAWP, and e-PADP predicted PAWP (AUC: 0.85, CI: 0.79-0.91) with a 94% positive predictive value (PPV) and a 55% negative predictive value (NPV), after exclusion of five patients with precapillary pulmonary hypertension. The e-PADP-based algorithm predicted PAWP with higher accuracy (PPV = 94%; NPV = 67%; accuracy = 85%; kappa: 0.65, P < .001) than the ASE-EACVI 2016 recommendations (PPV = 97%; NPV = 47%; accuracy = 68% undetermined = 18.9%; kappa: 0.15, P < .001). CONCLUSIONS: An algorithm based on noninvasively e-PADP can accurately predict increased PAWP in patients with cardiac disease and reduced or preserved LV EF.
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Barbier et al. (2020) studied this question.
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