Left atrial inflow propagation velocity derived by color M-mode Doppler in acute heart failure.
Øyvind JohannessenPeder Langeland MyhreBrian ClaggettMoritz LindnerEldrin F LewisJose RiveroSusan ChengElke PlatzPublished in: The international journal of cardiovascular imaging (2022)
Left atrial (LA) inflow propagation velocity from the pulmonary vein (LAIF-PV) has been proposed as a novel measure of LA reservoir function and is associated with pulmonary capillary wedge pressure in critically ill patients. However, data on LAIF-PV in acute heart failure (AHF) are lacking. We sought to examine the feasibility of measuring LAIF-PV and evaluate clinical and echocardiographic correlates of LAIF-PV in AHF. In a prospective cohort study of adults hospitalized for AHF, we used color M-mode Doppler of the pulmonary veins to obtain LAIF-PV in systole. Among 142 patients with appropriate images and no more than moderate mitral regurgitation, LAIF-PV measures were feasible in 76 patients (54%) aged 71 ± 14 years, including 68% men with left ventricular ejection fraction (LVEF) 38% ± 13. Mean LAIF-PV was 24.2 ± 5.9 cm/s. In multivariable regression analysis adjusted for age, sex, systolic blood pressure, heart rate, body mass index, New York Heart Association class, LA volume and LVEF, the only independent echocardiographic predictors of LAIF-PV were right ventricular (RV) S' [ß 0.46 cm/s per cm/s (95% CI 0.01-0.91), p = 0.045] and tricuspid annular plane systolic excursion (TAPSE) [ß 0.28 cm/s per mm (95% CI 0.02-0.54), p = 0.039]. Notably, LAIF-PV was not significantly correlated with measures of LV function, LA function or E/e'. In conclusion, LAIF-PV was measurable in 54% of patients with AHF, and lower values were associated with measures of impaired RV systolic function but not LV or LA function.
Keyphrases
- left ventricular
- left atrial
- blood pressure
- ejection fraction
- mitral valve
- heart rate
- heart failure
- acute heart failure
- aortic stenosis
- atrial fibrillation
- body mass index
- pulmonary hypertension
- hypertrophic cardiomyopathy
- mycobacterium tuberculosis
- acute myocardial infarction
- hypertensive patients
- heart rate variability
- catheter ablation
- convolutional neural network
- type diabetes
- deep learning
- prognostic factors
- artificial intelligence
- electronic health record
- big data
- percutaneous coronary intervention
- skeletal muscle
- weight gain
- high intensity