Publications in Scientific Journals:
B. Hametner, S. Parragh, T. Weber, S. Wassertheurer:
"Wave intensity of aortic root pressure as diagnostic marker of left ventricular systolic dysfunction";
Systolic left ventricular function strongly influences the blood pressure waveform. Therefore, pressure-derived parameters might potentially be used as non-invasive, diagnostic markers of left ventricular impairment. The aim of this study was to investigate the performance of pressure-based parameters in combination with electrocardiography (ECG) for the detection of left ventricular systolic dysfunction defined as severely reduced ejection fraction (EF).
Methods and results
Two populations, each comprising patients with reduced EF and pressure-matched controls, were included for the main analysis (51/102 patients) and model testing (44/88 patients). Central pressure was derived from radial readings and used to compute blood flow. Subsequently, pulse wave analysis and wave intensity analysis were performed and the ratio of the two peaks of forward intensity (SDR) was calculated as a novel index of ventricular function. SDR was significantly decreased in the reduced EF group (2.5 vs. 4.4, P<0.001), as was central pulse pressure, augmentation index and ejection duration (ED), while the QRS-duration was prolonged. SDR and ED were independent predictors of ventricular impairment and when combined with QRS in a simple decision tree, a reduced EF could be detected with a sensitivity of 92% and a specificity of 80%. The independent power of ED, SDR and QRS to predict reduced EF was furthermore confirmed in the test population.
The detection or indication of reduced ejection fraction from pressure-derived parameters seems feasible. These parameters could help to improve the quality of cardiovascular risk stratification or might be used in screening strategies in the general population.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Created from the Publication Database of the Vienna University of Technology.