Impact of respiratory cycle during mechanical ventilation on beat-to-beat right ventricle stroke volume estimation by pulmonary artery pulse wave analysis

Abstract

Abstract Background The same principle behind pulse wave analysis can be applied on the pulmonary artery (PA) pressure waveform to estimate right ventricle stroke volume (RVSV). However, the PA pressure waveform might be influenced by the direct transmission of the intrathoracic pressure changes throughout the respiratory cycle caused by mechanical ventilation (MV), potentially impacting the reliability of PA pulse wave analysis (PAPWA). We assessed a new method that minimizes the direct effect of the MV on continuous PA pressure measurements and enhances the reliability of PAPWA in tracking beat-to-beat RVSV. Methods Continuous PA pressure and flow were simultaneously measured for 2–3 min in 5 pigs using a high-fidelity micro-tip catheter and a transonic flow sensor around the PA trunk, both pre and post an experimental ARDS model. RVSV was estimated by PAPWA indexes such as pulse pressure (SVPP), systolic area (SVSystAUC) and standard deviation (SVSD) beat-to-beat from both corrected and non-corrected PA signals. The reference RVSV was derived from the PA flow signal (SVref). Results The reliability of PAPWA in tracking RVSV on a beat-to-beat basis was enhanced after accounting for the direct impact of intrathoracic pressure changes induced by MV throughout the respiratory cycle. This was evidenced by an increase in the correlation between SVref and RVSV estimated by PAPWA under healthy conditions: rho between SVref and non-corrected SVSD – 0.111 (0.342), corrected SVSD 0.876 (0.130), non-corrected SVSystAUC 0.543 (0.141) and corrected SVSystAUC 0.923 (0.050). Following ARDS, correlations were SVref and non-corrected SVSD – 0.033 (0.262), corrected SVSD 0.839 (0.077), non-corrected SVSystAUC 0.483 (0.114) and corrected SVSystAUC 0.928 (0.026). Correction also led to reduced limits of agreement between SVref and SVSD and SVSystAUC in the two evaluated conditions. Conclusions In our experimental model, we confirmed that correcting for mechanical ventilation induced changes during the respiratory cycle improves the performance of PAPWA for beat-to-beat estimation of RVSV compared to uncorrected measurements. This was demonstrated by a better correlation and agreement between the actual SV and the obtained from PAPWA.