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. 2021 Mar;25(1):11-18.
doi: 10.1177/1089253220960894. Epub 2020 Sep 21.

Venous Waveform Analysis Correlates With Echocardiography in Detecting Hypovolemia in a Rat Hemorrhage Model

Ryan J Lefevre  1 , Claudius Balzer  1 , Franz J Baudenbacher  2 , Matthias L Riess  1   2   3 , Antonio Hernandez  1 , Susan S Eagle  1
Affiliations

Venous Waveform Analysis Correlates With Echocardiography in Detecting Hypovolemia in a Rat Hemorrhage Model

Ryan J Lefevre et al. Semin Cardiothorac Vasc Anesth. 2021 Mar.

Abstract

Background: Assessing intravascular hypovolemia due to hemorrhage remains a clinical challenge. Central venous pressure (CVP) remains a commonly used monitor in surgical and intensive care settings for evaluating blood loss, despite well-described pitfalls of static pressure measurements. The authors investigated an alternative to CVP, intravenous waveform analysis (IVA) as a method for detecting blood loss and examined its correlation with echocardiography.

Methods: Seven anesthetized, spontaneously breathing male Sprague Dawley rats with right internal jugular central venous and femoral arterial catheters underwent hemorrhage. Mean arterial pressure (MAP), heart rate, CVP, and IVA were assessed and recorded. Hemorrhage was performed until each rat had 25% estimated blood volume removed. IVA was obtained using fast Fourier transform and the amplitude of the fundamental frequency (f1) was measured. Transthoracic echocardiography was performed utilizing a parasternal short axis image of the left ventricle during hemorrhage. MAP, CVP, and IVA were compared with blood removed and correlated with left ventricular end diastolic area (LVEDA).

Results: All 7 rats underwent successful hemorrhage. MAP and f1 peak amplitude obtained by IVA showed significant changes with hemorrhage. MAP and f1 peak amplitude also significantly correlated with LVEDA during hemorrhage (R = 0.82 and 0.77, respectively). CVP did not significantly change with hemorrhage, and there was no significant correlation between CVP and LVEDA.

Conclusions: In this study, f1 peak amplitude obtained by IVA was superior to CVP for detecting acute, massive hemorrhage. In addition, f1 peak amplitude correlated well with LVEDA on echocardiography. Translated clinically, IVA might provide a viable alternative to CVP for detecting hemorrhage.

Keywords: Fourier transform; central venous pressure; hemodynamic monitoring; hypotension; vascular.

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Figures

Figure 1:
Figure 1:. Central venous f1 amplitude decreases with hemorrhage.
Central venous waveform obtained at baseline (A) and after 8 mL of hemorrhage (B) in a rat model. Corresponding fast Fourier transform at baseline (C) and after 8 mL of hemorrhage (D). The first peak represents the amplitude of the venous signal at the heart rate of the animal. The f1 peak significantly decreases following hemorrhage (P < 0.01).
Figure 2:
Figure 2:. LVEDA decreases with hemorrhage.
(A) Shows representative baseline parasternal short axis view of the left ventricle during diastole prior to hemorrhage. (B) Shows a similar view after 8 mL of blood was removed revealing reduced left ventricular size.
Figure 3:
Figure 3:. f1 amplitude detects hemorrhage and correlates significantly with LVEDA.
(A) Depicts f1 amplitude during hemorrhage of 2, 4, 6, and 8 mL. Error bars indicate 95% Confidence Interval. * indicates significant difference of P < 0.05, ** indicates P < 0.01. (B) shows the correlation between f1 amplitude and LVEDA during this hemorrhage (R=0.77) with best fit equation of Y = (1.179 +/− 0.1861) * X – (0.4137 +/− 0.149). Dotted lines indicate 95% Confidence Interval.
Figure 4:
Figure 4:. MAP detects hemorrhage and correlates significantly with LVEDA.
(A) Depicts MAP during hemorrhage of 2, 4, 6, and 8 mL. Error bars indicate 95% Confidence Interval. * indicates significant difference of P < 0.05, ** indicates P < 0.01, *** indicates P < 0.001. (B) Shows the correlation between MAP and LVEDA during this hemorrhage (R=0.82) with best fit equation of Y = (161.1 +/− 17.78) * X – (42.67 +/− 13.79). Dotted lines indicate 95% Confidence Interval.
Figure 5:
Figure 5:. CVP does not detect hemorrhage or correlate with LVEDA.
(A) Depicts CVP during hemorrhage of 2, 4, 6, and 8 mL showing no significant change. Error bars indicate 95% Confidence Interval. (B) shows no significant correlation between CVP and LVEDA during this hemorrhage (R=0.14) with best fit equation of Y = (3.044 +/− 3.285) * X + (1.62 +/− 2.59). Dotted lines indicate 95% Confidence Interval.
Figure 6:
Figure 6:. MAP and f1 show superior sensitivity and specificity compared to CVP for detecting hemorrhage.
ROC curve showing the response of MAP (AUC 0.93 [0.85–1.0]), f1 (AUC 0.90 [0.78–1.0]), and CVP (AUC 0.54 [0.34–0.73]).
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