Original Contribution
Exploring the best predictors of fluid responsiveness in patients with septic shock

https://doi.org/10.1016/j.ajem.2017.03.052Get rights and content

Abstract

Objective

To evaluate respiratory variations in carotid and brachial peak velocity and other hemodynamic parameters to predict responsiveness to fluid challenge.

Methods

A prospective observational study was performed on mechanically ventilated patients with septic shock. Outcomes included the measurements of central venous pressure, intrathoracic blood volume index, stroke volume variation (SVV), pleth variability index(PVI), and ultrasound assessments of respiratory variations in inferior vena cava diameter (ΔIVC), carotid Doppler peak velocity (ΔCDPV), and brachial artery peak velocity (ΔVpeak brach).

Results

All patients received 200 mL normal saline challenge. There were 27 responders and 22 non-responders. Responders had higher SVV, PVI, ΔIVC, ΔCDPV, and ΔVpeak brach measurements. In addition, all these measurements had statistically significant linear correlations with changes in cardiac index (CI).When responders were defined by ΔCI  10%, receiver operating characteristics (ROC) curve analysis showed that fluid responsiveness could be predicted:11.5% optimal cut-off 1evels of SVV with sensitivity of 75% and specificity of 85%, 15.5% optimal cut-off 1evels of PVI with sensitivity of 65% and specificity of 80%, 20.5% optimal cut-off 1evels of ΔIVC with sensitivity of 67% and specificity of 77%, 13% optimal cut-off 1evels of ΔCDPV with sensitivity of 78%% and specificity of 90%, 11.7% optimal cut-off 1evels of ΔVpeak brach with sensitivity of 70% and specificity of 80%.

Conclusion

Ultrasound assessment of ΔIVC and ΔVpeak brach, especially ΔCDPV, could predict fluid responsiveness and might be recommended as a continuous and noninvasive method to monitor functional hemodynamic parameter in mechanically ventilated patients with septic shock.

Introduction

Septic shock is a serious infectious condition characterized by low blood pressure and multiple organ damage. One of the traditional recommendations is to administer intravenous fluids as the first step to improve blood pressure [1], [2]. However, studies have shown that not every patient benefits from aggressive intravenous hydration [3], [4]. Only about 40% of hypotensive patients with sepsis respond to fluid infusion with improvement in blood pressure and outcomes [5], [6]. Those who do not respond to fluid infusion are liable to develop high intravascular pressure, pulmonary edema, heart failure with a high associated mortality [7], [8], [9]. Therefore, it is crucial to develop a hemodynamically-guided approach to evaluate volume status and to identify patients who are likely to benefit from fluid administration.

Previous studies have shown that certain parameters may correlate with volume status. The traditional static parameters, such as central venous pressure (CVP), pulmonary wedge pressure, and intrathoracic blood volume index (ITBVI), have been shown not to correlate with patient volume status [10], [11]. Hemodynamic parameters, such as stroke volume variation (SVV) and pleth variability index (PVI) may better predict fluid responsiveness. However, assessments of these parameters require invasive procedures and special monitoring equipment, which limits their clinical application [12].

In recent years, ultrasound has been proposed as a tool to help guide fluid resuscitation [13], [14]. According to the Frank-Starling curve, when patients are in the low volume status, the cardiac preload is low and the curve is in the rising phase,therefore intrathoracic pressure fluctuations by breathing could have a greater impact on cardiac stroke volume(SV) [15], [16]. The variation of SV may be assessed by variation of arterial blood peak velocity on the Doppler ultrasound. At last, it leads the higher variation of SV and arterial blood peak velocity. Studies have shown that respiratory variation in aortic blood peak velocity had high sensitivity and specificity to predict fluid responsiveness [17], [18], [19]. However, measurements of aortic blood flow velocity require transesophageal ultrasound which is an invasive procedure. Measurements of femoral artery blood flow are frequently affected by changes in intra-abdominal pressure. Measures of carotid or brachial artery flow were recently shown to predict fluid responsiveness [18], [19], [20], [21]. Both these peripheral arteries are relatively superficial large vessels which can provide easy ultrasound evaluation and high-quality images. However, assessment of respiratory variation in artery peak velocity in these two arteries in ventilated patients with septic shock has not been studied.

In the current study, we measured the respiratory variation in arterial blood peak velocity in carotid and brachial arteries and compared their use against that of other static and hemodynamic parameters for predicting fluid responsiveness in ventilated patients with septic shock. Clinical application of these measures is discussed.

Section snippets

Study design and patient selection

A prospective observation study was performed in the Intensive Care Unit in our hospital between January 2012 and December 2015. Study protocol was approved by the Institutional Ethics Committee. Written informed consent was obtained from every patient's health care proxy.

Inclusion criteria were: 1) age  18 years; 2) patients who met the diagnostic criteria for septic shock, which was defined as systolic blood pressure (SBP) < 90 mmHg, or mean arterial pressure (MAP) < 70 mmHg, or SBP decreases 40 

Results

A total of 49 patients were enrolled in the study, of which 27 patients were categorized as responders on fluid challenge (responder group) and 22 as non-responders (non-responder group). The baseline characteristics are summarized in Table 1. There were no statistically significant differences in demographic and clinical variables. Most common source of infection was respiratory infection.

Before fluid challenge, patients in the responder group had higher SVV, PVI, ΔIVC, ΔCDPV, and ΔVpeak brach

Discussion

In the present study, we compared the predictive values of several measures for fluid responsiveness in ventilated patients with septic shock. Respiratory variation in carotid Doppler peak velocity (ΔCDPV) showed the best predictive value for fluid responsiveness in this patient population.

Intravenous fluid infusion was recommended as a key element in the treatment of patients with septic shock. Fluid infusion increases the preload on the heart, augments cardiac output, and improves tissue

Acknowledgements

This study was funded by the Ministry of Science and Technology of the People's Republic of China (grant number 2012BAI11B05) and Beijing Municipal Science and Technology Commission (BSTC) (grant number D101100050010058).

References (29)

  • S. Vandervelden et al.

    Initial resuscitation from severe sepsis: one size does not fit all

    Anaesthesiol Intensive Ther

    (2015)
  • A.B. Groeneveld

    Fluids in septic shock: too much of a good thing?

    Crit Care

    (2010)
  • S.W. Thiel et al.

    Non-invasive stroke volume measurement and passive leg raising predict volume responsiveness in medical ICU patients: an observational cohort study

    Crit Care

    (2009)
  • S. Preau et al.

    Passive leg raising is predictive of fluid responsiveness in spontaneously breathing patients with severe sepsis or acute pancreatitis

    Crit Care Med

    (2010)
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