Evaluation of fluid responsiveness by ultrasound


Overview

Fluid therapy is the cornerstone of hemodynamic resuscitation, and its aim is to increase tissue perfusion. Notably, a positive fluid balance is associated with a poor outcome. Thus it is important to optimize fluid administration and identify patients who may most benefit from it while trying to predict fluid responsiveness. Fluids increase tissue perfusion by means of an increase in cardiac output (CO), which is related to an increase in cardiac preload. However, the relationship between preload and CO or, more precisely, between left ventricular (LV) preload and stroke volume is curvilinear ( Figure 38-1 ). In patients with altered contractility the curve is even flattened. Fluids should be administered only to those on the steep part of the curve.

Figure 38-1, Prediction of fluid responsiveness with static indices. Fluid responsiveness depends on the patient’s intrinsic contractility (1 = normal, 2 = moderately altered, 3 = severely altered) and position on the Frank-Starling curve (A, B, and C). A given value of preload (e.g., B) may be associated with a positive response to fluids (B1) or no response to fluids (B3). Only extreme values of preload such as A (very low) and C (very high) are predictive of fluid responsiveness. Of note, even patients with severely impaired cardiac function may respond to fluids (A3).

Another important aspect is fluid tolerance. When preload increases, hydrostatic pressure also increases. The magnitude of the increase in hydrostatic pressure for a given increase in preload depends on patient’s position on the Frank-Starling curve and on ventricular compliance ( Chapter 36 ). In patients with altered diastolic function, the increase in hydrostatic pressure is more pronounced ( Figure 38-2 ). Tolerance to fluids also depends on right ventricular (RV) function. In patients with RV dysfunction, fluid administration may induce RV dilatation. This chapter illustrates mainly the role of ultrasound in evaluating fluid responsiveness in the intensive care unit (ICU).

Figure 38-2, Relationship between left ventricular (LV) volume and pressure. In patients with impaired LV compliance, an increase in preload is associated with an increase in pressure, even when cardiac output (CO) also increases ( A ). The increase in hydrostatic pressure is more pronounced when patients are on the flat part of the Frank-Starling curve ( B ).

Prediction of fluid responsiveness

The literature reports that only half of patients respond to the administration of fluids. Several static and dynamic indices can be used to predict fluid responsiveness ( Table 38-1 ). The technical details of these indices are discussed elsewhere in this book.

TABLE 38-1
Ultrasound Indices Used to Predict Fluid Responsiveness
Index Principle Comments
STATIC INDICES
Inferior vena cava diameter Diameter inversely proportional to CVP and thus RV preload Poor predictive value
LV area LV area inversely proportional to LV preload Poor predictive value. Kissing ventricles highly suggestive of a positive response to fluids
Mitral inflow pattern Small E wave suggests low PAOP and thus low LV preload Poor to moderate predictive value
Mitral inflow–to–mitral annulus ratio Low E/Ea suggest low PAOP and thus low LV preload Poor to moderate predictive value
DYNAMIC INDICES
Respiratory variations in aortic flow Mechanical ventilation induces cyclic changes in preload that result in cyclic changes in stroke volume only in preload-responsive patients Well-validated physiologic concept. Excellent predictive value. Many limitations. Cutoff value 12%
Respiratory variations in superior vena cava diameter Mechanical ventilation induces cyclic changes in preload that result in cyclic changes in superior vena cava diameter only in preload-responsive patients Excellent predictive value. Cutoff value 35%. Validated in only 1 trial
Respiratory variations in inferior vena cava diameter Respiration induces cyclic changes in preload that result in cyclic changes in inferior vena cava diameter only in preload-responsive patients Good predictive value. Cutoff value 15-18% (with different formulas). Proposed but questioned in spontaneously breathing patients
Expiratory pause Expiratory pause induces an abrupt increase in LV preload that results in an increase in stroke volume only in preload-responsive patients Excellent predictive value. Cutoff value 12%. Validated in only 1 trial
Passive leg-raising test Passive leg raising induces an abrupt increase in LV preload that results in an increase in stroke volume only in preload-responsive patients Excellent predictive value. Cutoff value 12%. Validated in several trials. Also valid in spontaneously breathing patients. Cumbersome
CVP , Central venous pressure; LV , left ventricular; PAOP , pulmonary artery occlusion pressure; RV , right ventricular.

Static indices

Ventricular pressure and volume can be measured with echocardiography to assess preload. Because a multitude of Frank-Starling curves exist (depending on the patient’s heart function), it is difficult to predict fluid responsiveness from a single estimate of preload. When preload is very low, only then is the likelihood of a patient being on the steep part of the Frank-Starling curve high. Conversely, when preload is very high, a patient’s chance to be fluid responsive is low. However, patients are usually in a more indefinite situation (see Figure 38-1 ).

The diameter of the inferior vena cava (IVC) reflects central venous pressure (CVP) and can be used to predict fluid responsiveness. When IVC diameter is markedly increased (>20 mm), the likelihood of a patient to be fluid responsive is low, whereas when the diameter is decreased (<10 mm), the likelihood appears to be higher. IVC diameter reflects RV preload, and even though it is measured from outside the thorax, it can be influenced by high intrathoracic and intraabdominal pressure. Hence return of blood to the heart may be impeded and fluid administration may not result in an increase in CO. A small IVC diameter usually indicates that RV preload is not elevated and venous return is not impeded; however, it cannot elucidate whether the left ventricle also works on the steep part of the Frank-Starling curve. The possibility of IVC collapse as a result of increased intraabdominal pressure or dilatation of the IVC when high positive end-expiratory pressure (PEEP) is used may further complicate the interpretation of changes in IVC diameter. Altogether, these factors explain why this method poorly predicts fluid responsiveness.

Color Doppler– and tissue Doppler imaging–derived mitral inflow patterns can be used to estimate pulmonary artery occlusion pressure (PAOP) and fluid responsiveness as mentioned elsewhere in this book. A low mitral E wave or a low mitral inflow E wave–to–mitral annulus ratio (E/Ea) suggests low PAOP and may reflect a greater chance to respond to fluid therapy. Nevertheless, its predictive value for fluid responsiveness varies in different published series, and no definite cutoff values of these echocardiographic parameters can be used to distinguish fluid responders from nonresponders. LV and RV size may be used to estimate preload. Ventricular size can be assessed visually or with echocardiography (calculation of ventricular diameters, surfaces, or volumes). Only extreme values of ventricular size appear to have some value in predicting fluid responsiveness. In this context, a small LV cavity is associated with a positive response to fluids, provided that the right ventricle is not dilated.

Dynamic indices

Dynamic indices include either variations in stroke volume with respiration and its surrogates related to heart-lung interactions or several tests that can be applied to detect fluid responsiveness. Their basic principle is that when preload is transiently increased, the expected subsequent increase in CO would occur only in patients who are on the steep part of the Frank-Starling curve. These patients are likely to respond to fluid therapy. Echocardiography is an essential tool in evaluating transient alterations in CO during various dynamic tests.

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