resuscitation from hypotensive circulatory shock is often more complex than just giving intravascular fluids . even in fluid - responsive hypotensive patients , vital organ perfusion may remain compromised despite fluid infusion if the mean arterial pressure ( map ) does not also increase with increasing cardiac output ( co ) . garca and colleagues suggested an approach that would predict whether the hypotensive patient would increase their map in response to intravascular fluid loading . there is a tight correlation between positive - pressure ventilation - induced changes in arterial pulse pressure ( pp ) , called pulse pressure variation ( ppv ) , and fluid responsiveness . ppv is calculated as the ratio of difference between maximum and minimum pp to their mean as assessed over about 5 breaths or 20 seconds . not surprisingly , subsequent studies showed that similarly calculated stroke volume variation ( svv ) , when measured independently , also predicted volume responsiveness . importantly , pp is created by stroke volume ( sv ) into the central arterial compartment as quantified by a transfer function . if arterial elastance ( ea ) and compliance remain constant , then aortic pp will vary directly with sv . if the bedside physician wants to know whether their hypotensive patient will increase their map in response to fluid loading , then they need to know two things . first , is the patient volume responsive ? if the patient is not responsive , then volume loading will not increase co. second , the physician needs to know the patient 's vasomotor tone . if the patient has marked vasodilation , as commonly occurs in septic shock , then map may not increase in response to fluid loading even if co does . to know whether a fluid - responsive patient is also pressure responsive the reciprocal of compliance is ea , which defines the pp / sv relation . increasing vasomotor tone increases both map and pp relative to co and sv . if one knew both ppv and svv , their ratio would define a dynamic ea ( eadyn ) . theoretically , map and pp should co - vary with changes in co if the heart rate remains constant . we previously predicted that ppv / svv > 0.8 would define pressure - responsive subjects if co increased . relative to this construct , garca and colleagues examined the ability of the ppv / svv ratio , deferred to as eadyn , to predict changes in map in 25 hypotensive patients with preserved volume responsiveness ( defined as map < 65 mmhg or systolic blood pressure < 90 mmhg and svv > 10% ) . using a standard 500 ml colloid fluid bolus , the authors defined map responders as those with a > 15% increase in map . they found that a baseline eadyn value > 0.89 predicted > 15% map increase after fluid administration with a sensitivity of 94% ( 95% confidence interval = 69.8 to 99.8% ) and a specificity of 100% ( 95% confidence interval = 66.4 to 100% ) . their clinically derived eadyn threshold of > 0.89 is remarkable similar to our > 0.8 value based on vascular modeling . importantly , as long as the ppv and svv values are great enough to define a slope , this relationship will remain constant and predictive even during spontaneous ventilation and with cardiac arrhythmias because eadyn is independent of volume responsiveness . since all of the commercially available arterial pressure - derived co monitoring devices report ppv and svv , this added eadyn parameter to define those patients needing vasopressors earlier in their management should have a significant impact on resuscitation efficacy . before embracing this approach and these findings totally , caution needs to be used in its routine bedside application . eadyn is a measure of arterial stiffness , which is itself partially determined by vasomotor tone . ea increases with age , with the expression of atherosclerosis and with aortic cross - clamping during aortic vascular procedures . for all these conditions , however , if sv increases then pp will also increase . regrettably , map may not increase as much as pp because diastolic pressure may remain constant . furthermore , pp can be independently increased by increasing left ventricular ejection velocity . to the extent that inotropic agents are being used , one may presume an increase in map not realized by increasing co even if eadyn > 0.89 . the above study , how - ever , used an arterial pulse contour estimating method to derive co and svv , and herein rests a potential problem . much attention has focused on using arterial pulse contour analysis devices at the bedside to measure co and svv from the arterial pulse . unfortunately , most indwelling arterial catheters sample a more peripheral arterial pressure signal , whose waveform may be altered in unexpected ways as the arterial tone , pulse wave velocity and left ventricular contractility vary . although this variability in co estimates can be readily improved by calibration , it will not improve the accuracy of the ppv / svv relation ( that is , eadyn ) . the eadyn accuracy is intrinsic to the assumptions used by each device to estimate svv . this is because ppv can be measured directly and is accurate when compared with ppv measured manually . all arterial pressure - sensing devices that estimate co do so by assuming a constant ea . how , then , is it possible for an algorithm that uses arterial pressure to calculate co to show differing changes in pp relative to sv over time ? the three major commercially available monitoring devices , however , do not share the same shoe size - the variance amongst these devices to estimate changing co is significant . the flotracdevice estimates svv from the standard deviation of the individual arterial pressure values over single beats averaged over 20 seconds . assuming the sv variance has a normal distribution , this assumption is valid for calculating svv . importantly , svv as a time - series function may not be normally distributed during atrial fibrillation and with vigorous spontaneous inspiratory efforts . how much error such non - normal distribution would introduce into the svv calculation is not known , but on theoretical modeling the degree of non - normal distribution would need to be great for it to affect svv by the standard deviation method . the picco uses a proprietary algorithm based on the ventriculo - arterial coupling transfer function   to calculate co. this co estimate is averaged over 20 to 30 seconds and is quite accurate . however , since the picco no longer reports individual sv values on a beat - to - beat basis , it is unclear how it derives svv . the lidco uses a simple power transfer function to estimate sv on a beat - to - beat basis and calculates co from the mean sv values . to the extent that this power transfer function is accurate over time , the svv estimates should also be accurate . since this device does not use the pulse contour , the lidco remains accurate with dampened arterial pressure signals . accordingly , although each device reports ppv and svv values , the cross - correlation amongst devices based on their different algorithms is poor . validation of eadyn thus needs to be done independently both for each device and for different types of patients before this new bedside parameter is used for clinical decision - making . co : cardiac output ; ea : arterial elastance ; eadyn : dynamic arterial elastance ; map : mean arterial pressure ; pp : pulse pressure ; ppv : pulse pressure variation ; sv : stroke volume ; svv : stroke volume variation .
assessment of vasomotor tone is essential in defining appropriate resuscitation strategies for the hypotensive patient . 
 although changes in mean arterial pressure to cardiac output define arterial resistance , resistance is only one component of vasomotor tone . 
 compliance is the other component . 
 the reciprocal of compliance is arterial elastance ( ea ) . 
 importantly , dynamic ea can be estimated by the pulse pressure variation to stroke volume variation relation . 
 dynamic ea is only one component of vasomotor tone , however , and increases in pulse pressure may not be proportional to increases in mean arterial pressure . 
 also , devices that use the arterial pressure pulse to calculate the stroke volume have an inherent bias that is different amongst devices based on their transfer function algorithms . 
 the use of dynamic ea for clinical decision - making thus needs to be validated separately for different devices and types of patients .