Arterial and Plethysmographic Waveform Analysis in Anesthetized Patients with Hypovolemia

Abstract

Arterial and pulse oximetry respiratory-induced changes in waveform variables are reliable indicators of mild hypovolemia in anesthetized patients. The pulse oximetry plethysmographic waveforms accurately reflect arterial waveforms during more progressive hypovolemia.

Bench-to-bedside review: Functional hemodynamics during surgery - should it be used for all high-risk cases?

“…PWV can be calculated as the difference between the maximal and minimal plethysmographic signal amplitudes divided by the amplitude of the signal during apnea or by the mean of the two values [57]. However, there are other variables and terms that are used to describe and measure PWV that may differ from each other [55].…”

“…In the absence of an automated measurement [58], the variations in the plethysmographic signal should be simply eyeballed, although there are no data regarding the sensitivity and accuracy of such observation. PWV has been shown to accurately reflect changes in circulating blood volume intraoperatively [31,57] and in fluid responsiveness in patients undergoing major abdominal surgery [5,59] and cardiac surgery [58,60]. …”

Detecting hypovolemia in postoperative patients using a discrete Fourier transform

“…In recent years, instead of conventional static hemodynamic variables (e.g., central venous pressure (CVP) [11,12], or heart rate (HR) [13]), dynamic parameters have emerged as useful techniques to predict fluid responsiveness in ICU patients [14] (e.g., systolic pressure variation [15], pulse pressure variation [16], central venous oxygen saturation (ScvO 2 ) [17]), and new variables have been introduced to guide fluid therapy in critically ill patients (e.g., global end-diastolic volume index (GEDVI) [18], hypovolemic index [19], extravascular lung water index [20]). However, each of these variables has limitations (regarding the physical condition [21] or age [22] of patients), and currently, no model exists to detect ongoing hypovolemia or bleeding [3].…”

A computational model based on human performance for fluid management in critical care

“…Despite these simplifications, however, the simulator aims to faithfully preserve the relationships between the elements themselves and the final simulator outputs. Regarding the evolution of dynamic parameters of fluid responsiveness and their relationship with hemorrhage and fluid responsiveness status, the simulator uses data from published studies [8], [9], [10]. The model begins with a baseline state that includes a height in inches, weight in kilos, HR, SBP, DBP, central venous pressure (CVP), left ventricular enddiastolic volume (LVEDV), and left-ventricular endsystolic volume (LVESV).…”