Secondary Logo

Journal Logo

Technology, Computing, and Simulation: Technical Communication

Respiratory Variation in Pulse Pressure and Plethysmographic Waveforms

Intraoperative Applicability in a North American Academic Center

Maguire, Sinead, MD; Rinehart, Joseph, MD; Vakharia, Shermeen, MD; Cannesson, Maxime, MD, PhD

Author Information
doi: 10.1213/ANE.0b013e318200366b

Dynamic variables (such as pulse pressure variation [ΔPP] or respiratory variations in the plethysmographic waveform amplitude [ΔPOP]) are the best predictors of fluid responsiveness in patients under general anesthesia and mechanical ventilation1,2 and they can now be continuously and noninvasively monitored.36 Moreover, recently published studies have suggested that they could be used for intraoperative goal-directed fluid management.79 However, these variables present with conditions of application and potential limitations that may decrease their applicability in daily clinical practice. These conditions of applications are (1) general anesthesia,2 (2) sinus rhythm,2 and (3) mechanical ventilation10 with (a) a tidal volume (VT) ≥8 mL/kg of body weight1113 and (b) a positive end-expiratory pressure (PEEP) <5 cm H2O. Moreover, ΔPP calculation requires an arterial line whereas ΔPOP only requires a pulse oximeter.2,14

Consequently, the goal of this retrospective study was to define the clinical applicability of intraoperative use of these variables in an academic North American center.


Surgical Procedures

After obtaining IRB approval (University of California Irvine, Irvine, CA), we extracted clinical data from anesthesia procedures performed at our institution (University of California Irvine, Medical Center, Orange, CA) from January 1, 2009 to December 31, 2009. Cardiac and thoracic surgery cases were excluded because these are not situations in which hemodynamic variables such as ΔPP and ΔPOP can be used (356 cases in 2009 at our institution). From this database (SIS Anesthesia™; Surgical Information Systems, Alpharetta, GA), we identified the number of cases that presented predefined conditions of application. Because this involved a retrospective electronic chart review, we relied on clinician input of data in patient files for the collection of data.

Essential Conditions of Applications

The following conditions of applications were screened in the general population and in the subpopulation of patients with an arterial line: (1) general anesthesia,2 (2) mechanical ventilation10 with (3) VT ≥8 mL/kg of body weight,1113 (4) PEEP <5 cm H2O, and (5) sinus rhythm.2 Mechanical ventilation was defined as volume or pressure-controlled ventilation with no spontaneous breathing activity. Data were collected in absolute values and were expressed as a percentage of the total number of procedures. Patients with an arterial line were also screened at each step.

Potential Limitations

From the resulting values, potential limitations to the use of dynamic variables of fluid responsiveness were screened. These potential limitations have not yet been definitively proven and are still under discussion. They include open chest procedures,15 use of a vasopressor drip (because it can affect vasomotor tone and potentially the plethysmographic waveform16), and laparoscopic procedures (because insufflation increases intraabdominal pressure and can affect ΔPP and/or ΔPOP values17).

Statistical Analysis

Data are expressed as absolute number and percentages related to the whole population and/or to patients who met the criteria for ΔPP and ΔPOP monitoring.


Overall Population Description

Over the 1-year study period, 12,308 anesthesia procedures were performed at our institution. Type of surgery and ASA classification are shown in Table 1. Incidence of conditions of application in the whole population are shown in Figure 1. In all, 4792 cases (38.9%) were found to have normal sinus rhythm as well as all of the conditions of application.

Table 1
Table 1:
Type of Surgery and ASA Classification in the Whole Population
Figure 1
Figure 1:
Flow chart showing methods involved to reach final value of patients to whom invasive and/or noninvasive dynamic variables of fluid responsiveness may be clinically applied. All percentages above and including sinus rhythm are related to the whole population (n = 12,308). Percentages below sinus rhythm are related to patients who met the criteria for variations in pulse pressure (ΔPP) and variations in the plethysmographic waveform (ΔPOP) monitoring (n = 4792). A line = arterial line; PEEP = positive end-expiratory pressure.

Incidence of Invasive Arterial Pressure Monitoring

The use of arterial lines was also recorded at multiple stages in this process. It was found that 1936 (15.7%) of the total 12,308 surgical procedures involved patients with an arterial line. General anesthesia was performed in 1898 cases (98.0%). Mechanical ventilation was used in 1847 cases (95.4%) with a VT ≥8 mL/kg in 1182 cases (61.1%) and a PEEP ≤5 cm H2O in 1091 cases (56.4%). Of this value, 72 cases (3.7%) involved patients with cardiac arrhythmias causing them to be excluded. In all, 1019 patients (52.6%) were found to have normal sinus rhythm as well as all of the above-mentioned conditions of application.


The results from our study show that 39% of the patients undergoing an anesthesiology procedure from January 1, 2009 to December 31, 2009 in our institution presented all conditions of application for the use of dynamic variables of fluid responsiveness based on cardiopulmonary interactions (77% noninvasively [ΔPOP] and 23% invasively [ΔPP]). In all patients with an arterial line, 53% presented all conditions of application of ΔPP.

Recently, these variables have been proposed for goal-directed fluid management,9,14 and studies conducted in the clinical setting have obtained promising results for improving patients' postoperative outcome.7,8,18 However, these indices require specific conditions to be of use. In the 39% of the whole population who met all of the prespecified conditions, a noninvasive index such as ΔPOP could be used for hemodynamic assessment and optimization. For the purpose of ΔPP monitoring, an arterial line is required. In our population, 23% of the patients who presented no limitations to the use of dynamic variables of fluid responsiveness were equipped with an arterial line. These patients could be optimized using ΔPP during surgery. Interestingly, 63% of these patients were classified as ASA physical status III or IV and would potentially benefit from goal-directed hemodynamic optimization.

Another limitation has recently been described by De Backer et al.19 and is related to the respiratory rate. These authors have shown that a heart rate/respiratory rate ratio <3.6 decreased the ability of ΔPP to predict fluid responsiveness. We were unable to screen for this limitation in our population of patients. However, the study by De Backer et al. was conducted in the intensive care unit and the ratio between heart rate and respiratory rate was attributable to high respiratory rate values (up to 40/min). It is likely that such high respiratory rates would not be encountered in the operating room anesthesiology setting. Also, we did not screen for right ventricular failure.

In conclusion, our study found that 39% of the patients undergoing surgical procedures in the operating room in our institution from January 1, 2009 to December 31, 2009 met the criteria for the monitoring of fluid responsiveness using noninvasively measured ΔPOP. Of the patients with arterial catheters, 53% met the criteria for the monitoring of ΔPP.


1. Marik PE, Cavallazzi R, Vasu T, Hirani A. Dynamic changes in arterial waveform derived variables and fluid responsiveness in mechanically ventilated patients: a systematic review of the literature. Crit Care Med 2009;37:2642–7
2. Michard F. Changes in arterial pressure during mechanical ventilation. Anesthesiology 2005;103:419–28
3. Aboy M, McNames J, Thong T, Phillips CR, Ellenby MS, Goldstein B. A novel algorithm to estimate the pulse pressure variation index deltaPP. IEEE Trans Biomed Eng 2004;51:2198–203
4. Auler JO Jr, Galas F, Hajjar L, Santos L, Carvalho T, Michard F. Online monitoring of pulse pressure variation to guide fluid therapy after cardiac surgery. Anesth Analg 2008;106:1201–6
5. Cannesson M, Slieker J, Desebbe O, Bauer C, Chiari P, Hénaine R, Lehot JJ. The ability of a novel algorithm for automatic estimation of the respiratory variations in arterial pulse pressure to monitor fluid responsiveness in the operating room. Anesth Analg 2008;106:1195–2000
6. Pestel G, Fukui K, Hartwich V, Schumacher PM, Vogt A, Hiltebrand LB, Kurz A, Fujita Y, Inderbitzin D, Leibundgut D. Automatic algorithm for monitoring systolic pressure variation and difference in pulse pressure. Anesth Analg 2009;108:1823–9
7. Lopes MR, Oliveira MA, Pereira VO, Lemos IP, Auler JO Jr, Michard F. Goal-directed fluid management based on pulse pressure variation monitoring during high-risk surgery: a pilot randomized controlled trial. Crit Care 2007;11:R100
8. Buettner M, Schummer W, Huettemann E, Schenke S, van Hout N, Sakka SG. Influence of systolic-pressure-variation-guided intraoperative fluid management on organ function and oxygen transport. Br J Anaesth 2008;101:194–9
9. Cannesson M. Arterial pressure variation and goal-directed fluid therapy. J Cardiothorac Vasc Anesth 2009;24:487–97
10. De Backer D, Pinsky MR. Can one predict fluid responsiveness in spontaneously breathing patients? Intensive Care Med 2007;33:1111–3
11. Charron C, Fessenmeyer C, Cosson C, Mazoit JX, Hebert JL, Benhamou D, Edouard AR. The influence of tidal volume on the dynamic variables of fluid responsiveness in critically ill patients. Anesth Analg 2006;102:1511–7
12. De Backer D, Heenen S, Piagnerelli M, Koch M, Vincent JL. Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med 2005;31:517–23
13. Desebbe O, Boucau C, Farhat F, Bastien O, Lehot JJ, Cannesson M. The ability of pleth variability index to predict the hemodynamic effects of positive end-expiratory pressure in mechanically ventilated patients under general anesthesia. Anesth Analg 2010;110:792–8
14. Desebbe O, Cannesson M. Using ventilation induced plethysmographic variations to optimize patient fluid status. Curr Opin Anaesthesiol 2008;21:772–8
15. Reuter DA, Goepfert MS, Goresch T, Schmoeckel M, Kilger E, Goetz AE. Assessing fluid responsiveness during open chest conditions. Br J Anaesth 2005;94:318–23
16. Landsverk SA, Hoiseth LO, Kvandal P, Hisdal J, Skare O, Kirkeboen KA. Poor agreement between respiratory variations in pulse oximetry photoplethysmographic waveform amplitude and pulse pressure in intensive care unit patients. Anesthesiology 2008;109:849–55
17. Duperret S, Lhuillier F, Piriou V, Vivier E, Metton O, Branche P, Annat G, Bendjelid K, Viale JP. Increased intra-abdominal pressure affects respiratory variations in arterial pressure in normovolaemice and hypovolaemic mechanically ventilated pigs. Intensive Care Med 2007;33:163–71
18. Mayer J, Boldt J, Beschmann R, Stephan A, Suttner S. Individualized intraoperative patient optimization using uncalibrated arterial pressure waveform analysis in higher risk patients undergoing major abdominal surgery. Eur J Anaesthesiol 2009;26:3A–P4-3
19. De Backer D, Taccone FS, Holsten R, Ibrahimi F, Vincent JL. Influence of respiratory rate on stroke volume variation in mechanically ventilated patients. Anesthesiology 2009; 110:1092–7


SM participated in the design of the study, collected the data, and drafted the manuscript. JR and SV collected the data and helped to draft the manuscript. MC conceived and designed the study, analyzed the data, performed the statistical analysis and final approval of the manuscript. All authors read and approved the final manuscript.

© 2011 International Anesthesia Research Society