Dynamic indicators have consistently been shown to be superior to static indicators for prediction of fluid responsiveness in the intensive care unit and in the operating room. The dynamic indicators rely on the cardiopulmonary interactions in patients under general anesthesia and mechanical ventilation. Positive pressure insufflation increases pleural pressure (leading to a decrease in right ventricular filling) and transpulmonary pressure (increasing right ventricular afterload and, consequently, decreasing right ventricular stroke volume). Moreover, positive pressure ventilation (PPV) also induces changes in LV loading conditions. These phenomena are responsible for the respiratory variations observed in LV stroke volume.13 With greater VT, there are corresponding increases in cyclic perturbations in cardiac filling, and hence, increased PPV.
In this study, we approached the relationship between PVI and fluid responsiveness in the opposite manner from which it is usually studied. Rather than study the predictive effects of PPV on fluid responsiveness by giving fluids, we studied the relationship by decreasing preload. By increasing PEEP from 0 to 10 cm H2O, our aim was to decrease systemic venous return and, consequently, to decrease CO. Because factors leading to a decrease in CO induced by PEEP are similar to factors inducing respiratory variations of LV stroke volume or on its surrogates (systemic arterial pulse pressure or pulse oximeter plethysmographic waveform amplitude), we postulated that both PPV and PVI would be able to predict the effects of the addition of PEEP on CI. Few studies have reported the hemodynamic effects of PEEP with dynamic indicators.14 Michard et al.14 showed that changes in CI induced by adding PEEP were correlated with ΔPP (r = −0.91, P < 0.001) in ventilated patients with acute lung injury. This study included 14 patients ventilated with VT between 7 and 12 mL/kg body weight.
In our study, we found that both ΔPP and PVI were able to predict the effects of PEEP on CO but only when VT was ≥8 mL/kg. Our findings are consistent with the results from De Backer et al.,21 showing that ΔPP was not an accurate predictor of fluid responsiveness in septic patients ventilated with VT of 6 mL/kg in the intensive care unit.22 This corresponds to the finding in patients receiving norepinephrine in the intensive care unit where Charron et al.23 showed that ΔPP was affected by VT. The higher the VT, the higher the ΔPP. However, because cardiopulmonary interactions depend on respiratory compliance, some authors found that dynamic indicators of fluid responsiveness are still valuable in septic or acute respiratory distress syndrome conditions even when VT is low (6.4 ± 0.7 mL/kg) and when PEEP is high.24,25
We believe that in the perioperative setting, high respiratory compliances explain the inability of such small VT values to predict fluid responsiveness with dynamic indices. VT tends to influence the optimal threshold value of PVI (ranging from 12% to 13% according to VT), and PVI at ZEEP was different according to VT. These results emphasize the importance of the respiratory settings when using PVI or any other dynamic indicators. Several studies used different VT and/or PEEP values,26–28 thus making it more difficult to obtain a valuable threshold value. A recent experimental study confirms the importance of VT for the assessment of fluid responsiveness using dynamic indicators.29
In this study, we found differences in PVI and ΔPP threshold values for the prediction of fluid responsiveness. PVI values were significantly higher than ΔPP values. This is in contrast to published studies in which we found that PVI and ΔPP threshold values were similar in the evaluation of fluid responsiveness assessment.16 Because these studies were conducted in the operating room and in very standardized conditions, the difference in these findings is likely attributable to the difference in study protocols. In our study, it is likely that changes in venous pool at the site of measurement had an effect on PVI, because the plethysmographic waveform relies in part on light absorption by venous blood.30 By increasing PEEP, we can postulate that we increased the venous congestion in extrathoracic compartments. This hypothesis is supported by the fact that PI decreased after the addition of PEEP, whatever the VT. The decrease in stroke volume and the venous congestion induced by PEEP would then increase the constant absorption (DC) and decrease the PI. This may explain the differences in PVI and ΔPP values. However, further studies are required to explore this phenomenon.
Our study has some limits. First, results should be interpreted with caution because of the small sample size. These results cannot be extrapolated to the general population (patients were free of pulmonary disease, cardiac dysfunction, and rhythm disorder). We studied only 1 level of PEEP. Nevertheless, this level seems to be the most appropriate to avoid alveolar derecruitment after a recruitment maneuver.10
Because PVI reflects variations in PI over a given period of time, any change in local conditions such as a variation in vasomotor tone may alter PI and, consequently, PVI. Recently, Landsverk et al.31 found a poor agreement between ΔPOP and ΔPP in patients receiving vasoactive drugs in the intensive care unit. These results were in contradiction with results from previously published studies from our team and from others conducted in this setting.27,28,32–34 The authors explained their results by the effect of vasomotor tone on the constant absorption portion of the photoplethysmographic waveform. However, our group of patients was more homogeneous and was studied in a steady-state condition (Figs. 2 and 3), the patients were under deep anesthesia (inducing a decrease in cyclic changes observed in microcirculation35), and were not given any vasoactive drugs. These conditions may strengthen the PVI value. However, because the ΔPP is less affected by vasomotor tone and venous congestion, the area under the ROC curve of ΔPP is better than the area under the curve for PVI. Moreover, this new index will have to be validated in daily clinical practice and may still be improved.36
In this study, we used the 184.108.40.206 version of the PVI software. The new available software (version 220.127.116.11) uses a longer period of smoothing for PVI. Its aim is to decrease the variability of PVI value over time. However, with this newer version, acute changes in loading conditions may have a later effect on PVI value. Future versions of the software should allow users to adjust this parameter.
Finally, these threshold values have been derived retrospectively and will have to be confirmed in prospective studies.
In conclusion, in patients with normal lung function and receiving no inotropes or vasoactive drugs, PVI is able to predict the hemodynamic effects of 10 cm H2O of PEEP in mechanically ventilated patients after cardiac surgery when VT is ≥8 mL/kg. Therefore, PVI may help the physician to optimize the respiratory uptake in oxygen and its delivery to the tissues.
The authors thank Ahmed Ghazouani and Max Cho for editing the language of the manuscript.
1. Magnusson L, Zemgulis V, Wicky S, Tyden H, Thelin S, Hedenstierna G. Atelectasis is a major cause of hypoxemia and shunt after cardiopulmonary bypass: an experimental study. Anesthesiology 1997;87:1153–63
2. Eichenberger A, Proietti S, Wicky S, Frascarolo P, Suter M, Spahn DR, Magnusson L. Morbid obesity and postoperative pulmonary atelectasis: an underestimated problem. Anesth Analg 2002;95:1788–92
3. Duggan M, Kavanagh BP. Pulmonary atelectasis: a pathogenic perioperative entity. Anesthesiology 2005;102:838–54
4. Lawrence VA, Hilsenbeck SG, Mulrow CD, Dhanda R, Sapp J, Page CP. Incidence and hospital stay for cardiac and pulmonary complications after abdominal surgery. J Gen Intern Med 1995;10:671–8
5. Brooks-Brunn JA. Predictors of postoperative pulmonary complications following abdominal surgery. Chest 1997;111:564–71
6. Parlow JL, Ahn R, Milne B. Obesity is a risk factor for failure of “fast track” extubation following coronary artery bypass surgery. Can J Anaesth 2006;53:288–94
7. Tusman G, Böhm SH, Vazquez de Anda GF, do Campo JL, Lachmann B. ‘Alveolar recruitment strategy’ improves arterial oxygenation during general anaesthesia. Br J Anaesth 1999;82:8–13
8. Minkovich L, Djaiani G, Katznelson R, Day F, Fedorko L, Tan J, Carroll J, Cheng D, Karski J. Effects of alveolar recruitment on arterial oxygenation in patients after cardiac surgery: a prospective, randomized, controlled clinical trial. J Cardiothorac Vasc Anesth 2007;21:375–8
9. Claxton BA, Morgan P, McKeague H, Mulpur A, Berridge J. Alveolar recruitment strategy improves arterial oxygenation after cardiopulmonary bypass. Anaesthesia 2003;58:111–6
10. Maisch S, Reissmann H, Fuellekrug B, Weismann D, Rutkowski T, Tusman G, Bohm SH. Compliance and dead space fraction indicate an optimal level of positive end-expiratory pressure after recruitment in anesthetized patients. Anesth Analg 2008;106:175–81
11. Celebi S, Köner O, Menda F, Korkut K, Suzer K, Cakar N. The pulmonary and hemodynamic effects of two different recruitment maneuvers after cardiac surgery. Anesth Analg 2007;104:384–90
12. Cannesson M, Attof Y, Rosamel P, Desebbe O, Joseph P, Metton O, Bastien O, Lehot JJ. Respiratory variations in pulse oximetry plethysmographic waveform amplitude to predict fluid responsiveness in the operating room. Anesthesiology 2007;106:1105–11
13. Michard F. Changes in arterial pressure during mechanical ventilation. Anesthesiology 2005;103:419–28
14. Michard F, Chemla D, Richard C, Wysocki M, Pinsky MR, Lecarpentier Y, Teboul JL. Clinical use of respiratory changes in arterial pulse pressure to monitor the hemodynamic effects of PEEP. Am J Respir Crit Care Med 1999;159:935–9
15. 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;106:1195–200
16. Cannesson M, Desebbe O, Rosamel P, Delannoy B, Robin J, Bastien O, Lehot JJ. Pleth variability index to monitor the respiratory variations in the pulse oximeter plethysmographic waveform amplitude and predict fluid responsiveness in the operating theatre. Br J Anaesth 2008;101:200–6
17. Teboul JL, Besbes M, Andrivet P, Axler O, Douguet D, Zelter M, Lemaire F, Brun-Buisson C. A bedside index assessing the reliability of pulmonary occlusion pressure measurements during mechanical ventilation with positive end-expiratory pressure. J Crit Care 1992;7:22–9
18. Michard F, Boussat S, Chemla D, Anguel N, Mercat A, Lecarpentier Y, Richard C, Pinsky MR, Teboul JL. Relation between respiratory changes in arterial pulse pressure and fluid responsiveness in septic patients with acute circulatory failure. Am J Respir Crit Care Med 2000;162:134–8
19. Balick-Weber CC, Nicolas P, Hedreville-Montout M, Blanchet P, Stéphan F. Respiratory and haemodynamic effects of volume-controlled vs pressure-controlled ventilation during laparoscopy: a cross-over study with echocardiographic assessment. Br J Anaesth 2007;99:429–35
20. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983;148:839–43
21. 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
22. Wiesenack C, Fiegl C, Keyser A, Prasser C, Keyl C. Assessment of fluid responsiveness in mechanically ventilated cardiac surgical patients. Eur J Anaesthesiol 2005;22:658–65
23. 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
24. Marx G, Cope T, McCrossan L, Swaraj S, Cowan C, Mostafa SM, Wenstone R, Leuwer M. Assessing fluid responsiveness by stroke volume variation in mechanically ventilated patients with severe sepsis. Eur J Anaesthesiol 2004;21:132–8
25. Huang CC, Fu JY, Hu HC, Kao KC, Chen NH, Hsieh MJ, Tsai YH. Prediction of fluid responsiveness in acute respiratory distress syndrome patients ventilated with low tidal volume and high positive end-expiratory pressure. Crit Care Med 2008;36:2810–6
26. Solus-Biguenet H, Fleyfel M, Tavernier B, Kipnis E, Onimus J, Robin E, Lebuffe G, Decoene C, Pruvot FR, Vallet B. Non-invasive prediction of fluid responsiveness during major hepatic surgery. Br J Anaesth 2006;97:808–16
27. Feissel M, Teboul JL, Merlani P, Badie J, Faller JP, Bendjelid K. Plethysmographic dynamic indices predict fluid responsiveness in septic ventilated patients. Intensive Care Med 2007;33:993–9
28. Natalini G, Rosano A, Taranto M, Faggian B, Vittorielli E, Bernardini A. Arterial versus plethysmographic dynamic indices to test responsiveness for testing fluid administration in hypotensive patients: a clinical trial. Anesth Analg 2006;103:1478–84
29. Kim HK, Pinsky MR. Effect of tidal volume, sampling duration, and cardiac contractility on pulse pressure and stroke volume variation during positive-pressure ventilation. Crit Care Med 2008;36:2858–62
30. Reisner A, Shaltis PA, McCombie D, Asada HH. Utility of the photoplethysmogram in circulatory monitoring. Anesthesiology 2008;108:950–8
31. 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
32. Cannesson M, Besnard C, Durand PG, Bohé J, Jacques D. Relation between respiratory variations in pulse oximetry plethysmographic waveform amplitude and arterial pulse pressure in ventilated patients. Crit Care 2005;9:R562–8
33. Natalini G, Rosano A, Franceschetti ME, Facchetti P, Bernardini A. Variations in arterial blood pressure and photoplethysmography during mechanical ventilation. Anesth Analg 2006;103:1182–8
34. Wyffels PA, Durnez PJ, Helderweirt J, Stockman WM, De Kegel D. Ventilation-induced plethysmographic variations predict fluid responsiveness in ventilated postoperative cardiac surgery patients. Anesth Analg 2007;105:448–52
35. Landsverk SA, Kvandal P, Bernjak A, Stefanovska A, Kirkeboen KA. The effects of general anesthesia on human skin microcirculation evaluated by wavelet transform. Anesth Analg 2007;105:1012–9
36. Cannesson M, Alian AA, Shelley K. Oscillations in the plethysmographic waveform amplitude: phenomenon hides behind artifacts. Anesthesiology 2009;111:206–7