Intensive Care Medicine

, Volume 36, Issue 11, pp 1875–1881 | Cite as

Fluid responsiveness predicted by noninvasive Bioreactance-based passive leg raise test

  • Brahim Benomar
  • Alexandre Ouattara
  • Philippe Estagnasie
  • Alain Brusset
  • Pierre Squara



To study the feasibility of predicting fluid responsiveness (FR) by passive leg raising (PLR) using a Bioreactance-based noninvasive cardiac output monitoring device (NICOM).


This prospective, two-center study included 75 consecutive intensive care unit (ICU) adult patients immediately after cardiac surgery. NICOM was used to continuously record cardiac output (CO) at baseline, during a PLR, and then during a 500 ml i.v. rapid colloid infusion. We estimated the precision of NICOM at baseline to derive the least minimum significant change (LMSC) in CO. We studied the predictability of PLR for FR by systematic analysis of different categorizations of PLR and FR, based on percentage change in CO (from 0 to 20%).


The LMSC was 8.85%. CO was 4.17 ± 1.04 L min−1 at baseline, 4.38 ± 1.14 L min−1 during PLR, 4.16 ± 1.08 L min−1 upon return to baseline, and 4.85 ± 1.41 L min−1 after fluid infusion. The change in CO following fluid bolus was highly correlated with the change in CO following PLR: y = 0.91x + 4.3, r = 0.77. The Pearson correlation coefficient showed that the best pair of thresholds was found for PLR ≥0% predicting FR ≥0%. Using this pair of thresholds, PLR had 88% sensitivity and 100% specificity for predicting FR. When we restricted the analysis to change in CO > LMSC, the best pair of thresholds was obtained for PLR >9% predicting FR >9%. Using this pair of thresholds, PLR sensitivity was reduced to 68% and specificity to 95%.


In this specific population of patients, it is clinically valid to use the bioreactance-based NICOM system to predict FR from changes in CO during PLR.


Cardiac output Monitoring Fluid response 



The authors thank Steve Novak for his help in collecting data. Cheetah-Medical gave for free the NICOM devices and the consumable.

Conflict of interest

Pierre Squara is a consultant for Cheetah-Medical. Other authors have no conflicts of interest.

Supplementary material

134_2010_1990_MOESM1_ESM.doc (261 kb)
(DOC 261 kb)


  1. 1.
    Shoemaker W, Appel P, Kram H, Waxman K, Lee T (1988) Prospective trial of supranormal values of survivors as therapeutic goals in high-risk surgical patients. Chest 94:1176–1186CrossRefPubMedGoogle Scholar
  2. 2.
    Boyd O, Grounds RM, Bennett ED (1993) A randomized clinical trial of the effect of deliberate perioperative increase of oxygen delivery on mortality in high-risk surgical patients. JAMA 270:2699–2707CrossRefPubMedGoogle Scholar
  3. 3.
    Lobo SM, Lobo FR, Polachini CA, Patini DS, Yamamoto AE, de Oliveira NE, Serrano P, Sanches HS, Spegiorin MA, Queiroz MM, Christiano AC Jr, Savieiro EF, Alvarez PA, Teixeira SP, Cunrath GS (2006) Prospective, randomized trial comparing fluids and dobutamine optimization of oxygen delivery in high-risk surgical patients. Crit Care 10:R72CrossRefPubMedGoogle Scholar
  4. 4.
    Joshi GP (2005) Intraoperative fluid restriction improves outcome after major elective gastrointestinal surgery. Anesth Analg 101:601–605CrossRefPubMedGoogle Scholar
  5. 5.
    Martinez EA, Pronovost P (2002) Perioperative beta-blockers in high-risk patients. J Crit Care 17:105–113CrossRefPubMedGoogle Scholar
  6. 6.
    Squara P, Dhainaut J, Lamy M, Perret C, Larbuisson R, Poli S, Armaganidis A, de Gournay J, Bleichner G (1989) Computer assistance for hemodynamic evaluation. J Crit Care 4:273–282CrossRefGoogle Scholar
  7. 7.
    Chytra I, Pradl R, Bosman R, Pelnar P, Kasal E, Zidkova A (2007) Esophageal Doppler-guided fluid management decreases blood lactate levels in multiple-trauma patients: a randomized controlled trial. Crit Care 11:R24CrossRefPubMedGoogle Scholar
  8. 8.
    Sinclair S, James S, Singer M (1997) Intraoperative intravascular volume optimisation and length of hospital stay after repair of proximal femoral fracture: randomised controlled trial. BMJ 315:909–912PubMedGoogle Scholar
  9. 9.
    Phan T, Ismail H, Heriot A, Ho K (2008) Improving perioperative outcomes: fluid optimization with the esophageal Doppler monitor, a metaanalysis and review. J Am Coll Surg 207:935–941CrossRefPubMedGoogle Scholar
  10. 10.
    Stewart R, Park P, Hunt J, McIntyre RJ, McCarthy J, Zarzabal L, Michalek J (2009) Less is more: improved outcomes in surgical patients with conservative fluid administration and central venous catheter monitoring. J Am Coll Surg 208:725–735; discussion 735–727CrossRefPubMedGoogle Scholar
  11. 11.
    Wiedemann H, Wheeler A, Bernard G, Thompson B, Hayden D, deBoisblanc B, Connors AJ, Hite R, Harabin A (2006) Comparison of two fluid-management strategies in acute lung injury. N Engl J Med 354:2564–2575CrossRefPubMedGoogle Scholar
  12. 12.
    Lafanechere A, Pene F, Goulenok C, Goulenok C, Delahaye A, Mallet V, Choukroun G, Chiche J, Mira J, Cariou A (2006) Changes in aortic blood flow induced by passive leg raising predict fluid responsiveness in critically ill patients. Crit Care 10:R132CrossRefPubMedGoogle Scholar
  13. 13.
    Monnet X, Teboul J (2008) Passive leg raising. Intensive Care Med 34:659–663CrossRefPubMedGoogle Scholar
  14. 14.
    Teboul J, Monnet X (2008) Prediction of volume responsiveness in critically ill patients with spontaneous breathing activity. Curr Opin Crit Care 14:334–339CrossRefPubMedGoogle Scholar
  15. 15.
    Caille V, Jabot J, Belliard G, Charron C, Jardin F, Vieillard-Baron A (2008) Hemodynamic effects of passive leg raising: an echocardiographic study in patients with shock. Intensive Care Med 34:1239–1245CrossRefPubMedGoogle Scholar
  16. 16.
    Monnet X, Rienzo M, Osman D, Anguel N, Richard C, Pinsky MR, Teboul JL (2006) Passive leg raising predicts fluid responsiveness in the critically ill. Crit Care Med 34:1402–1407CrossRefPubMedGoogle Scholar
  17. 17.
    Lamia B, Ochagavia A, Monnet X, Chemla D, Richard C, Teboul JL (2007) Echocardiographic prediction of volume responsiveness in critically ill patients with spontaneously breathing activity. Intensive Care Med 33:1125–1132CrossRefPubMedGoogle Scholar
  18. 18.
    Cecconi M, Rhodes A, Poloniecki J, Della Rocca G, Grounds R (2009) Bench-to-bedside review: The importance of the precision of the reference technique in method comparison studies: with specific reference to the measurement of cardiac output. Crit Care 13:201CrossRefPubMedGoogle Scholar
  19. 19.
    Jabot J, Teboul J, Richard C, Monnet X (2009) Passive leg raising for predicting fluid responsiveness: importance of the postural change. Intensive Care Med 35:85–90CrossRefPubMedGoogle Scholar
  20. 20.
    Bundgaard-Nielsen M, Holte K, Secher N, Kehlet H (2007) Monitoring of peri-operative fluid administration by individualized goal-directed therapy. Acta Anaesthesiol Scand 51:331–340CrossRefPubMedGoogle Scholar
  21. 21.
    Marqué S, Cariou A, Chiche J, Squara P (2009) Non invasive cardiac output monitoring (NICOM) compared to minimally invasive monitoring (VIGILEO). Crit Care 13:R73CrossRefPubMedGoogle Scholar
  22. 22.
    Raval N, Squara P, Cleman M, Yalamanchili K, Winklmaier M, Burkhoff D (2008) Multicenter evaluation of noninvasive cardiac output measurement by bioreactance technique. J Clin Monit Comput 10:113–119CrossRefGoogle Scholar
  23. 23.
    Squara P, Denjean D, Estagnasie P, Brusset A, Dib JC, Dubois C (2007) Noninvasive cardiac output monitoring (NICOM): a clinical validation. Intensive Care Med 33:1191–1194CrossRefPubMedGoogle Scholar
  24. 24.
    Squara P, Rotcajg D, Denjean D, Estagnasie P, Brusset A (2009) Comparison of monitoring performance of Bioreactance vs. pulse contour during lung recruitment maneuvers. Crit Care 13:125CrossRefGoogle Scholar
  25. 25.
    Squara P, Fourquet E, Jacquet L, Broccard A, Uhlig T, Rhodes A, Bakker J, Perret C (2003) A computer program for interpreting pulmonary artery catheterization data: results of the European HEMODYN Resident Study. Intensive Care Med 29:735–741PubMedGoogle Scholar
  26. 26.
    Squara P (2008) Bioreactance, a new method for non invasive cardiac output monitoring. In: Vincent J (ed) Year book of intensive care and emergency medicine. Springer, Paris, pp 619–630CrossRefGoogle Scholar
  27. 27.
    Parsonnet V, Bernstein A, Gera M (1996) Clinical usefulness of risk-stratified outcome analysis in cardiac surgery in New Jersey. Ann Thorac Surg 61:S8–11CrossRefPubMedGoogle Scholar
  28. 28.
    Nilsson J, Algotsson L, Höglund P, Lührs C, Brandt J (2004) EuroSCORE predicts intensive care unit stay and costs of open heart surgery. Ann Thorac Surg 78:1528–1534CrossRefPubMedGoogle Scholar
  29. 29.
    Trof R, Sukul S, Twisk J, Girbes A, Groeneveld A (2010) Greater cardiac response of colloid than saline fluid loading in septic and non-septic critically ill patients with clinical hypovolaemia. Intensive Care Med 36:697–701CrossRefPubMedGoogle Scholar
  30. 30.
    Squara P, Cecconi C, Singer M, Rhodes A, Chiche J (2009) Tracking changes in cardiac output; methodological considerations for the validation of monitoring devices. Intensive Care Med 35:1801–1808CrossRefPubMedGoogle Scholar
  31. 31.
    Baldi P, Brunak S, Chauvin Y, Andersen C, Nielsen H (2000) Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 16:412–424CrossRefPubMedGoogle Scholar
  32. 32.
    Della Rocca G, Costa M (2004) Hemodynamic-volumetric monitoring. Minerva Anesthesiol 70:229–232Google Scholar
  33. 33.
    McGee W (2009) A simple physiologic algorithm for managing hemodynamics using stroke volume and stroke volume variation: physiologic optimization program. J Intensive Care Med 24:352–360CrossRefPubMedGoogle Scholar
  34. 34.
    Muller L, Louart G, Bousquet P, Candela D, Zoric L, de La Coussaye J, Jaber S, Lefrant J (2010) The influence of the airway driving pressure on pulsed pressure variation as a predictor of fluid responsiveness. Intensive Care Med 36:496–503CrossRefPubMedGoogle Scholar
  35. 35.
    Greene A, Shoukas A (1986) Changes in canine cardiac function and venous return curves by the carotid baroreflex. Am J Physiol 25:1288–1296Google Scholar
  36. 36.
    Takata M, Wise R, Robotham J (1990) Effects of abdominal pressure on venous return: abdominal vascular zone conditions. J Appl Physiol 69:1961–1972PubMedGoogle Scholar
  37. 37.
    Kitano Y, Takata M, Sasaki N, Zhang Q, Yamamoto S, Miyasaka K (1999) Influence of increased abdominal pressure on steady-state cardiac performance. J Appl Physiol 86:1651–1656PubMedGoogle Scholar
  38. 38.
    Fessler H, Brower R, Shapiro E, Permutt S (1993) Effects of positive end-expiratory pressure and body position on pressure in the thoracic great veins. Am Rev Respir Dis 148:1657–1664PubMedGoogle Scholar
  39. 39.
    Cecconi M, Dawson D, Grounds R, Rhodes A (2009) Lithium dilution cardiac output measurement in the critically ill patient: determination of precision of the technique. Intensive Care Med 35:498–504CrossRefPubMedGoogle Scholar
  40. 40.
    Lakhal K, Ehrmann S, Runge I, Benzekri-Lefevre D, Legras A, Dequin P, Mercie rE, Wolff M, Regnier B, Boulain T (2010) Central venous pressure measurements improve the accuracy of leg raising-induced change in pulse pressure to predict fluid responsiveness. Intensive Care Med 36:940–948CrossRefPubMedGoogle Scholar

Copyright information

© Copyright jointly held by Springer and ESICM 2010

Authors and Affiliations

  • Brahim Benomar
    • 1
  • Alexandre Ouattara
    • 2
  • Philippe Estagnasie
    • 3
  • Alain Brusset
    • 3
  • Pierre Squara
    • 3
  1. 1.Département d’anesthésie-RéanimationGH Pitié-Salpêtrière, Assistance Publique Hôpitaux de Paris (AP-HP)ParisFrance
  2. 2.Service d’anesthésie-RéanimationGroupe Hospitalier Sud, Avenue de MagellanPESSACFrance
  3. 3.Réanimation, Clinique Ambroise ParéNeuilly-sur-SeineFrance

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