Intensive Care Medicine

, 34:2291 | Cite as

Ability of dynamic airway pressure curve profile and elastance for positive end-expiratory pressure titration

  • Alysson R. Carvalho
  • Peter M. Spieth
  • Paolo Pelosi
  • Marcos F. Vidal Melo
  • Thea Koch
  • Frederico C. Jandre
  • Antonio Giannella-Neto
  • Marcelo Gama de AbreuEmail author



To evaluate the ability of three indices derived from the airway pressure curve for titrating positive end-expiratory pressure (PEEP) to minimize mechanical stress while improving lung aeration assessed by computed tomography (CT).


Prospective, experimental study.


University research facilities.


Twelve pigs.


Animals were anesthetized and mechanically ventilated with tidal volume of 7 ml kg−1. In non-injured lungs (n = 6), PEEP was set at 16 cmH2O and stepwise decreased until zero. Acute lung injury was then induced either with oleic acid (n = 6) or surfactant depletion (n = 6). A recruitment maneuver was performed, the PEEP set at 26 cmH2O and decreased stepwise until zero. CT scans were obtained at end-expiratory and end-inspiratory pauses. The elastance of the respiratory system (Ers), the stress index and the percentage of volume-dependent elastance (%E 2) were estimated.

Measurements and main results

In non-injured and injured lungs, the PEEP at which Ers was lowest (8–4 and 16–12 cmH2O, respectively) corresponded to the best compromise between recruitment/hyperinflation. In non-injured lungs, stress index and %E 2 correlated with tidal recruitment and hyperinflation. In injured lungs, stress index and %E 2 suggested overdistension at all PEEP levels, whereas the CT scans evidenced tidal recruitment and hyperinflation simultaneously.


During ventilation with low tidal volumes, Ers seems to be useful for guiding PEEP titration in non-injured and injured lungs, while stress index and %E 2 are useful in non-injured lungs only. Our results suggest that Ers can be superior to the stress index and %E 2 to guide PEEP titration in focal loss of lung aeration.


Acute lung injury Lung protective strategy Ventilator-induced lung injury 



This work was supported by grants from the Brazilian Agencies CNPq and FAPERJ, the Clinic of Anesthesiology of the University Hospital Carl Gustav Carus, Technical University Dresden, Germany and by grant no. HL-086827 from the National Institutes of Health, Bethesda, MA, USA.

Supplementary material

134_2008_1301_MOESM1_ESM.doc (1.2 mb)

Dynamic CT-scan. Tidal inflation-related changes at the hilus region with a PEEP of 0 cmH2O (WMV 6123 kb)

Dynamic CT-scan. Tidal inflation-related changes at the hilus region with a PEEP of 12 cmH2O (WMV 6123 kb)

Dynamic CT-scan. Tidal inflation-related changes at the hilus region with a PEEP of 26 cmH2O (WMV 6123 kb)


  1. 1.
    Ranieri VM, Zhang H, Mascia L, Aubin M, Lin CY, Mullen JB, Grasso S, Binnie M, Volgyesi GA, Eng P, Slutsky AS (2000) Pressure-time curve predicts minimally injurious ventilatory strategy in an isolated rat lung model. Anesthesiology 93:1320–1328PubMedCrossRefGoogle Scholar
  2. 2.
    Grasso S, Stripoli T, De MM, Bruno F, Moschetta M, Angelelli G, Munno I, Ruggiero V, Anaclerio R, Cafarelli A, Driessen B, Fiore T (2007) ARDSnet ventilatory protocol and alveolar hyperinflation: role of positive end-expiratory pressure. Am J Respir Crit Care Med 176:761–767PubMedCrossRefGoogle Scholar
  3. 3.
    Ranieri VM, Giuliani R, Fiore T, Dambrosio M, Milic-Emili J (1994) Volume-pressure curve of the respiratory system predicts effects of PEEP in ARDS: “Occlusion” versus “Constant flow” technique. Am J Respir Crit Care Med 149:19–27PubMedGoogle Scholar
  4. 4.
    Kano S, Lanteri CJ, Duncan AW, Sly PD (1994) Influence of nonlinearities on estimates of respiratory mechanics using multilinear regression analysis. J Appl Physiol 77:1185–1197PubMedGoogle Scholar
  5. 5.
    Bersten AD (1998) Measurement of overinflation by multiple linear regression analysis in patients with acute lung injury. Eur Respir J 12:526–532PubMedCrossRefGoogle Scholar
  6. 6.
    Edibam C, Rutten AJ, Collins DV, Bersten AD (2003) Effect of inspiratory flow pattern and inspiratory to expiratory ratio on nonlinear elastic behavior in patients with acute lung injury. Am J Respir Crit Care Med 167:702–707PubMedCrossRefGoogle Scholar
  7. 7.
    Nève V, De La Roque ED, Leclerc F, Leteurtre S, Dorkenoo A, Sadik A, Cremer R, Logier R (2000) Ventilator-induced overdistension in children: dynamic versus low-flow inflation volume-pressure curves. Am J Respir Crit Care Med 162:139–147PubMedGoogle Scholar
  8. 8.
    Gama de Abreu M, Heintz M, Heller A, Szechenyi R, Albrecht DM, Koch T (2003) One-lung ventilation with high tidal volumes and zero positive end-expiratory pressure is injurious in the isolated rabbit lung model. Anesth Analg 96:220–228PubMedCrossRefGoogle Scholar
  9. 9.
    Carvalho AR, Jandre FC, Pino AV, Bozza FA, Saluh JI, Rodrigues R, Soares JH, Giannella-Neto A (2006) Effects of descending positive end-expiratory pressure on lung mechanics and aeration in healthy anaesthetized piglets. Crit Care 10:R122PubMedCrossRefGoogle Scholar
  10. 10.
    Carvalho AR, Jandre FC, Pino AV, Bozza FA, Salluh JI, Rodrigues R, Ascoli FO, Giannella-Neto A (2007) Positive end-expiratory pressure at minimal respiratory elastance corresponds to the best compromise between mechanical stress and lung aeration in oleic acid-induced lung injury. Crit Care 11:R86PubMedCrossRefGoogle Scholar
  11. 11.
    Suarez-Sipmann F, Bohm SH, Tusman G, Pesch T, Thamm O, Reissmann H, Reske A, Magnusson A, Hedenstierna G (2006) Use of dynamic compliance for open lung positive end-expiratory pressure titration in an experimental study. Crit Care Med 35:214–221CrossRefGoogle Scholar
  12. 12.
    Lachmann B, Robertson B, Vogel J (1980) In vivo lung lavage as an experimental model of the respiratory distress syndrome. Acta Anaesthesiol Scand 24:231–236PubMedCrossRefGoogle Scholar
  13. 13.
    Uhl RR, Lewis FJ (1974) Digital computer calculation of human pulmonary mechanics using a least squares fit technique. Comput Biomed Res 7:489–495PubMedCrossRefGoogle Scholar
  14. 14.
    Malboisson LM, Muller JC, Constantin JM, Lu Qin, Puybasset L, Rouby JJ, The CT Scan ARDS Study Group (2001) Computed tomography assessment of positive end-expiratory pressure-induced alveolar recruitment in patients with acute respiratory distress syndrome. Am J Respir Crit Care Med 163:1444–1450Google Scholar
  15. 15.
    Crotti S, Mascheroni D, Caironi P, Pelosi P, Ronzoni G, Mondino M, Marini JJ, Gattinoni L (2001) Recruitment and derecruitment during acute respiratory failure: a clinical study. Am J Respir Crit Care Med 164:131–140PubMedGoogle Scholar
  16. 16.
    Luecke T, Meinhardt JP, Herrmann P, Weiss A, Quintel M, Pelosi P (2006) Oleic acid vs saline solution lung lavage-induced acute lung injury: effects on lung morphology, pressure-volume relationships, and response to positive end-expiratory pressure. Chest 130:392–401PubMedCrossRefGoogle Scholar
  17. 17.
    Musch G, Bellani G, Vidal Melo MF, Harris RS, Winkler T, Schroeder T, Venegas JG (2007) Relation between shunt, aeration and perfusion in experimental acute lung injury. Am J Respir Crit Care Med 177:292–300PubMedCrossRefGoogle Scholar
  18. 18.
    Hedenstierna G (2003) Alveolar collapse and closure of airways: regular effects of anaesthesia. Clin Physiol Funct Imaging 23:123–129PubMedCrossRefGoogle Scholar
  19. 19.
    Pelosi P, Rocco PR (2007) Airway closure: the silent killer of peripheral airways. Crit Care 11:114PubMedCrossRefGoogle Scholar
  20. 20.
    Pelosi P, D’Andrea L, Vitale G, Pesenti A, Gattinoni L (1994) Vertical gradient of regional lung inflation in adult respiratory distress syndrome. Am J Respir Crit Care Med 149:8–13PubMedGoogle Scholar
  21. 21.
    Puybasset L, Gusman P, Muller JC, Cluzel P, Coriat P, Rouby JJ (2000) Regional distribution of gas and tissue in acute respiratory distress syndrome. III. Consequences for the effects of positive end-expiratory pressure. CT Scan ARDS Study Group. Intensive Care Med 26:1215–1227PubMedCrossRefGoogle Scholar
  22. 22.
    Vieira SR, Puybasset L, Richecoeur J, Lu Q, Cluzel P, Gusman PB, Coriat P, Rouby JJ (1998) A lung computed tomographic assessment of positive end-expiratory pressure-induced lung overdistension. Am J Respir Crit Care Med 158:1571–1577PubMedGoogle Scholar
  23. 23.
    Rouby JJ, Puybasset L, Nieszkowska A, Lu Q (2003) Acute respiratory distress syndrome: lessons from computed tomography of the whole lung. Crit Care Med 31:S285–S295PubMedCrossRefGoogle Scholar
  24. 24.
    Rouby JJ, Lu Q, Vieira S (2003) Pressure/volume curves and lung computed tomography in acute respiratory distress syndrome. Eur Respir J 22:27S–36SCrossRefGoogle Scholar
  25. 25.
    Rouby JJ (2003) Lung overinflation. The hidden face of alveolar recruitment. Anesthesiology 99:2–4PubMedCrossRefGoogle Scholar
  26. 26.
    Grasso S, Terragni P, Mascia L, Fanelli V, Quintel M, Herrmann P, Hedenstierna G, Slutsky AS, Ranieri VM (2004) Airway pressure-time curve profile (stress index) detects tidal recruitment/hyperinflation in experimental acute lung injury. Crit Care Med 32:1018–1027PubMedCrossRefGoogle Scholar
  27. 27.
    Terragni PP, Rosboch GL, Lisi A, Viale AG, Ranieri VM (2003) How respiratory system mechanics may help in minimising ventilator-induced lung injury in ARDS patients. Eur Respir J 22:15S–21SCrossRefGoogle Scholar
  28. 28.
    Nieszkowska A, Lu Q, Vieira S, Elman M, Fetita C, Rouby J-J (2004) Incidence and regional distribution of lung overinflation during mechanical ventilation with positive end-expiratory pressure. Crit Care Med 32:1496–1503PubMedCrossRefGoogle Scholar
  29. 29.
    Puybasset L, Cluzel P, Gusman P, Grenier P, Preteux F, Rouby JJ (2000) Regional distribution of gas and tissue in acute respiratory distress syndrome. I. Consequences for lung morphology. CT Scan ARDS Study Group. Intensive Care Med 26:857–869PubMedCrossRefGoogle Scholar
  30. 30.
    Rouby JJ, Puybasset L, Cluzel P, Richecoeur J, Lu Q, Grenier P (2000) Regional distribution of gas and tissue in acute respiratory distress syndrome. II. Physiological correlations and definition of an ARDS Severity Score. CT Scan ARDS Study Group. Intensive Care Med 26:1046–1056PubMedCrossRefGoogle Scholar
  31. 31.
    Gattinoni L, Caironi P, Cressoni M, Chiumello D, Ranieri VM, Quintel M, Russo S, Patroniti N, Cornejo R, Bugedo G (2006) Lung recruitment in patients with the acute respiratory distress syndrome. N Engl J Med 354:1775–1786PubMedCrossRefGoogle Scholar
  32. 32.
    Gattinoni L, Caironi P, Pelosi P, Goodman LR (2001) What has computed tomography taught us about the acute respiratory distress syndrome? Am J Respir Crit Care Med 164:1701–1711PubMedGoogle Scholar
  33. 33.
    Pelosi P, Cereda M, Foti G, Giacomini M, Pesenti A (1995) Alterations of lung and chest wall mechanics in patients with acute lung injury: effects of positive end-expiratory pressure. Am J Respir Crit Care Med 152:531–537PubMedGoogle Scholar
  34. 34.
    Neumann P, Berglund JE, Mondéjar EF, Magnusson A, Hedenstierna G (1998) Dynamics of lung collapse and recruitment during prolonged breathing in porcine lung injury. J Appl Physiol 85:1533–1543PubMedGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Alysson R. Carvalho
    • 1
    • 2
  • Peter M. Spieth
    • 1
  • Paolo Pelosi
    • 3
  • Marcos F. Vidal Melo
    • 4
  • Thea Koch
    • 1
  • Frederico C. Jandre
    • 2
  • Antonio Giannella-Neto
    • 2
  • Marcelo Gama de Abreu
    • 1
    • 5
    Email author
  1. 1.Clinic of Anesthesiology and Intensive Care Therapy, Medical FacultyUniversity Hospital Carl Gustav CarusDresdenGermany
  2. 2.Program of Biomedical EngineeringCOPPE, Federal University of Rio de JaneiroRio de JaneiroBrazil
  3. 3.Department of Ambient, Health and SafetyUniversity of InsubriaVareseItaly
  4. 4.Department of Anesthesia and Critical CareMassachusetts General Hospital, Harvard Medical SchoolBostonUSA
  5. 5.Pulmonary Engineering Group, Department of Anesthesiology and Intensive Care TherapyUniversity Hospital DresdenDresdenGermany

Personalised recommendations