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Mathematical modelling to centre low tidal volumes following acute lung injury: A study with biologically variable ventilation

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dc.contributor.author Graham, M R
dc.contributor.author Haberman, Craig J
dc.contributor.author Brewster, John F
dc.contributor.author Girling, Linda G
dc.contributor.author McManus, Bruce M
dc.contributor.author Mutch, W A C
dc.date.accessioned 2016-01-25T21:36:17Z
dc.date.available 2016-01-25T21:36:17Z
dc.date.issued 2005-06-28
dc.identifier.citation Respiratory Research. 2005 Jun 28;6(1):64
dc.identifier.uri http://dx.doi.org/10.1186/1465-9921-6-64
dc.identifier.uri http://hdl.handle.net/1993/31117
dc.description.abstract Abstract Background With biologically variable ventilation [BVV – using a computer-controller to add breath-to-breath variability to respiratory frequency (f) and tidal volume (VT)] gas exchange and respiratory mechanics were compared using the ARDSNet low VT algorithm (Control) versus an approach using mathematical modelling to individually optimise VT at the point of maximal compliance change on the convex portion of the inspiratory pressure-volume (P-V) curve (Experimental). Methods Pigs (n = 22) received pentothal/midazolam anaesthesia, oleic acid lung injury, then inspiratory P-V curve fitting to the four-parameter logistic Venegas equation F(P) = a + b[1 + e -(P-c)/d ]-1 where: a = volume at lower asymptote, b = the vital capacity or the total change in volume between the lower and upper asymptotes, c = pressure at the inflection point and d = index related to linear compliance. Both groups received BVV with gas exchange and respiratory mechanics measured hourly for 5 hrs. Postmortem bronchoalveolar fluid was analysed for interleukin-8 (IL-8). Results All P-V curves fit the Venegas equation (R2 > 0.995). Control VT averaged 7.4 ± 0.4 mL/kg as compared to Experimental 9.5 ± 1.6 mL/kg (range 6.6 – 10.8 mL/kg; p < 0.05). Variable VTs were within the convex portion of the P-V curve. In such circumstances, Jensen's inequality states "if F(P) is a convex function defined on an interval (r, s), and if P is a random variable taking values in (r, s), then the average or expected value (E) of F(P); E(F(P)) > F(E(P))." In both groups the inequality applied, since F(P) defines volume in the Venegas equation and (P) pressure and the range of VTs varied within the convex interval for individual P-V curves. Over 5 hrs, there were no significant differences between groups in minute ventilation, airway pressure, blood gases, haemodynamics, respiratory compliance or IL-8 concentrations. Conclusion No difference between groups is a consequence of BVV occurring on the convex interval for individualised Venegas P-V curves in all experiments irrespective of group. Jensen's inequality provides theoretical proof of why a variable ventilatory approach is advantageous under these circumstances. When using BVV, with VT centred by Venegas P-V curve analysis at the point of maximal compliance change, some leeway in low VT settings beyond ARDSNet protocols may be possible in acute lung injury. This study also shows that in this model, the standard ARDSNet algorithm assures ventilation occurs on the convex portion of the P-V curve.
dc.rights info:eu-repo/semantics/openAccess
dc.title Mathematical modelling to centre low tidal volumes following acute lung injury: A study with biologically variable ventilation
dc.type Journal Article
dc.type info:eu-repo/semantics/article
dc.language.rfc3066 en
dc.rights.holder Graham et al.
dc.date.updated 2016-01-25T17:03:02Z


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