Literature DB >> 8339795

Modelling of passive expiration in patients with adult respiratory distress syndrome.

G L Chelucci1, J Dall' Ava-Santucci, J F Dhainaut, A Chelucci, A Allegra, D Paccaly, F Brunet, J Milic-Emili, A Lockhart.   

Abstract

The time-course of volume change during passive expiration preceded by an end-inspiratory hold was studied with a biexponential model in six adult respiratory distress syndrome (ARDS) patients. We measured the initial volumes and time constants of the fast (tau 1), and the slow (tau 2) compartments of expiration, as well as the static elastance of the respiratory system. The results were compared to those of 11 normal subjects. We observed that: 1) the biexponential model fitted closely the volume decay; 2) the fast compartment was responsible for 81 +/- 7% (ARDS) versus 84 +/- 10% (controls) of the total volume exhaled, with tau 1 = 0.35 +/- 0.11 s (ARDS) versus 0.50 +/- 0.22 s (controls); 3) the slow compartment contributed only 19 +/- 6% (ARDS) versus 16 +/- 7% (controls), with tau 2 = 4.67 +/- 2.38 s (ARDS) versus 3.27 +/- 1.54 s (controls); and 4) static elastance was higher in ARDS patients. The findings could be explained in terms of a four parameter viscoelastic model of the respiratory system.

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Year:  1993        PMID: 8339795

Source DB:  PubMed          Journal:  Eur Respir J        ISSN: 0903-1936            Impact factor:   16.671


  5 in total

Review 1.  As simple as possible, but not simpler.

Authors:  A Rossi; G Polese
Journal:  Intensive Care Med       Date:  2000-11       Impact factor: 17.440

2.  Determination of rate-constants as a method to describe passive expiration.

Authors:  Fabrizio Locchi; Gian-Luca Chelucci; Walter Araujo Zin
Journal:  Eur J Appl Physiol       Date:  2003-08-05       Impact factor: 3.078

3.  Turn the ARDS patient prone to improve oxygenation and decrease risk of lung injury.

Authors:  Antonia Koutsoukou
Journal:  Intensive Care Med       Date:  2004-12-18       Impact factor: 17.440

4.  Expiratory model-based method to monitor ARDS disease state.

Authors:  Erwin J van Drunen; Yeong Shiong Chiew; J Geoffrey Chase; Geoffrey M Shaw; Bernard Lambermont; Nathalie Janssen; Nor Salwa Damanhuri; Thomas Desaive
Journal:  Biomed Eng Online       Date:  2013-06-26       Impact factor: 2.819

5.  Analysis of forced expired volume signals using multi-exponential functions.

Authors:  H Steltner; M Vogel; S Sorichter; H Matthys; J Guttmann; J Timmer
Journal:  Med Biol Eng Comput       Date:  2001-03       Impact factor: 3.079

  5 in total

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