Intensive Care Medicine

, Volume 29, Issue 5, pp 727–734 | Cite as

Non-invasive estimation of shunt and ventilation-perfusion mismatch

  • Søren KjaergaardEmail author
  • Stephen Rees
  • Jerzy Malczynski
  • Jørgen Ahrenkiel Nielsen
  • Per Thorgaard
  • Egon Toft
  • Steen Andreassen



To investigate whether parameters describing pulmonary gas exchange (shunt and ventilation-perfusion mismatch) can be estimated consistently by the use of non-invasive data as input to a mathematical model of oxygen transport.


Prospective study.


Investigations were carried out in the post-anaesthesia care unit, coronary care unit, and intensive care unit.


Data from ninety-five patients and six normal subjects were included for the comparison. The clinical situations differed, ranging from healthy subjects to patients with acute respiratory failure in the intensive care unit.


The experimental procedure involved changing the inspired oxygen fraction (FIO2) in 4–6 steps in order to obtain arterial oxygen saturations (SaO2) in the range from 90–100%. This procedure allows plotting a FIO2/SaO2 or FEO2/SaO2 curve, the shape and position of which was quantified using the mathematical model estimating pulmonary shunt and a measure of ventilation-perfusion mismatch (ΔPO2). This procedure was performed using either arterial blood samples at each FIO2 level (invasive approach) or using values from the pulse oximeter (non-invasive approach).

Main results

The model provided good fit to data using both the invasive and non-invasive experimental approach. The parameter estimates were linearly correlated with highly significant correlation coefficients; shuntinvasive vs shuntnon-invasive, r2 = 0.74, P <0.01, and ΔPO2invasive vs ΔPO2non-invasive, r2 = 0.97, P <0.001.


Pulmonary gas exchange can be described equally well using non-invasive data. The simplicity of the non-invasive approach makes the method suitable for large-scale clinical use.


Pulmonary gas exchange Biological models Ventilation-perfusion ratio Physiologic monitoring Oximetry 



This work was partially supported by grants awarded by the Danish Heart Foundation, the Danish Research Academy under the DANVIS program, the Research Foundation for Northern Jutland County, and by the IT-committee under the Danish Technical Research Council.

Supplementary material

134_2003_1708_MOESM1_ESM.pdf (135 kb)
Supplementary material, approximately 138 KB.


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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • Søren Kjaergaard
    • 1
    Email author
  • Stephen Rees
    • 4
  • Jerzy Malczynski
    • 2
  • Jørgen Ahrenkiel Nielsen
    • 1
  • Per Thorgaard
    • 1
  • Egon Toft
    • 2
    • 3
  • Steen Andreassen
    • 4
  1. 1.Department of AnaesthesiologyAalborg Hospital, Aarhus University HospitalsAalborgDenmark
  2. 2.Department of CardiologyAalborg Hospital, Aarhus University HospitalsAalborgDenmark
  3. 3.Department of Health Science and TechnologyAalborg UniversityAalborgDenmark
  4. 4.Centre for Model-Based Medical Decision SupportAalborg UniversityAalborgDenmark

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