Abstract
SummaryMeasurement allows us to quantify various parameters and variables in natural systems. In addition, by measuring the effect by which a perturbation of one part of the system influences the system as a whole, insights into the functional mechanisms of the system can be inferred. Clinical monitoring has a different role to that of scientific measurement. Monitoring describes measurements whose prime purpose is not to give insights into underlying mechanisms, but to provide information to ‘warn’ of imminent events. What is often more important is the description of trends in measured variables. In this article, we give some examples ‐ focussed around oxygen sensors ‐ of how new sensors can make important measurements and might in the future contribute to improved clinical management.
Highlights
Terragni et al showed in human patients imaged with CT, that those in whom tidal ventilation was predominantly distributed to hyperaerated lung regions showed a greater inflammatory response – as measured by pulmonary cytokine concentrations – than those in whom tidal ventilation was predominantly distributed to normally aerated lung [15]
If we propose that in ARDS/acute lung injury, the PaO2 oscillations are due to cyclical changes in shunt fraction resulting from cyclical recruitment/ derecruitment, theoretical modelling predicts that the PaO2 oscillation amplitude would vary as FIO2 varies
Rapid PaO2 sensing by a small plastic fibre-optic sensor capable of being inserted into a standard arterial cannula, has the potential to change the way clinicians understand disordered gas exchange in patients with lung injury
Summary
Measurement allows us to quantify various parameters and variables in natural systems. The accuracy of data from clinical monitors is usually less important than those of similar scientific instruments. This is mostly because patient variables almost always have more intrinsic variability, so in a measurement snapshot, we have no way of knowing, a priori, whether the measured value deviates from an expected result because of measurement inaccuracy, measurement imprecision, patient variability or patient abnormality. It is axiomatic that trends become more readily apparent if the variance attributable to the instrument is minimum (i.e. the measurements are precise) Anaesthesia and critical care have seen monitoring fashions come and go In these environments, we tend to want to believe in the importance of the variables we can measure, but do not give much consideration to those we cannot. We give some examples of how new sensors can make important measurements that might challenge the accepted wisdom, and might in the future contribute to improved clinical management
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