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Response-time enhancement of a clinical gas analyzer facilitates measurement of breath-by-breath gas exchange
<jats:p> Tidal ventilation gas-exchange models in respiratory physiology and medicine not only require solution of mass balance equations breath-by-breath but also may require within-breath measurements, which are instantaneous functions of time. This demands a degree of temporal resolution and fidelity of integration of gas flow and concentration signals that cannot be provided by most clinical gas analyzers because of their slow response times. We have characterized the step responses of the Datex Ultima (Datex Instrumentation, Helsinki, Finland) gas analyzer to oxygen, carbon dioxide, and nitrous oxide in terms of a Gompertz four-parameter sigmoidal function. By inversion of this function, we were able to reduce the rise times for all these gases almost fivefold, and, by its application to real on-line respiratory gas signals, it is possible to achieve a performance comparable to the fastest mass spectrometers. With the use of this technique, measurements required for non-steady-state and tidal gas-exchange models can be made easily and reliably in the clinical setting. </jats:p>
A method of reconstruction of clinical gas-analyzer signals corrupted by positive-pressure ventilation
<jats:p> The use of sidestream infrared and paramagnetic clinical gas analyzers is widespread in anesthesiology and respiratory medicine. For most clinical applications, these instruments are entirely satisfactory. However, their ability to measure breath-by-breath volumetric gas fluxes, as required for measurement of airway dead space, oxygen uptake, and so on, is usually inferior to that of the mass spectrometer, and this is thought to be due, in part, to their slower response times. We describe how volumetric gas analysis with the Datex Ultima analyzer, although reasonably accurate for spontaneous ventilation, gives very inaccurate results in conditions of positive-pressure ventilation. We show that this problem is a property of the gas sampling system rather than the technique of gas analysis itself. We examine the source of this error and describe how cyclic changes in airway pressure result in variations in the flow rate of the gas within the sampling catheter. This results in the phenomenon of “time distortion,” and the resultant gas concentration signal becomes a nonlinear time series. This corrupted signal cannot be aligned or integrated with the measured flow signal. We describe a method to correct for this effect. With the use of this method, measurements required for breath-by-breath gas-exchange models can be made easily and reliably in the clinical setting. </jats:p>