This is a feasibility study of the use of a novel technique called 'Inspiwave' to measure heart and lung function in adult patients in critical care. The preliminary work has already been undertaken in animal models and in healthy volunteers. The ultimate aim of this study is to develop a clinical tool for measuring (and therefore being able to make treatment changes based on) indices of heart and lung function in critical care patients. This study is the first assessment of the technique in this population, and whilst we know it works in patients undergoing general anaesthesia, we now need to assess whether Inspiwave can be used at all in critical care patients who may have much more physiological derangement. The purpose of this phase of the research is to determine whether it is feasible to use Inspiwave in critical care. Inspiwave generates a sinusoidally modulated tracer gas signal in the inspired air. It also measures the resulting signal in the expired air. The unique handling of this signal by the patient can used be to derive key variables related to cardiopulmonary function such as lung volume, pulmonary blood flow, the deadspace (wasted ventilation) and the degree to which ventilation and blood flow are non-uniform. These are 'vital signs' in sick patients, yet are currently technically difficult to measure, particularly non-invasively.
Study Type
OBSERVATIONAL
Enrollment
80
patients are monitored with the Inspiwave device. A low dose inert tracer gas is added to the inspred air
Oxford University Hospitals NHS Foundation Trust
Oxford, United Kingdom
RECRUITINGProduction of any numerical values of effective lung volume and pulmonary blood flow
We wish to know whether the technique can be applied, and whether the signal to noise ratio allows computation of the variables of interest. It is yet unclear whether or not the device can operate in a critical care environment.
Time frame: Sept 2020
Comparison of measurements of effective lung volume and pulmonary blood flow under changes in observed clinical condition.
To observe if changes in clinical condition can be detected by the device.
Time frame: Sept 2020
Signal:noise ratio of measured data.
If values for effective lung volume and pulmonary blood flow can be produced, are these with adequate signal:noise ratio to allow inverse modelling.
Time frame: Sept 2020
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