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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.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Inspiwave | Device | patients are monitored with the Inspiwave device. A low dose inert tracer gas is added to the inspred air |
| Measure | Description | Time Frame |
|---|---|---|
| Production 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. | Sept 2020 |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | Sept 2020 |
| Signal:noise ratio of measured data. |
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Inclusion Criteria:
Exclusion Criteria:
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-mechanically ventilated patients in a critical care area
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Andrew D Farmery, MD | Contact | +441865231420 | andrew.farmery@nda.ox.ac.uk | |
| Heather House | Contact | +441865572242 | ouhtma@ouh.nhs.uk |
| Name | Affiliation | Role |
|---|---|---|
| Andrew D Farmery, MD | heather.house@admin.ox.ac.uk | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Oxford University Hospitals NHS Foundation Trust | Recruiting | Oxford | United Kingdom |
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| ID | Term |
|---|---|
| D012128 | Respiratory Distress Syndrome |
| D016638 | Critical Illness |
| ID | Term |
|---|---|
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D012120 | Respiration Disorders |
| D020969 | Disease Attributes |
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If values for effective lung volume and pulmonary blood flow can be produced, are these with adequate signal:noise ratio to allow inverse modelling.
| Sept 2020 |
| D010335 |
| Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |