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Prediction of shock status using open flow approaches with biosensor detection

Objectif

Development of multi-metabolite sensor arrays for measurement of tissue oxygen, glucose, lactate, pyruvate and glutamate during normal and experimental shock states.
Provision of an optimised sampling and monitoring regime yielding real-time diagnostic information.
Determination of dynamic interrelationships as an appropriate index for circulatory shock.
Provision of metabolite transport model for prediction of time related analyte distribution at various tissue locations during normal and injury states.
Establishment of user groups to provide feedback to project on progress with development and to facilitate efforts to identify exploitation partners.

Deprivation of tissue oxygen in the critically ill subject is the root cause of many deaths occurring in hospital. Current techniques for assessment of shock status (measurement of cardiac/respiratory activity, blood pressure, blood gases) are expensive and provide inadequate information preventing early shoch prediction and effective resuscitation. The spearhead of the proposal is to establish the dynamic interrelationships existing between oxygen, glucose, glutamate, lactate and pyruvate during normal and shock states exploiting measured parameters as a tool for generation of a reliable, appropriate index for circulatory shock. Open flow sampling approaches for reproducible metabolite recovery are already in a mature state and established regimens (micro dialysis, ultrafiltration transcutaneous and open micro flow) will be integrated with biosensor end detection for continuous parameter monitoring. Particular emphasis will focus on the lactate: pyruvate ratio which undoubtedly offers a highly specific measure of tissue oxygen but whose analysis has long been hindered by the lack of reliable sensors for pyruvate measurement. This has recently become possible for the first time (pioneered by the coordinating group) and represents a major advance in the ability to predict and titrate shock status.

Derived systems will compare dynamic metabolite relationships at various tissue locations (peripheral, brain and liver tissue) during normal and shock status to target areas most severely affected by tissue hypoxia and to determine optimal monitoring sites for reliable data generation and minimal invasion. Measurements will be critically compared against conventional analytical approaches (via routine blood assay). It is likely that solute diffusion between the flowing blood and gel like tissue matrix may experience a rate transfer imbalance and promote poor correlation between blood and tissue sampling approaches. Therefore to resolve such difficulties a mathematical model of blood-tissue exchange will be developed to assess the kinetcs of analyte transport in normal and hypoxic tissue states with respect to time and space. This will provide a computer model of analyte distribution which could be used for simulation purposes and estimation of real time blood parameters. 03

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Coordinateur

The Victoria University of Manchester
Contribution de l’UE
Aucune donnée
Adresse
Eccles Old Road
M6 8HD Salford
Royaume-Uni

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