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AVERT-IT Project

Avert-IT is an EU-funded project to develop a mechanism, for use within intensive and high-dependency care units, which will have the ability to monitor and predict the likelihood, and primary causes of arterial adverse hypotension events. The full project title is "Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network" and will run for three years, beginning in January 2008.

Objectives

The main scientific objective of the project is the determination of the weighted association between multiple patient parameters and subsequent arterial hypotension. The association will then be used to define the novel Bayesian neural network, which will be trained against the BrainIT dataset, before undertaking a clinical trial to demonstrate the Avert-IT project concept.

The main technological objective will be the development of an IT-based decision support system ("HypoPredict") appropriate for deployment within intensive and high dependency care units. The system will be capable of:

• Automatically and continually monitoring at least four in-vivo patient parameters (ECG, arterial blood pressure, Oxygen saturation and core temperature), together with open interfaces providing input of key demographic data (age, gender etc.) and periodic data (clinical pathology results etc.) related to the patient.


• Outputting a continuous Hypotension Prediction Index (HPi).


• Providing primary and secondary weighted causal data (current values of input parameters) in parallel with the HPi to facilitate appropriate intervention selection by clinician (for example, elevated core temperature could be indicative of sepsis, a common precursor to hypotension).


• Providing updated HPi, and primary and secondary causal data values, immediately upon any change detected in the patient parameter input set.

Resources

The resources in terms of data, technology and expertise for the project will be combined from a variety of areas:

• Historic patient care data from 22 specialist brain injury units across Europe.


• Grid technologies for secure data access across multiple specialist units and hospitals.


• Baysian Artificial Neural Network (BANN) techniques for analysing data.


• Specialists in treating Traumatic Brain Injury (TBI) from 6 leading hospitals, in Sweden, Germany, Italy, Spain, Lithuania and Scotland.


• C3 Amulet's expertise in device monitoring, data analysis and reporting, and software development, distribution and support.

Outputs

The project will also look to develop an exploitation model for the commercialisation of the software in product/service sales across international markets. For such commercial exploitation, C3 Amulet will have exclusive access to the results of the research. Potential opportunities include:

• Monitoring of intensive care patient treatment


• Clinical trials of both drugs and medical devices


• BANN (Bayesian Artificial Neural Network) techniques for asset performance management and environmental monitoring and control

Contacts

For more information on the AVERT-IT project please contact the commercial manager Steve Reeves (steve.reeves@avertit.info), the technical co-ordinator Ian Piper (ipiper@clinmed.gla.ac.uk) or the overall co-ordinator David Keirs (david.keirs@pera.com).

For all queries relating to the grid technology used please contact Professor Richard Sinnott (r.sinnott@nesc.gla.ac.uk).

Page updated on the 31st March 2008
Maintained by Anthony Stell