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Federating Distributed Clinical Data for the Prediction of Adverse Hypotensive Events. Anthony Stell, National e-Science Centre AHM 2008, Edinburgh, UK. Overview. Adverse hypotensive events Current monitoring systems Avert-IT Project Threshold definitions Avert-IT centre definitions

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federating distributed clinical data for the prediction of adverse hypotensive events

Federating Distributed Clinical Data for the Prediction of Adverse Hypotensive Events

Anthony Stell, National e-Science Centre

AHM 2008, Edinburgh, UK

overview
Overview
  • Adverse hypotensive events
  • Current monitoring systems
  • Avert-IT Project
  • Threshold definitions
    • Avert-IT centre definitions
    • EUSIG definitions
  • Data grid
  • “Hypo-Predict” engine
  • Progress
  • Future work
adverse hypotensive events
Adverse hypotensive events

“Abnormally low blood pressure”

Various numerical definitions:

  • BPs > 100; 5mins
  • BPm > 70; 5mins
  • Etc…
current monitoring systems
Current monitoring systems
  • Odin browser/monitor
    • Database browser of information about secondary insults following head injury
  • BioSign
    • Produces index predicting cardiovascular instability based on several vital signs (Heart rate, respiration rate, etc.)
  • Philips Event Surveillance Monitor
    • Manual correlation of patient parameters into discrete “events”
avert it
Avert-IT

No single system that can predict

the onset of a hypotensive event

over a useful timescale

(e.g. half an hour in advance)

avert it consortium
Avert-IT Consortium

Grant number: FP7-217049

€1,780,000 over 3 years

Technical

  • C3 Amulet, Dingwall, UK
  • National e-Science Centre, Glasgow, UK

Clinical

  • Southern General Hospital, Glasgow, UK
  • Uppsala University Hospital, Sweden
  • University of Heidelberg, Germany
  • Ospedale San Gerardo, Monza, Italy
  • Kaunas University of Technology, Kaunas, Lithuania
  • Universidad Autonoma de Barcelona, Barcelona, Spain
  • Philips Medizin Systeme Boblingen GmbH, Boblingen, Germany

Administration

  • PERA Innovation Ltd, Bellshill, UK
brainit
BrainIT
  • http://www.brainit.org
  • “An internet-based group set up to work collaboratively on standards for the collection and analyses of data from brain-injured patients”
  • Avert-IT builds on the work of BrainIT
    • Many causes of events but naturally focus will be on those related to Traumatic Brain Injury (TBI)…
threshold definitions eusig
Threshold definitions: EUSIG

Edinburgh University Secondary Insult Grade (EUSIG)

data grid 1 architecture
Data grid #1: architecture

Lightweight client at clinical end:

  • Parses output data, packages in SOAP
  • Connects to grid provider through WS

Data grid provider deconstructs

WS and uploads to central repository

End developer connect to this database and use to populate the user interface and the BANN

data grid 2 clinical end points
Data grid #2: clinical end-points
  • Many different formats:
    • Philips DocVu (ASCII text)
    • BrainIT (Access database)
    • CMA ICU Pilot (XML)
    • Health-Level 7 (HL7)
  • Parameters used so far:
    • Blood pressure (BPs, BPd, BPm)
    • Intra-cranial pressure (ICPm)
    • Cerebral perfusion pressure (CPP)
    • Heart rate (HRT)
    • Temperature (TC)
    • Blood oxygen saturation (SaO2/SpO2)
data grid 3 security and performance
Data grid #3: security and performance
  • Security
    • Encryption of data in transit and at rest
    • Locally linked patient identifiers
      • Contextual demographic information…
      • Episodic activity could allow inference…
    • Need feedback mechanism to capture consent
  • Performance
    • Database optimisation
      • Records for a single patient over 2 days number ~8000 for BrainIT, ~6000 for ICU-Pilot
      • Need smart storage solutions
    • WS thresholds
      • May need other connection options?
hypo predict engine
Hypo-Predict engine
  • Decision support tools
    • Look-up tables, case-based reasoning (CBR), genetic algorithms (GA), Bayesian belief networks (BBN), artificial neural networks (ANN)
  • Bayesian approach to ANN (BANN)
    • Accounts for probabilities of causative effects
    • Experience within BrainIT of setting up BANNs
      • Tim Howells (Uppsala), author of Odin software
  • Train the Hypo-Predict engine on unified data
    • … then turn into a product and give to individual centres.
progress
Progress
  • Clinical research
    • Threshold definition agreed upon (< 90;5mins)
    • Parameter list for data established
  • Implementation
    • Parsers for four out of the seven clinical sources
      • BrainIT, Glasgow, Heidelberg, Monza
    • Connections established between end-developers (C3) and data grid provider (NeSC-Glasgow) using JDBC
    • User interface prototypes developed
future work
Future work
  • Distribute parsers and automate WS connections/uploads (subject to validation)
    • Involves negotiating with sysadmins at various clinical centres => takes ages…
  • Development of the BANN on the data available:
    • BrainIT database already available
    • Example sources available for centres already parsed (still awaiting full, real-time data)
  • Consent capture loop to be implemented
  • Dissemination of work and Hypo-Predict product
avert it resources
Avert-IT Resources
  • Website – http://www.avert-it.org
  • Wiki – http://wiki.avert-it.org/wordpress
  • Dissemination
    • Wiki - http://frontofficebox.com/knowledgebase/index.php?title=Avert-IT_Portal
    • Blog – http://avertit.wordpress.com
    • Network – http://avertit.ning.com
  • Contact
    • Steve Reeves (C3 Amulet)
    • Ian Piper (Southern General Hospital)
    • David Keirs (PERA)
    • Richard Sinnott, Anthony Stell, Jipu Jiang (NeSC)
demonstration
Demonstration
  • At 10.05am on Thursday morning
    • Avert-IT
    • EuroDSD
    • VOTES / Vanguard
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