Principal Clinical Physicist,
NHS Greater Glasgow & Clyde
School of Medicine, University of Glasgow
Dr Martin Shaw is a Principal Clinical Physicist working for the Department of Clinical Physics and Bioengineering in the Greater Glasgow and Clyde NHS Trust. He is Head of the Anaesthesia Physics section which focuses on finding novel technical solutions to complex clinical problems. He holds degrees in Mathematics and Clinical Physics from the University of Glasgow. His primary research area is in mathematical modelling of cerebral haemodynamics and more specifically cerebral autoregulation. He is one of the co-founders of the cerebral autoregulation network (www.car-net.org), a research group interested in sharing techniques, ideas and data relating to cerebral autoregulation and is on the steering group for the network.
- Mail: Level 2, New Lister Building, Glasgow Royal Infirmary, 10-16 Alexandra Parade, Glasgow, G31 2ER
- Phone: +44 (0)141 201 8626
Current and Recent Projects
CHART-ADAPT: Connecting Healthcare And Research Through A Data Analysis Provisioning Technology
- Aridhia Informatics
- Philips Medical
- University of Glasgow
- NHS Greater Glasgow and Clyde
Head Injury is a devastating injury not only to the victim but also to their carers and to the society that supports their recovery, which is often long term. Unlike other forms of pathology including cancer, stroke or cardiovascular disease, there have been few recently proven effective therapies for brain injury. What is needed is a step-change in approach, one that brings recent advances in big data modelling directly into clinical practice, allows agile development, testing of new interpretations of high-frequency data for improved detection and prediction of clinically relevant and treatable events that occur during their early management in intensive care.
CHART-ADAPT is a two year Innovate UK funded project which brings together leaders in healthcare technology and informatics to collaboratively develop a platform which will enable clinically important physiological models and analyses to be implemented more quickly into clinical practice. The novel platform will empower specialist care providers. It will be capable of extracting high-frequency physiological patient data, analysing it, and then returning the results directly back into clinical practice. This will provide the basis for better treatment and more cost-effective and sustainable healthcare by closing the loop between clinical research and practice.
The platform will be demonstrated in the Neurointensive Care domain. Enabling the analysis of high-frequency data and the implementation of clinically important physiological models will immediately deliver previously unavailable evidence-driven patient care. Hospital treatment of head injury is expensive and the loss of employment to the victim and the stress and increased burden of care to family members has significant social and economic effects. The smallest improvement in the treatment of head injured patients has the potential to generate a huge impact on the social and economic effects of head injury.
Improving Decision Support for Treating Arterial Hypotension in Adult Patients During their Management in Intensive Care
- Dr. Ian Piper, Department of Clinical Physics & Bioengineering, NHS Greater Glasgow & Clyde
- Prof. Chris Williams, School of Informatics, University of Edinburgh
- Prof. Peter Andrews, University of Edinburgh
- Dr. Chris Hawthorne, Department of Anaesthesia, Pain & Critical Care, University of Glasgow
- Prof. John Kinsella, Department of Anaesthesia, Pain & Critical Care, University of Glasgow
Maintaining blood pressure in critically ill patients is a key management goal and yet it is the physiological parameter most prone to error. Studies indicate as much as a third of hypotension (low blood pressure) is missed due to presence of artifact. This project is to develop and validate advanced statistical methods for detection, removal and cleaning of artifact from blood pressure (BP) data. Without these methods any audit or trial of BP therapy will not be accurate. This proposal will develop these methods to interpret data from traumatic brain injury (TBI) and sub-arachnoid haemorrhage (SAH) patients and evaluate them in the neuro-intensive care unit at the Southern General Hospital, Glasgow. The proposal brings together experts in anaesthesia and intensive care with the expertise of Prof Williams' group at Edinburgh in advanced methods (including Factorial Switching Linear Dynamical Systems-FSLDS) for physiological condition monitoring (initially developed in the neonatal ICU).
Remote Positional Monitoring of Critical Care Patients
- Dr. Ian Piper, Department of Clinical Physics & Bioengineering, NHS Greater Glasgow & Clyde
- Dr. Laura Moss, Department of Clinical Physics & Bioengineering, NHS Greater Glasgow & Clyde
- Dr. Chris Hawthorne, Department of Anaesthesia, Pain, & Critical Care, School of Medicine, University of Glasgow
- Prof. DK Arvind, School of Informatics, University of Edinburgh
Non-surgical management of patients with traumatic brain injury is the treatment and prevention of secondary insults such as low cerebral perfusion pressure (CPP). Most clinical pressure monitoring systems measure pressure relative to atmospheric pressure. If a patient is managed with their head tilted up, relative to their arterial pressure transducer, then a hydrostatic pressure gradient (HPG) can act against arterial pressure and cause significant errors in calculated CPP. To correct for HPG, the arterial pressure transducer should be placed level with the ICP transducer. However, this is not always achieved. In our project we have explored the application of Speckled Computing (or ‘specks’) for the automatic monitoring of patient’s head tilt and subsequent automatic calculation of HPG. In future applications this will allow us to automatically correct CPP to take into account any HPG.
- The Association of Anaesthetists of Great Britain and Ireland (£13008)
- Neuroscience Foundation (£800)
- Clinical Physics Research Fund (£6000)
Peer Reviewed Publications
- Emerson, P., McPeake, J., O'Neill, A., Gilmour, H., Forrest, E., Puxty, A., Kinsella, J., Shaw, M. The Utility of Scoring Systems in Critically Ill Cirrhotic Patients Admitted to a General Intensive Care Unit. J Crit Care. 2014 Jul 2. pii: S0883-9441(14)00258-5. doi: 10.1016/j.jcrc.2014.06.027. [Epub ahead of print]
- McPeake, J,M., Shaw, M., O'Neill, A., Forrest, E., Puxty, A., Quasim, T., Kinsella, J. Do alcohol use disorders impact on long term outcomes from intensive care? Crit Care. 2015 Apr 22;19:185. doi: 10.1186/s13054-015-0909-6.
- Shaw, M,, Piper, I., Daley, M. Autoregulatory Model Comparison and Optimisation Methodology. Acta Neurochir Suppl. 2012;114:135-9. doi: 10.1007/978-3-7091-0956-4_25.
- Shaw, M., Piper, I., Campbell, P., McKeown, C., Britton, J., Oommen, K., Stewart, L., Whittle, I., Gregson, R., Clutton, E. Investigation of the Relationship between Transcranial Impedance and Intracranial Pressure. Acta Neurochir Suppl. 2012;114:61-5. doi: 10.1007/978-3-7091-0956-4_11.
- Dani, K.A., Santosh, C., Brennan, D., McCabe, C., Holmes, W.M., Condon, B., Hadley, D.M., Macrae, I.M., Shaw, M., Muir, K.W. T2*-weighted magnetic resonance imaging with hyperoxia in acute ischemic stroke. Ann Neurol. 2010 Jul;68(1):37-47. doi: 10.1002/ana.22032.
- Shaw, M,, Piper, I., BrainIT Group. Pilot application of fractal characterisation and its response to change on physiological wave forms. Acta Neurochir Suppl. 2008;102:229-33.
- Shaw, M,, Piper, I., Daley, M. Relationship of a Cerebral Autoregulatory Index with outcome in Head Injured Patients. Acta Neurochir Suppl. 2008;102:33-6.
- Jack, E.S., Shaw, M, Harten, J.M., Anderson, K., Kinsella, J. Cardiovascular Changes after Achieving Constant Effect Site Concentration of Propofol. Anaesthesia 2008 Feb;63(2):116-20. doi: 10.1111/j.1365-2044.2007.05315.x.
- Shaw, M., Piper, I., Chambers, I., et al. The Brain Monitoring with Information Technology (BrainIT) Collaborative Network: Data Validation Results. Acta Neurochirurgica Supp 2008;102:217-21.
Conference Abstracts and Posters
- Shaw, M., Moss, L., Piper,I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. Improving the performance time of the Pressure Reactivity Index (PRx) model using R and Scala. British Neurosurgical Research Group Meeting 2016, Cambridge, UK, March 2016
- Shaw, M., Moss, L., Piper,I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. Comparison of hypotension burden models in the neuro-intensive care unit. British Neurosurgical Research Group Meeting 2016, Cambridge, UK, March 2016
- Moss, L.,, Shaw, M., Piper,I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. Enabling Big Data Analysis in the Neurointensive Care Unit. British Neurosurgical Research Group Meeting 2016, Cambridge, UK, March 2016
- Moss, L., Shaw, M., Piper, I, and Aridhia. Assessing the Impact of Data Modelling in Real-Time Traumatic Brain Injury Monitoring To Improve Patient Outcomes. Farr Institute International Conference 2015: Data Health Intensive Research and Care, St.Andrews, UK, August 2015.
- Henderson, W., Shaw, M., McLennan, F., Piper, I., Moss, L., Hawthorne, C. Cluster Analysis of the BrainIT Database. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015
- Shaw, M., O'Donnell, A., Piper, I., Moss, L. Down-Sampling Traumatic Brain Injury Physiological Data Using High Performance Computing. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015
- Canty, M., O’Kane, R., Turner, C., Shaw, M., Hawthorne, C., Moss, L., Piper, I. Comparison of 24 Vs 48 Hour ICP Recording for the Detection of metrics for raised ICP in Patients Investigated for CSF circulation abnormalities. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015
- Shaw, M., Hawthorne, C., Moss, L., Piper, I. Improvements to the Optimal Cerebral Perfusion Pressure Calculation. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015
- Moss. L., Corsar, D., Hawthorne, C., Piper, I., Shaw, M., Kinsella, J. Data Quality in Neurointensive Care Datasets. Society of Critical Care Medicine (SCCM) 44th Critical Care Congress, Phoenix, Arizona, USA, January 2015.
- Moss, L., Shaw, M., Piper, I., Arvind, D.K, Automatic Calculation of Hydrostatic Pressure Gradient in Head Injured Patients: A Pilot Study. 15th International Symposium on Intracranial Pressure and Brain Monitoring (ICP 2013), Singapore, November 2013.
- Shaw, M. Automatic Removal of Artifact from Physiological Data in Brain Injured Patients using Factorial Switching Linear Dynamical Systems. ICP 2013 - 15th International Conference on Intracranial Pressure and Brain Monitoring, Singapore, 2013.
- McLennan, F., Hawthorne, C., Shaw, M., Piper, I. Cluster Analysis of the BrainIT Database: A Pilot Study. ICP 2013 - 15th International Conference on Intracranial Pressure and Brain Monitoring, Singapore, 2013.
- Shaw, M. Multi-Resolution Convolution Methodology for ICP Waveform Morphology Analysis. ICP 2013 - 15th International Conference on Intracranial Pressure and Brain Monitoring, Singapore, 2013.
- Shaw, M. Derivation of Cerebral Autoregulatory Indices and Study of its association with Outcome in Head Injured Patients. European Association of Neurological Societies Meeting, Glasgow, UK, 2007.
- Shaw, M. Multi-Fractal Classification of Physiological Time Series and its Reaction To Underlying Change. European Association of Neurological Societies Meeting, Glasgow, UK, 2007.
- Shaw, M. The BrainIT Collaborative Network: Sampling Rates and Summary Measures. ICP 2007 - The 13th International Symposium on Intracranial Pressure and Brain Monitoring, Mechanism & Treatment, San Francisco, USA, May 2007.
- Shaw, M., Piper, I., Chambers, I., et al. The Brain Monitoring with Information Technology (BrainIT) Collaborative Network: Validation Results. ICP 2007 - The 13th International Symposium on Intracranial Pressure and Brain Monitoring, Mechanism & Treatment, San Francisco, USA, May 2007.