Personalised Simulation Technologies for Optimising Treatment in the Intensive Care Unit
Condition: Respiratory Distress Syndrome, Adult; Respiratory Insufficiency
MeSH terms: Respiratory Distress Syndrome; Respiratory Distress Syndrome, Newborn; Respiratory Insufficiency; Acute Lung Injury
Study type: Observational

Summary: 
      This project aims to develop software models describing how critically ill patients respond
      to changes in their treatment whilst admitted to an Intensive Care Unit (ICU). We will use
      high performance computers to fit software models to the physiological and treatment data of
      patients receiving mechanical ventilation.
    

Detailed description: 
      In the United Kingdom, approximately 142,000 people are admitted to ICU each year. A large
      proportion, 10 - 20%, of these patients have a life-threatening respiratory illness called
      Acute Respiratory Distress Syndrome (ARDS). These patients need specialist help with their
      breathing, from a machine called a ventilator. Only seven out of ten patients will survive
      this illness and even survival may bring ongoing problems, sometimes for a long time after
      leaving hospital.

      Accurate mathematical and computer models of ARDS, would allow investigation of the illness
      outside of the ICU and inside the virtual environment of a computer. Different treatments
      could be simulated on the same 'virtual' patient, or the same treatment on many different
      patients with varying degrees of illness.

      Development of these software models, requires collection of a library of data describing how
      patients respond to changes in their treatment. An example would be to describe how a
      patient's blood pressure responds to a change in the settings of their ventilator. The
      changes to a patient's ventilation would be made as part of the normal care provided by the
      doctors and nurses looking after them.

      Mathematical descriptions have been created before, from simpler data sets which were
      essentially single snapshots of a patient's condition and treatment. The investigators aim to
      capture sequences of snapshots over several hours, allowing them to build more accurate
      models.

      Guy's and St Thomas' NHS Foundation Trust (GSTFT) is the clinical partner of the project.
      Patients would be identified there by clinical researchers, who would then collect the data
      describing their treatment. This data would be anonymised before adding to the library of
      data to be shared with academic researchers.

      Academic members of the team at the University of Warwick and the University of Nottingham
      possess the engineering and mathematical expertise needed to develop the complex software
      models. They also provide the facility of a high performance computing cluster necessary for
      the difficult process of fitting models to the data.

      Once the software models have been built and used to examine the how treatment might be
      improved, the findings would be shared with clinical staff around the world, through the
      publication of articles in medical journals. It is possible that the insights gained by the
      modelling process might inform, change and improve how clinical staff use ventilators to
      support patients with ARDS.
    

Observational model: Case-Only
Time perspective: Retrospective
Sampling method: Non-Probability Sample
Study population: 
        Subjects will be drawn from the adult critical care population at GSTFT. Subjects of
        interest are those receiving mechanical ventilation.
      
Keywords: ICU; Patient Simulation; Critical Care; ARDS; Mechanical Ventilation