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Completed

NCT Number: NCT04297397

Personalised Simulation Technologies for Optimising Treatment in the Intensive Care Unit

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.

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Key information

Age range

18 year–100 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Guys & St. Thomas' NHS Foundation Trust

London, SE1 7EH, United Kingdom

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • At least 18 years of age
  • Patients admitted to GSTFT Intensive Care between the dates 01/01/2010 and 31/03/2019
  • Receiving mechanical ventilation

Exclusion criteria

  • Pregnancy or lactation

Treatment and study plan

Primary outcomes

  1. Development of a simulation platform

    Time frame: 2 years

    Develop predictive physiological models and simulation platform in mechanically ventilated patients with ARDS

Secondary outcomes

  1. Development of dynamic modelling with integration of real time ICU data streams

    Time frame: 2 years

    To integrate data-streams available in the ICU with our existing physiological modelling algorithms to enable real-time simulation of treatment response.

  2. Exploration of therapeutic intervention design space

    Time frame: 2 years

    To develop mathematical methods to explore the "design space" for a clinical support system.

Sponsors and collaborators

Lead sponsor

Guy's and St Thomas' NHS Foundation Trust

Other

Collaborators

  • University of Nottingham
  • University of Warwick

Registry information

Acronym: PSTOTICU

Important dates

Study start
2020
Primary completion
2022
Study completion
2022
First posted
Mar 5, 2020
Registry last updated
Jul 11, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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