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Kadoorie

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Critical care research

Current and research projects from the Critical Care Research Group, who are based at the Kadoorie Centre for Critical Care Research and Education, include the following.

BRC Technology and Digital Health Theme

CAFÉ - a study looking at why some patients develop new onset atrial fibrillation when admitted to ICU and how best to treat them.

C3 - The Short and Long-term Cardiovascular Consequences of Critical Illness (C3 Study) aims to collect data about the care of patients admitted to ICUs and link this data with NHS long-term follow-up data. Using this linked data, we hope to identify the factors that increase patients' long-term risks of heart problems or strokes and identify those patients at highest risk.

FOBS - a project aiming to develop an evidence-based protocol for how frequently vital signs (heart rate, breathing rate, blood pressure, temperature etc) are taken when patients are admitted to hospital.

HAVEN - a hospital-wide project to design and develop an electronic early warning system to identify patients who may need treatment on the intensive care unit.

MOLLIE - Mapping Of Lower Limb skIn pErfusion is a collaborative study between the Critical Care Research Group and the Oxford Biomedical Signal Processing Group. We monitor skin perfusion changes using several types of non-contact cameras.

OPTIC-19 - Outcomes of Patients who survived Treatment on an Intensive Care unit for COVID-19 in England and Wales is a comparative retrospective cohort study. This study will follow up survivors for 1 year after discharge from hospital.

PARADISE - This study will develop two reliable prediction models to identify which patients are at greatest risk of developing Atrial Fibrillation (AF) following heart surgery.

RRAM - routinely collected data to evaluate effects of different medications that prevent blood clotting during treatment to improve kidney function

SHINE - The introduction of SEND to Oxford University Hospitals NHS Foundation Trust has paved the way for real-time and intelligent automated recognition of patients whose observations indicate they may be at increased risk of undiagnosed chronic disease, such as hypertension. SHINE is an observational diagnostic accuracy study.

vHDU - Virtual high-dependency unit. Sometimes in hospital, patients are not detected quickly enough as becoming unwell . This may mean that they are less likely to survive than if the worsening of their illness had been picked up sooner. One reason for this may be that hospital staff are unable to monitor patients' vital signs frequently enough to help them decide if a patient is becoming more unwell.

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