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Research Theme

Modernising Medical Microbiology and Big Infection Diagnostics

Home > Research Themes Overview > Modernising Medical Microbiology and Big Infection Diagnostics > Infections in Oxfordshire Research Database > IORD Projects > Contribution of inflammation to infectious and supposedly non-infectious respiratory conditions leading to inpatient admission

IORD Project

Contribution of inflammation to infectious and supposedly non-infectious respiratory conditions leading to inpatient admission

ONGOING
IORD category: Specific Infections
Chief Investigator: Prof Sarah Walker
Sponsor: OUH
Research location: Oxford University
Approval date: 23 Mar 2018

Patients are usually defined by their clinical symptoms, for example pneumonia as opposed to bronchitis or chronic obstructive pulmonary disease (COPD). However, scientists are starting to work out that sometimes the same underlying problem can lead to different clinical presentations. One example is when the body reacts to something, called inflammation. A particular kind of cell which fights some infections, called an eosinophil, can be involved in some types of inflammation. Recent laboratory data suggest that this kind of inflammation could be driving conditions like COPD even though these are not traditionally thought of as being due to infections. Further, these inflammatory processes may only happen in a modest proportion of conditions that are considered likely due to an infection, like pneumonia. We want to see how frequently different lung conditions, other infections and other reasons for admission to Oxford hospitals are associated with different numbers of cells that fight infection. This is a scoping project to see whether more analysis could be helpful in finding ways to work out what is really causing illnesses in patients, and so how they might be treated better.

Modernising Medical Microbiology and Big Infection Diagnostics

  • Modernising Medical Microbiology and Big Infection Diagnostics
  • Sub-theme 1: Novel rapid, high-throughput diagnostic workflows for infection
  • Sub-theme 2: Big data-led infection diagnosis and management strategies
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