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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 > The prognostic utility of the MeMed COVID-19 Severity™ assay in patients with COVID-19 at Oxford University Hospitals NHS Foundation Trust (OUH)

IORD Project

The prognostic utility of the MeMed COVID-19 Severity™ assay in patients with COVID-19 at Oxford University Hospitals NHS Foundation Trust (OUH)

ONGOING
IORD category: COVID-19
Chief Investigator: Dr Alexander Mentzer, Dr James Fullerton
Sponsor: OUH
Research location: Oxford University
Approval date: 24 Jan 2022

COVID-19 caused by SARS-CoV2, remains a significant cause of hospital attendance, admission and mortality. The clinical presentation of COVID-19 is variable, with most patients experiencing mild self-limiting symptoms, while others progress to respiratory failure. The use of biomarkers early in the disease course, to predict the development of severe disease, has garnered significant interest as a guide to permit appropriate intervention and decision making regarding the setting of care. The MeMed COVID-19 Severity™ assay is a point of care assay based upon the host response. Quantifying and integrating serum concentrations of tumour necrosis factor-related apoptosis inducing-ligand (TRAIL), interferon gamma-induced protein 10 (IP-10) and C-reactive protein (CRP) via a proprietary algorithm, a numerical score from 0-100 (0 representing a low likelihood of severe outcome and 100 a high likelihood) is generated. We have set up a workflow to perform this assay in individuals presenting with PCR-confirmed COVID-19 disease. The results are stored on the biochemistry LIMS system, with clinicians blinded to the results. We propose to extract clinical data linked to these measures using the IORD structure and test whether admission MeMed COVID-19 Severity™ score is a predictor of deterioration independent of current clinical or biochemical predictors.

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
  • Infections in Oxfordshire Research Database (IORD)
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