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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 > C. difficile recurrence: incidence, predictors and risk scores

IORD Project

C. difficile recurrence: incidence, predictors and risk scores

COMPLETED
IORD category: Specific Pathogens
Chief Investigator: Dr Sarah Walker
Sponsor: OUH
Research location: OUH NHS Trust
Approval date: 14 Sep 2012

This project focusses on patients who do not recover straightaway from C. difficile, but in whom either initial treatment for the infection does not work, or in whom the infection comes back (termed “recurrence” of infection). We want to work how often C. difficile recurrence happens, and how long does this typically take. We will try to find factors that predict patients having a C. difficile recurrence, and will develop a risk score to predict patients at high risk of this outcome which could be used with electronic patient records. We will consider important demographic (age, sex) and hospital-associated factors (speciality, admitted as emergency/elective, admission speciality, duration and type of previous hospital exposure including days since current admission, number of previous admissions, total prior hospital stay, time since last discharged, previous isolation of S. aureus or C. difficile). Separate models will also include results of laboratory tests at the time a diagnosis was made, that may not be available in all individuals, and strain type. The final regression model will be used to develop an integerised risk score.

Summary of findings: 22% of patients surviving 14 days after their first C. difficile infection will go onto to have a recurrence of C. difficile, mostly in the next 4 months. Risk factors, including increasing age, initial disease severity, and hospital exposure, predict CDI recurrence and identify patients likely to benefit from enhanced initial CDI treatment.

See Manuscript on Oxford Journals

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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