Prospective validation and automated generation of clinical scorecards for the assessment of C. difficile infection severity

Principal investigator(s)Co-InvestigatorPhD student or Research Fellow(s)Project title

Professor Ed Keedwell

Dr Steve Michell, Dr Ray Sheridan Dr Diane Fraser, Dr Hossein Mohammadi Prospective validation and automated generation of clinical scorecards for the assessment of C. difficile infection severity

 

Lay summary:

C. difficile is a serious infection that can result in death, particularly in the elderly.  A significant number of people are admitted to hospital with C. difficile infection symptoms.  In previous work we have developed a scorecard of combinations of symptoms and thresholds (e.g. respiratory rate > 17/min) for clinical staff to follow to determine the severity of the disease.  Since creating the scorecard, the RD&E hospital in Exeter have been using it to prioritise treatment for their patients and we propose to analyse this new dataset to determine how effective it has been in determining disease severity. Additionally, we propose to create a new computational tool that will automatically mine clinical data to create new scorecards that will be more accurate than the one we developed previously.  The developed tool could then also be applicable to any disease where suitable clinical dataset exists.



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