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Automated system to identify Clostridium difficile infection among hospitalised patients
Journal of Hospital Infection, 08/18/09
Yadava Y et al. – The results were validated using logistic regression with number of days with diarrhoea identified as the most important predictor. Using an electronic data capture technique, number of days of diarrhoea and maximum number of diarrhoea stools in a 24 h time period were able to identify a patient population at high risk for CDI.
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