A biological Bayesian network for prediction of adverse outcome in a population of acutely ill patients triaged in the Emergency Department

Background We know from previous studies that increasing age, abnormal vital signs and abnormal acid-base status are strongly associated with in-hospital mortality in unselected patients admitted acutely to hospital. A model including this information will make us able to explore associations and predict the risk for future patients. Our aim was to describe a Bayesian model for prediction of adverse outcome in the acute ill adult patient admitted to hospital, based on already existing data from the ‘Acute Admission Database’.