Current evidence for closure of a patent foramen ovale for cryptogenic stroke prevention.

A patent foramen ovale (PFO) has long been implicated as a potential mechanism for cryptogenic stroke (CS), which accounts for up to 40% of all cases of ischaemic stroke. Although there is a strong association between a PFO and CS, there is less evidence that percutaneous closure of the defect, as opposed to medical therapy with antithrombotics or anticoagulants, is the most effective form of secondary prevention. The aim of this review is to examine the evidence comparing percutaneous closure with medical therapy, with a particular focus on three recently published randomised controlled trials.

Use of an artificial neural network to predict length of stay in acute pancreatitis.

Length of stay (LOS) predictions in acute pancreatitis could be used to stratify patients with severe acute pancreatitis, make treatment and resource allocation decisions, and for quality assurance. Artificial neural networks have been used to predict LOS in other conditions but not acute pancreatitis. The hypothesis of this study was that a neural network could predict LOS in patients with acute pancreatitis. The medical records of 195 patients admitted with acute pancreatitis were reviewed. A backpropagation neural network was developed to predict LOS >7 days. The network was trained on 156 randomly selected cases and tested on the remaining 39 cases. The neural network had the highest sensitivity (75%) for predicting LOS >7 days. Ranson criteria had the highest specificity (94%) for making this prediction. All methods incorrectly predicted LOS in two patients with severe acute pancreatitis who died early in their hospital course. An artificial neural network can predict LOS >7 days. The network and traditional prognostic indices were least accurate for predicting LOS in patients with severe acute pancreatitis who died early in their hospital course. The neural network has the advantage of making this prediction using admission data.