Trends in Socioeconomic Inequalities in Ischemic Heart Disease Mortality in Small Areas of Nine Spanish Cities from 1996 to 2007 Using Smoothed ANOVA

The aim of this study was to analyze the evolution of socioeconomic inequalities in mortality due to ischemic heart diseases (IHD) in the census tracts of nine Spanish cities between the periods 1996–2001 and 2002–2007. Among women, there are socioeconomic inequalities in IHD mortality in the first period which tended to remain stable or even increase in the second period in most of the cities. Among men, in general, no socioeconomic inequalities have been detected for this cause in either of the periods. These results highlight the importance of intra-urban inequalities in mortality due to IHD and their evolution over time.

Aid decision algorithms to estimate the risk in congenital heart surgery

Background and objective: In this paper, we have tested the suitability of using different artificial intelligence-based algorithms for decision support when classifying the risk of congenital heart surgery. In this sense, classification of those surgical risks provides enormous benefits as the a priori estimation of surgical outcomes depending on either the type of disease or the type of repair, and other elements that influence the final result. This preventive estimation may help to avoid future complications, or even death. Methods: We have evaluated four machine learning algorithms to achieve our objective: multilayer perceptron, self-organizing map, radial basis function networks and decision trees. The architectures implemented have the aim of classifying among three types of surgical risk: low complexity, medium complexity and high complexity. Results: Accuracy outcomes achieved range between 80% and 99%, being the multilayer perceptron method the one that offered a higher hit ratio. Conclusions: According to the results, it is feasible to develop a clinical decision support system using the evaluated algorithms. Such system would help cardiology specialists, paediatricians and surgeons to forecast the level of risk related to a congenital heart disease surgery.