Inferior Myocardial Infarction Secondary to Coronary Artery Vasospasm Following Regadenoson Stress Imaging.

Coronary artery vasospasm is a rare condition that is caused by hyperactive arterial smooth muscle vasoconstriction leading to reversible coronary artery occlusion. Patients that suffer from coronary artery vasospasm have the potential to develop life-threatening conditions such as myocardial infarction and fatal arrhythmias. ST-elevations are a rare complication that can occur in people with coronary vasospasm, and to the best of our knowledge there are no documented cases of ST-elevation myocardial infarction occurring in patients undergoing regadenoson stress test. We present a unique case of a patient with known coronary artery disease and catheter-induced coronary artery vasospasm who developed ST-segment elevations and typical angina immediately following the administration of regadenoson during an elective myocardial stress test.

Neural hypernetwork approach for pulmonary embolism diagnosis.

BACKGROUND: Hypernetworks are based on topological simplicial complexes and generalize the concept of two-body relation to many-body relation. Furthermore, Hypernetworks provide a significant generalization of network theory, enabling the integration of relational structure, logic and analytic dynamics. A pulmonary embolism is a blockage of the main artery of the lung or one of its branches, frequently fatal. RESULTS: Our study uses data on 28 diagnostic features of 1427 people considered to be at risk of pulmonary embolism enrolled in the Department of Internal and Subintensive Medicine of an Italian National Hospital "Ospedali Riuniti di Ancona". Patients arrived in the department after a first screening executed by the emergency room. The resulting neural hypernetwork correctly recognized 94% of those developing pulmonary embolism. This is better than previous results obtained with other methods (statistical selection of features, partial least squares regression, topological data analysis in a metric space). CONCLUSION: In this work we successfully derived a new integrative approach for the analysis of partial and incomplete datasets that is based on Q-analysis with machine learning. The new approach, called Neural Hypernetwork, has been applied to a case study of pulmonary embolism diagnosis. The novelty of this method is that it does not use clinical parameters extracted by imaging analysis.

Remote physiological monitoring: clinical, financial, and behavioral outcomes in a heart failure population.

This article reports on the outcomes associated with remote physiological monitoring (RPM) conducted as part of a heart failure disease management program. Claims data, medical records, data transmission records, and survey results for 91 individuals ages 50-92 (mean 74 years) successfully completing a heart failure RPM program were analyzed for time periods before, during, and after the monitoring intervention. The program was associated with significant reductions in per member per month costs and emergency room and hospital utilization. More detailed analyses were performed for specific gender and age subgroups. Participant surveys indicated high levels of satisfaction, and improvements in self-perceived health status, self-efficacy, and self-management behaviors. This study is the first to assess the impact of a RPM program following removal of the monitoring equipment. The results indicate that RPM, as a component of a traditional disease management program, has a sustained, beneficial effect on participants' lifestyles after the monitoring period has ended.