Hauge Buchanan (ratrail5)

Medicine is, in its essence, decision making under uncertainty; the decisions are made about tests to be performed and treatments to be administered. Traditionally, the uncertainty in decision making was handled using expertise collected by individual providers and, more recently, systematic appraisal of research in the form of evidence-based medicine. The traditional approach has been used successfully in medicine for a very long time. However, it has substantial limitations because of the complexity of the system of the human body and healthcare. The complex systems are a network of highly coupled components intensely interacting with each other. These interactions give those systems redundancy and thus robustness to failure and, at the same time, equifinality, that is, many different causative pathways leading to the same outcome. The equifinality of the complex systems of the human body and healthcare system demand the individualization of medical care, medicine, and medical decision making. Computational models excel in modeling complex systems and, consequently, enabling individualization of medical decision making and medicine. Computational models are theory- or knowledge-based models, data-driven models, or models that combine both approaches. Data are essential, although to a different degree, for computational models to successfully represent complex systems. selleck The individualized decision making, made possible by the computational modeling of complex systems, has the potential to revolutionize the entire spectrum of medicine from individual patient care to policymaking. This approach allows applying tests and treatments to individuals who receive a net benefit from them, for whom benefits outweigh the risk, rather than treating all individuals in a population because, on average, the population benefits. Thus, the computational modeling-enabled individualization of medical decision making has the potential to both improve health outcomes and decrease the costs of healthcare.Although it has been claimed that rolling massage (RM), may lead to improvements in skeletal muscle oxygenation, metabolism, blood flow, and vascular function, scientific evidence has not yet been provided. Thus, the current study investigated the effects of 30 s and 2 min of RM on forearm muscle oxygenation, parameters associated with oxidative metabolism, and microvascular reactivity as well as brachial artery endothelial function. Forearm skeletal muscle parameters were assessed in 12 healthy young men (26 ± 6 yrs) using near-infrared spectroscopy (NIRS) combined with a 5-min vascular occlusion test. Additionally, brachial artery endothelial function was simultaneously assessed by measuring the relative change in brachial artery diameter normalized to the hyperemic blood flow (Normalized %FMD). These measurements were performed before and after the RM interventions performed on the anterior forearm muscles. Forearm muscle oxygenation increased after 30 s of RM (62 ± 7 to 71 ± 11%; p = 0.02) while there was no change from baseline to post-intervention after 2 min of RM. No change was observed for oxidative metabolism, however, the significant main effect (p = 0.02) for NIRS-derived reperfusion slope (%·s-1) indicated that microvascular function improved after both 30 s (2.30 ± 0.5 to 2.61 ± 0.70%·s-1) and 2 min of RM (2.33 ± 0.4 to 2.60 ± 0.85%·s-1). The lack of significant effects of RM on Normalized %FMD suggest that the RM did not acutely improve brachial artery endothelial function. These findings provide, for the first time, evidence that RM improves skeletal muscle oxygenation and parameters associated with microvascular reactivity. Additionally, RM increased brachial artery blood flow, but not upstream brachial artery endothelial function.Veno-Venous Extracorporeal Membrane Oxygenation (VV-ECMO) is a rescue treatment for severe acute respiratory failure refractory to conventional ventilation. We examined the alterations of subl