Renal Denervation Update From the International Sympathetic Nervous System Summit:JACC State-of-the-Art Review

Three recent renal denervation studies in both drug-naïve and drug-treated hypertensive patients demonstrated a significant reduction of ambulatory blood pressure compared with respective sham control groups. Improved trial design, selection of relevant patient cohorts, and optimized interventional procedures have likely contributed to these positive findings. However, substantial variability in the blood pressure response to renal denervation can still be observed and remains a challenging and important problem. The International Sympathetic Nervous System Summit was convened to bring together experts in both experimental and clinical medicine to discuss the current evidence base, novel developments in our understanding of neural interplay, procedural aspects, monitoring of technical success, and others. Identification of relevant trends in the field and initiation of tailored and combined experimental and clinical research efforts will help to address remaining questions and provide much-needed evidence to guide clinical use of renal denervation for hypertension treatment and other potential indications

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models