Chronic Kidney Disease and Coronary Artery Disease: JACC State-of-the-Art Review

Chronic kidney disease (CKD) is a major risk factor for coronary artery disease (CAD). As well as their high prevalence of traditional CAD risk factors, such as diabetes and hypertension, persons with CKD are also exposed to other nontraditional, uremia-related cardiovascular disease risk factors, including inflammation, oxidative stress, and abnormal calcium-phosphorus metabolism. CKD and end-stage kidney disease not only increase the risk of CAD, but they also modify its clinical presentation and cardinal symptoms. Management of CAD is complicated in CKD patients, due to their\ua0likelihood of comorbid conditions and potential for side effects during interventions. This summary of the Kidney\ua0Disease: Improving Global Outcomes (KDIGO) Controversies Conference on CAD and CKD (including end-stage\ua0kidney disease and\ua0transplant recipients) seeks to improve understanding of the epidemiology, pathophysiology, diagnosis, and\ua0treatment of CAD in CKD and to identify knowledge gaps, areas of controversy, and\ua0priorities for research

Efficient posterior probability mapping using savage-dickey ratios.

Statistical Parametric Mapping (SPM) is the dominant paradigm for mass-univariate analysis of neuroimaging data. More recently, a Bayesian approach termed Posterior Probability Mapping (PPM) has been proposed as an alternative. PPM offers two advantages: (i) inferences can be made about effect size thus lending a precise physiological meaning to activated regions, (ii) regions can be declared inactive. This latter facility is most parsimoniously provided by PPMs based on Bayesian model comparisons. To date these comparisons have been implemented by an Independent Model Optimization (IMO) procedure which separately fits null and alternative models. This paper proposes a more computationally efficient procedure based on Savage-Dickey approximations to the Bayes factor, and Taylor-series approximations to the voxel-wise posterior covariance matrices. Simulations show the accuracy of this Savage-Dickey-Taylor (SDT) method to be comparable to that of IMO. Results on fMRI data show excellent agreement between SDT and IMO for second-level models, and reasonable agreement for first-level models. This Savage-Dickey test is a Bayesian analogue of the classical SPM-F and allows users to implement model comparison in a truly interactive manner

Endothelium-derived endothelin-1

One year after the revelation by Dr. Furchgott in 1980 that the endothelium was obligatory for acetylcholine to relax isolated arteries, it was clearly shown that the endothelium could also promote contraction. In 1988, Dr. Yanagisawa’s group identified endothelin-1 (ET-1) as the first endothelium-derived contracting factor. The circulating levels of this short (21-amino acid) peptide were quickly determined in humans, and it was reported that, in most cardiovascular diseases, circulating levels of ET-1 were increased, and ET-1 was then tagged as “a bad guy.” The discovery of two receptor subtypes in 1990, ET(A) and ET(B), permitted optimization of the first dual ET-1 receptor antagonist in 1993 by Dr. Clozel’s team, who entered clinical development with bosentan, which was offered to patients with pulmonary arterial hypertension in 2001. The revelation of Dr. Furchgott opened a Pandora’s box with ET-1 as one of the actors. In this brief review, we will discuss the physiological and pathophysiological role of endothelium-derived ET-1 focusing on the regulation of the vascular tone, and as much as possible in humans. The coronary bed will be used as a running example in this review because it is the most susceptible to endothelial dysfunction, but references to the cerebral and renal circulation will also be made. Many of the cardiovascular complications associated with aging and cardiovascular risk factors are initially attributable, at least in part, to endothelial dysfunction, particularly dysregulation of the vascular function associated with an imbalance in the close interdependence of nitric oxide and ET-1