Design and rationale of a randomized trial: Using short stay units instead of routine admission to improve patient centered health outcomes for acute heart failure patients (SSU-AHF)

Nearly 85% of acute heart failure (AHF) patients who present to the emergency department (ED) with acute heart failure are hospitalized. Once hospitalized, within 30 days post-discharge, 27% of patients are re-hospitalized or die. Attempts to improve outcomes with novel therapies have all failed. The evidence for existing AHF therapies are poor: No currently used AHF treatment is known to improve long-term outcomes. ED treatment is largely the same today as 40 years ago. Admitting patients who could have avoided hospitalization may contribute to adverse outcomes. Hospitalization is not benign; patients enter a vulnerable phase post-discharge, at increased risk for morbidity and mortality. When hospitalization is able to be shortened or avoid completely, certain risks can be mitigated, including risk of medication errors, in-hospital falls, delirium, nosocomial infections, and other iatrogenic complications. Additionally, patients would prefer to be home, not hospitalized. Furthermore, hospitalization and re-hospitalization for AHF predominantly affects patients of lower socioeconomic status (SES). Avoiding hospitalization in patients who do not require admission may improve outcomes and quality of life, while reducing costs. Short stay unit (SSU: <24 h, also referred to as an ‘observation unit’) management of AHF may be effective for lower risk patients. However, to date there have only been small studies or retrospective analyses on the SSU management for AHF patients. In addition, SSU management has been considered ‘cheating’ for hospitals trying to avoid 30-day readmission penalties, as SSUs or observation units do not count as an admission. However, more recent analyses demonstrate differential use of observation status has not led to decreases in re-admission, suggesting this concern may be misplaced. Thus, we propose a robust clinical effectiveness trial to demonstrate the effectiveness of this patient-centered strategy

Methods for detecting flaring structures in Sagittarius A* with high frequency VLBI

The super massive black hole candidate, Sagittarius A*, exhibits variability from radio to X-ray wavelengths on time scales that correspond to < 10 Schwarzschild radii. We survey the potential of millimeter-wavelength VLBI to detect and constrain time variable structures that could give rise to such variations, focusing on a model in which an orbiting hot spot is embedded in an accretion disk. Non-imaging algorithms are developed that use interferometric closure quantities to test for periodicity, and applied to an ensemble of hot-spot models that sample a range of parameter space. We find that structural periodicity in a wide range of cases can be detected on most potential VLBI arrays using modern VLBI instrumentation. Future enhancements of mm/sub-mm VLBI arrays including phased array processors to aggregate VLBI station collecting area, increased bandwidth recording, and addition of new VLBI sites all significantly aid periodicity detection. The methods described herein can be applied to other models of Sagittarius A*, including jet outflows and Magneto-Hydrodynamic accretion simulations.Comment: Submitted to Ap

Patients experiencing statin-induced myalgia exhibit a unique program of skeletal muscle gene expression following statin re-challenge

<div><p>Statins, the 3-hydroxy-3-methyl-glutaryl (HMG)-CoA reductase inhibitors, are widely prescribed for treatment of hypercholesterolemia. Although statins are generally well tolerated, up to ten percent of statin-treated patients experience myalgia symptoms, defined as muscle pain without elevated creatinine phosphokinase (CPK) levels. Myalgia is the most frequent reason for discontinuation of statin therapy. The mechanisms underlying statin myalgia are not clearly understood. To elucidate changes in gene expression associated with statin myalgia, we compared profiles of gene expression in skeletal muscle biopsies from patients with statin myalgia who were undergoing statin re-challenge (cases) <i>versus</i> those of statin-tolerant controls. A robust separation of case and control cohorts was revealed by Principal Component Analysis of differentially expressed genes (DEGs). To identify putative gene expression and metabolic pathways that may be perturbed in skeletal muscles of patients with statin myalgia, we subjected DEGs to Ingenuity Pathways (IPA) and DAVID (Database for Annotation, Visualization and Integrated Discovery) analyses. The most prominent pathways altered by statins included cellular stress, apoptosis, cell senescence and DNA repair (TP53, BARD1, Mre11 and RAD51); activation of pro-inflammatory immune response (CXCL12, CST5, POU2F1); protein catabolism, cholesterol biosynthesis, protein prenylation and RAS-GTPase activation (FDFT1, LSS, TP53, UBD, ATF2, H-ras). Based on these data we tentatively conclude that persistent myalgia in response to statins may emanate from cellular stress underpinned by mechanisms of post-inflammatory repair and regeneration. We also posit that this subset of individuals is genetically predisposed to eliciting altered statin metabolism and/or increased end-organ susceptibility that lead to a range of statin-induced myopathies. This mechanistic scenario is further bolstered by the discovery that a number of single nucleotide polymorphisms (e.g., <i>SLCO1B1</i>, <i>SLCO2B1</i> and <i>RYR2)</i> associated with statin myalgia and myositis were observed with increased frequency among patients with statin myalgia.</p></div

Demographic and laboratory characteristics of cases and controls ^§.

<p>Demographic and laboratory characteristics of cases and controls <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0181308#t001fn001" target="_blank">^§</a>.</p

A hypothetical scheme of statin-induced blockade of mevalonate biosynthesis and its consequences for skeletal muscle gene expression and myopathy.

<p>Potential differences in inter-organ uptake, metabolism and flux of statins in genetically susceptible patients lead to greater skeletal muscle toxicity. Inhibition of mevalonate and its downstream reaction products result in reduced availability of geranyl-pyrophosphate and farnesyl-pyrophosphate, needed for prenylation/lipidation of signaling proteins. Altered signal transduction pathways re-program skeletal muscle gene expression. Genetic polymorphisms and significantly altered genes that putatively underpin skeletal muscle pathology are indicated. (Modified with permission from Norata GD, Tibolla G, and Catapano AL. Pharmacological Research 88 (2014) 107–113.)</p

IPA analysis identifies 5 upstream regulators related to differentially expressed genes (DEGs).

<p>IPA analysis identifies 5 upstream regulators related to differentially expressed genes (DEGs).</p

Ingenuity pathway analysis top 10 up-regulated genes.

<p>Ingenuity pathway analysis top 10 up-regulated genes.</p

Functional annotation clustering of DEGs seen in the muscle of patients experiencing statin myalgia (DAVID functional annotation clustering).

<p>Functional annotation clustering of DEGs seen in the muscle of patients experiencing statin myalgia (DAVID functional annotation clustering).</p

Observed versus expected minor allele frequency for gene polymorphisms associated with statin myalgia in cases versus controls compared to population frequency.

<p>Observed versus expected minor allele frequency for gene polymorphisms associated with statin myalgia in cases versus controls compared to population frequency.</p

Ingenuity Pathway Analysis (IPA) identifies a network enriched in differentially expressed genes (DEGs).

<p>The inter-relationship of DEGs identified as part of a gene network related to organismal injury and skeletal and muscular disorders (Network 4 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0181308#pone.0181308.t003" target="_blank">Table 3</a>) is depicted visually. Genes exhibiting differential expression in skeletal muscle of cases versus controls are denoted in green (lower expression in cases) and pink/red (higher expression in cases). Regulatory molecules shared by genes within each network some of which are DEGs and some are not are identified as "hubs". Solid lines denote positive interaction and dashed lines inhibitory influences. Genes denoted by circles represent other proteins, triangles represent kinases, inverted triangles represent phosphatases, and diamonds represent enzymes.</p