Cardiovascular outcomes among elderly patients with heart failure and coronary artery disease and without atrial fibrillation: a retrospective cohort study

Background Coronary artery disease accelerates heart failure progression, leading to poor prognosis and a substantial increase in morbidity and mortality. This study was aimed to assess the impact of coronary artery disease on all-cause mortality, myocardial infarction (MI), and ischemic stroke (IS) among hospitalized newly-diagnosed heart failure (HF) patients with left ventricular systolic dysfunction (LVSD). Methods This retrospective cohort study included Medicare patients (aged ≥65 years) with ≥1 inpatient heart failure claim (index date = discharge date) during 01JAN2007-31DEC2013. Patients were required to have continuous enrollment for ≥1-year pre-index date (baseline: 1-year pre-index period) without a prior heart failure claim (in the 1 year pre-index prior to the index hospital admission); follow-up ran from the index date to death, disenrollment from the health plan, or the end of the study period, whichever occurred first. HF with LVSD patients, identified with diagnosis codes of systolic dysfunction (excluding baseline atrial fibrillation), were stratified based on prevalent coronary artery disease at baseline into coronary artery disease and non-coronary artery disease cohorts. Main outcomes were occurrence of major adverse cardiovascular events including all-cause mortality, myocardial infarction, and ischemic stroke. Propensity score matching (PSM) was used to balance patient characteristics. Kaplan-Meier curves of ACM and cumulative incidence distribution of MI/IS were presented. Results Of 22,230 HF with LVSD patients, 15,827 (71.2%) had coronary artery disease and were overall more likely to be younger (79.8 vs 80.9 years), male (49.6% vs. 35.6%), white (86.2% vs 81.4%), with more prevalent comorbidities including hypertension (80.7% vs 74.3%), hyperlipidemia (67.7% vs 46.7%), and diabetes (46.3% vs 35.8%) (all p < 0.0001). After propensity score matching, cohorts included 5792 patients each. The coronary artery disease cohort had significantly higher cumulative incidence of myocardial infarction and ischemic stroke at the end of 7-year follow-up vs non-coronary artery disease (myocardial infarction = 50.0% vs 18.0%; ischemic stroke = 23.3% vs 18.7%; all p < 0.0001). Follow-up all-cause mortality rates were similar between the two cohorts. Conclusions HF with LVSD patients with coronary artery disease had significantly higher incidence of ischemic stroke and myocardial infarction, but similar all-cause mortality compared to those without coronary artery disease

Complete Haplotype Sequence of the Human Immunoglobulin Heavy-Chain Variable, Diversity, and Joining Genes and Characterization of Allelic and Copy-Number Variation

The immunoglobulin heavy-chain locus (IGH) encodes variable (IGHV), diversity (IGHD), joining (IGHJ), and constant (IGHC) genes and is responsible for antibody heavy-chain biosynthesis, which is vital to the adaptive immune response. Programmed V-(D)-J somatic rearrangement and the complex duplicated nature of the locus have impeded attempts to reconcile its genomic organization based on traditional B-lymphocyte derived genetic material. As a result, sequence descriptions of germline variation within IGHV are lacking, haplotype inference using traditional linkage disequilibrium methods has been difficult, and the human genome reference assembly is missing several expressed IGHV genes. By using a hydatidiform mole BAC clone resource, we present the most complete haplotype of IGHV, IGHD, and IGHJ gene regions derived from a single chromosome, representing an alternate assembly of ∼1 Mbp of high-quality finished sequence. From this we add 101 kbp of previously uncharacterized sequence, including functional IGHV genes, and characterize four large germline copy-number variants (CNVs). In addition to this germline reference, we identify and characterize eight CNV-containing haplotypes from a panel of nine diploid genomes of diverse ethnic origin, discovering previously unmapped IGHV genes and an additional 121 kbp of insertion sequence. We genotype four of these CNVs by using PCR in 425 individuals from nine human populations. We find that all four are highly polymorphic and show considerable evidence of stratification (Fst = 0.3–0.5), with the greatest differences observed between African and Asian populations. These CNVs exhibit weak linkage disequilibrium with SNPs from two commercial arrays in most of the populations tested

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

High performing hospitals: a qualitative systematic review of associated factors and practical strategies for improvement.

BACKGROUND: High performing hospitals attain excellence across multiple measures of performance and multiple departments. Studying high performing hospitals can be valuable if factors associated with high performance can be identified and applied. Factors leading to high performance are complex and an exclusive quantitative approach may fail to identify richly descriptive or relevant contextual factors. The objective of this study was to undertake a systematic review of qualitative literature to identify methods used to identify high performing hospitals, the factors associated with high performers, and practical strategies for improvement. METHODS: Methods used to collect and summarise the evidence contributing to this review followed the 'enhancing transparency in reporting the synthesis of qualitative research' protocol. Peer reviewed studies were identified through Medline, Embase and Cinahl (Jan 2000-Feb 2014) using specified key words, subject terms, and medical subject headings. Eligible studies required the use of a quantitative method to identify high performing hospitals, and qualitative methods or tools to identify factors associated with high performing hospitals or hospital departments. Title, abstract, and full text screening was undertaken by four reviewers, and inter-rater reliability statistics were calculated for each review phase. Risk of bias was assessed. Following data extraction, thematic syntheses identified contextual factors important for explaining success. Practical strategies for achieving high performance were then mapped against the identified themes. RESULTS: A total of 19 studies from a possible 11,428 were included in the review. A range of process, output, outcome and other indicators were used to identify high performing hospitals. Seven themes representing factors associated with high performance (and 25 sub-themes) emerged from the thematic syntheses: positive organisational culture, senior management support, effective performance monitoring, building and maintaining a proficient workforce, effective leaders across the organisation, expertise-driven practice, and interdisciplinary teamwork. Fifty six practical strategies for achieving high performance were catalogued. CONCLUSIONS: This review provides insights into methods used to identify high performing hospitals, and yields ideas about the factors important for success. It highlights the need to advance approaches for understanding what constitutes high performance and how to harness factors associated with high performance