Coronary-artery bypass surgery in patients with ischemic cardiomyopathy

BACKGROUND The survival benefit of a strategy of coronary-artery bypass grafting (CABG) added to guideline-directed medical therapy, as compared with medical therapy alone, in patients with coronary artery disease, heart failure, and severe left ventricular systolic dysfunction remains unclear. METHODS From July 2002 to May 2007, a total of 1212 patients with an ejection fraction of 35% or less and coronary artery disease amenable to CABG were randomly assigned to undergo CABG plus medical therapy (CABG group, 610 patients) or medical therapy alone (medical-therapy group, 602 patients). The primary outcome was death from any cause. Major secondary outcomes included death from cardiovascular causes and death from any cause or hospitalization for cardiovascular causes. The median duration of follow-up, including the current extended-follow-up study, was 9.8 years. RESULTS A primary outcome event occurred in 359 patients (58.9%) in the CABG group and in 398 patients (66.1%) in the medical-therapy group (hazard ratio with CABG vs. medical therapy, 0.84; 95% confidence interval [CI], 0.73 to 0.97; P=0.02 by log-rank test). A total of 247 patients (40.5%) in the CABG group and 297 patients (49.3%) in the medical-therapy group died from cardiovascular causes (hazard ratio, 0.79; 95% CI, 0.66 to 0.93; P=0.006 by log-rank test). Death from any cause or hospitalization for cardiovascular causes occurred in 467 patients (76.6%) in the CABG group and in 524 patients (87.0%) in the medical-therapy group (hazard ratio, 0.72; 95% CI, 0.64 to 0.82; P<0.001 by log-rank test). CONCLUSIONS In a cohort of patients with ischemic cardiomyopathy, the rates of death from any cause, death from cardiovascular causes, and death from any cause or hospitalization for cardiovascular causes were significantly lower over 10 years among patients who underwent CABG in addition to receiving medical therapy than among those who received medical therapy alone. (Funded by the National Institutes of Health; STICH [and STICHES] ClinicalTrials.gov number, NCT00023595.

A simple measure with complex determinants: investigation of the correlates of self-rated health in older men and women from three continents

Self-rated health is commonly employed in research studies that seek to assess the health status of older individuals. Perceptions of health are, however, influenced by individual and societal level factors that may differ within and between countries. This study investigates levels of self-rated health (SRH) and correlates of SRH among older adults in Australia, United States of America (USA), Japan and South Korea. We conclude that when examining correlates of SRH, the similarities are greater than the differences between countries. There are however differences in levels of SRH which are not fully accounted for by the health correlates. Broad generalizations about styles of responding are not helpful for understanding these differences, which appear to be country- and possibly cohort-specific. When using SRH to characterize the health status of older people, it is important to consider earlier life experiences of cohorts as well as national and individual factors in later life. Further research is required to understand the complex societal influences on perceptions of health.The Australian data on which this research is based were drawn from several Australian longitudinal studies including: the Australian Longitudinal Study of Ageing (ALSA), the Australian Longitudinal Study of Women’s Health (ALSWH) and the Personality And Total Health Through Life Study (PATH). These studies were pooled and harmonized for the Dynamic Analyses to Optimize Ageing (DYNOPTA) project. DYNOPTA was funded by a National Health and Medical Research Council (NHMRC) grant (# 410215)

Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data

Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about their biology. Yet, as more experiments are considered, a complex’s signature may become conditional and less identifiable. Previously we successfully distinguished the general proteomic signature of genuine chromosomal proteins from hitchhikers using the Random Forests (RF) machine learning algorithm. Here we test whether small protein complexes can define distinguishable signatures of their own, despite the assumption that machine learning needs large training sets. We show, with simulated and real proteomics data, that RF can detect small protein complexes and relationships between them. We identify several complexes in quantitative proteomics results of wild-type and knockout mitotic chromosomes. Other proteins covary strongly with these complexes, suggesting novel functional links for later study. Integrating the RF analysis for several complexes reveals known interdependences among kinetochore subunits and a novel dependence between the inner kinetochore and condensin. Ribosomal proteins, although identified, remained independent of kinetochore subcomplexes. Together these results show that this complex-oriented RF (NanoRF) approach can integrate proteomics data to uncover subtle protein relationships. Our NanoRF pipeline is available online

The choice of self-rated health measures matter when predicting mortality: evidence from 10 years follow-up of the Australian longitudinal study of ageing

<p>Abstract</p> <p>Background</p> <p>Self-rated health (SRH) measures with different wording and reference points are often used as equivalent health indicators in public health surveys estimating health outcomes such as healthy life expectancies and mortality for older adults. Whilst the robust relationship between SRH and mortality is well established, it is not known how comparable different SRH items are in their relationship to mortality over time. We used a dynamic evaluation model to investigate the sensitivity of time-varying SRH measures with different reference points to predict mortality in older adults over time.</p> <p>Methods</p> <p>We used seven waves of data from the Australian Longitudinal Study of Ageing (1992 to 2004; N = 1733, 52.6% males). Cox regression analysis was used to evaluate the relationship between three time-varying SRH measures (global, age-comparative and self-comparative reference point) with mortality in older adults (65+ years).</p> <p>Results</p> <p>After accounting for other mortality risk factors, poor global SRH ratings increased mortality risk by 2.83 times compared to excellent ratings. In contrast, the mortality relationship with age-comparative and self-comparative SRH was moderated by age, revealing that these comparative SRH measures did not independently predict mortality for adults over 75 years of age in adjusted models.</p> <p>Conclusions</p> <p>We found that a global measure of SRH not referenced to age or self is the best predictor of mortality, and is the most reliable measure of self-perceived health for longitudinal research and population health estimates of healthy life expectancy in older adults. Findings emphasize that the SRH measures are not equivalent measures of health status.</p

Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: A simulation study

<p>Abstract</p> <p>Background</p> <p>Multicentre randomized controlled trials (RCTs) routinely use randomization and analysis stratified by centre to control for differences between centres and to improve precision. No consensus has been reached on how to best analyze correlated continuous outcomes in such settings. Our objective was to investigate the properties of commonly used statistical models at various levels of clustering in the context of multicentre RCTs.</p> <p>Methods</p> <p>Assuming no treatment by centre interaction, we compared six methods (ignoring centre effects, including centres as fixed effects, including centres as random effects, generalized estimating equation (GEE), and fixed- and random-effects centre-level analysis) to analyze continuous outcomes in multicentre RCTs using simulations over a wide spectrum of intraclass correlation (ICC) values, and varying numbers of centres and centre size. The performance of models was evaluated in terms of bias, precision, mean squared error of the point estimator of treatment effect, empirical coverage of the 95% confidence interval, and statistical power of the procedure.</p> <p>Results</p> <p>While all methods yielded unbiased estimates of treatment effect, ignoring centres led to inflation of standard error and loss of statistical power when within centre correlation was present. Mixed-effects model was most efficient and attained nominal coverage of 95% and 90% power in almost all scenarios. Fixed-effects model was less precise when the number of centres was large and treatment allocation was subject to chance imbalance within centre. GEE approach underestimated standard error of the treatment effect when the number of centres was small. The two centre-level models led to more variable point estimates and relatively low interval coverage or statistical power depending on whether or not heterogeneity of treatment contrasts was considered in the analysis.</p> <p>Conclusions</p> <p>All six models produced unbiased estimates of treatment effect in the context of multicentre trials. Adjusting for centre as a random intercept led to the most efficient treatment effect estimation across all simulations under the normality assumption, when there was no treatment by centre interaction.</p

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Patient and general practitioner attitudes to taking medication to prevent cardiovascular disease after receiving detailed information on risks and benefits of treatment: a qualitative study

Abstract Background There are now effective drugs to prevent cardiovascular disease and guidelines recommend their use. Patients do not always choose to accept preventive medication at levels of risk reduction recommended in guidelines. The purpose of the study was to identify and explore the attitudes of patients and general practitioners towards preventative medication for cardiovascular disease (CVD) after they have received information about it; to identify implications for practice and prescribing. Methods Qualitative interviews with GPs and patients following presentation of in depth information about CVD risks and the absolute effects of medication. Setting: GP practices in Birmingham, United Kingdom. Results In both populations: wide variation on attitudes to preventative medication; concerns about unnecessary drug taking & side effects; preferring to consider lifestyle changes first. In patient population: whatever their attitudes to medication were, the vast majority explained that they would ultimately do what their GP recommended; there was some misunderstanding of the distinction between curative and preventative medication. A common theme was the degree of trust in their doctors' judgement and recommendations, which contrasted with scepticism of the role of pharmaceutical companies and academics. Scepticism in guidelines was also common among doctors although many nevertheless recommended treatment for their patients Conclusions A guideline approach to prescribing preventative medication could be against the interests and preferences of the patient. GPs must take extra care to explain what preventative medication is and why it is recommended, attempt to discern preferences and make recommendations balancing these potentially conflicting concerns.</p

ATM Regulates Differentiation of Myofibroblastic Cancer-Associated Fibroblasts and Can Be Targeted to Overcome Immunotherapy Resistance

Myofibroblastic cancer-associated fibroblast (myoCAF)-rich tumors generally contain few T cells and respond poorly to immune-checkpoint blockade. Although myoCAFs are associated with poor outcome in most solid tumors, the molecular mechanisms regulating myoCAF accumulation remain unclear, limiting the potential for therapeutic intervention. Here, we identify ataxia-telangiectasia mutated (ATM) as a central regulator of the myoCAF phenotype. Differentiating myofibroblasts in vitro and myoCAFs cultured ex vivo display activated ATM signaling, and targeting ATM genetically or pharmacologically could suppress and reverse differentiation. ATM activation was regulated by the reactive oxygen species-producing enzyme NOX4, both through DNA damage and increased oxidative stress. Targeting fibroblast ATM in vivo suppressed myoCAF-rich tumor growth, promoted intratumoral CD8 T-cell infiltration, and potentiated the response to anti-PD-1 blockade and antitumor vaccination. This work identifies a novel pathway regulating myoCAF differentiation and provides a rationale for using ATM inhibitors to overcome CAF-mediated immunotherapy resistance.SignificanceATM signaling supports the differentiation of myoCAFs to suppress T-cell infiltration and antitumor immunity, supporting the potential clinical use of ATM inhibitors in combination with checkpoint inhibition in myoCAF-rich, immune-cold tumors

Variability in the performance of preventive services and in the degree of control of identified health problems: A primary care study protocol

Background: Preventive activities carried out in primary care have important variability that makes necessary to know which factors have an impact in order to establish future strategies for improvement. The present study has three objectives: 1) To describe the variability in the implementation of 7 preventive services (screening for smoking status, alcohol abuse, hypertension, hypercholesterolemia, obesity, influenza and tetanus immunization) and to determine their related factors; 2) To describe the degree of control of 5 identified health problems (smoking, alcohol abuse, hypertension, hypercholesterolemia and obesity); 3) To calculate intraclass correlation coefficients. Design: Multi-centered cross-sectional study of a randomised sample of primary health care teams from 3 regions of Spain designed to analyse variability and related factors of 7 selected preventive services in years 2006 and 2007. At the end of 2008, we will perform a cross-sectional study of a cohort of patients attended in 2006 or 2007 to asses the degree of control of 5 identified health problems. All subjects older than16 years assigned to a randomised sample of 22 computerized primary health care teams and attended during the study period are included in each region providing a sample with more than 850.000 subjects. The main outcome measures will be implementation of 7 preventive services and control of 5 identified health problems. Furthermore, there will be 3 levels of data collection: 1) Patient level (age, gender, morbidity, preventive services, attendance); 2) Health-care professional level (professional characteristics, years working at the team, workload); 3) Team level (characteristics, electronic clinical record system). Data will be transferred from electronic clinical records to a central database with prior encryption and dissociation of subject, professional and team identity. Global and regional analysis will be performed including standard analysis for primary health care teams and health-care professional level. Linear and logistic regression multilevel analysis adjusted for individual and cluster variables will also be performed. Variability in the number of preventive services implemented will be calculated with Poisson multilevel models. Team and health-care professional will be considered random effects. Intraclass correlation coefficients, standard error and variance components for the different outcome measures will be calculated