The current status of heart failure diagnostic biomarkers

Heart failure (HF) affects approximately 23 million individuals worldwide and this number is increasing, due to an aging and growing population. Early detection of HF is crucial in the management of this debilitating disease. Current diagnostic methods for HF rely heavily on clinical imaging techniques and blood analysis, which makes them less than ideal for population-based screening purposes. Studies focusing on developing novel biomarkers for HF have utilized various techniques and biological fluids, including urine and saliva. Promising results from these studies imply that these body fluids can be used in evaluating the clinical manifestation of HF and will one day be integrated into a clinical workflow and facilitate HF management.

Reduced withdrawal and failure rates of accelerated nursing students enrolled in pharmacology is associated with a supportive intervention

Background To reduce nursing shortages, accelerated nursing programs are available for domestic and international students. However, the withdrawal and failure rates from these programs may be different than for the traditional programs. The main aim of our study was to improve the retention and experience of accelerated nursing students. Methods The academic background, age, withdrawal and failure rates of the accelerated and traditional students were determined. Data from 2009 and 2010 were collected prior to intervention. In an attempt to reduce the withdrawal of accelerated students, we set up an intervention, which was available to all students. The assessment of the intervention was a pre-post-test design with non-equivalent groups (the traditional and the accelerated students). The elements of the intervention were a) a formative website activity of some basic concepts in anatomy, physiology and pharmacology, b) a workshop addressing study skills and online resources, and c) resource lectures in anatomy/physiology and microbiology. The formative website and workshop was evaluated using questionnaires. Results The accelerated nursing students were five years older than the traditional students (p < 0.0001). The withdrawal rates from a pharmacology course are higher for accelerated nursing students, than for traditional students who have undertaken first year courses in anatomy and physiology (p = 0.04 in 2010). The withdrawing students were predominantly the domestic students with non-university qualifications or equivalent experience. The failure rates were also higher for this group, compared to the traditional students (p = 0.05 in 2009 and 0.03 in 2010). In contrast, the withdrawal rates for the international and domestic graduate accelerated students were very low. After the intervention, the withdrawal and failure rates in pharmacology for domestic accelerated students with non-university qualifications were not significantly different than those of traditional students. Conclusions The accelerated international and domestic graduate nursing students have low withdrawal rates and high success rates in a pharmacology course. However, domestic students with non-university qualifications have higher withdrawal and failure rates than other nursing students and may be underprepared for university study in pharmacology in nursing programs. The introduction of an intervention was associated with reduced withdrawal and failure rates for these students in the pharmacology course.

Achieving a national sample of nursing homes: Balancing probability techniques and practicalities

Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

A pilot education on heart failure self-management and introduction of the teach-back method to cardiac nurses in Vietnam

It is recognised that patients with chronic disease are unable to remembercorrectly information provided by health care profesionals. The teach-back method is acknowledgedas a technique to improve patients’ understanding. Yet it is not used in nursing practice in Vietnam. Objectives This study sought to examine knowledge background of heart failure among cardiac nurses, introduce a education about heart failure self-management and the teach-back method to assist teaching patients on self-care. The study also wanted to explore if a short education could benefit nurses’ knowledge so they would be qualified to deliver education to patients. Methods A pre/post-test design was employed. Cardiac nurses from 3 hospitals (Vietnam National Heart Institute, E Hospital, Huu Nghi Hospital) were invited to attend a six-hour educational session which covered both the teach-back method and heart failure self-management. Role-play with scenarios were used to reinforce educational contents. The Dutch Heart Failure Knowledge Scale was used to assess nurses’ knowledge of heart failure at baseline and after the educational session. Results 20 nurses from3 selected hospitals participated. Average age was 34.5±7.9 years and years of nursing experience was 11.6±8.3. Heart failure knowledge score at the baseline was 12.7±1.2 and post education was 13.8±1.0. There was deficiency of nurses knowledge regarding fluid restriction among heart failure people, causes of worsening heart failure. Heart failure knowledge improved significantly following the workshop (p < 0.001). All nurses achieved an overall adequate knowledge score (≥11 of the maximum 15) at the end. 100% of nurses agreed that the teach-back method was effective and could be used to educate patients about heart failure self-management. Conclusions The results of this study have shown the effectiveness of the piloteducaiton in increasing nurses’ knowledge of heart failure. The teach-back method is accepted for Vietnamese nurses to use in routine cardiac practice.

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

Optimal maintenance and replacement via a semi-Markov decision model

Optimal bang-coast maintenance policies for a machine, subject to failure, are considered. The approach utilizes a semi-Markov model for the system. A simplified model for modifying the probability of machine failure with maintenance is employed. A numerical example is presented to illustrate the procedure and results.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Conditions of Compromise and Failure (The Dickensian Aspect)

‘Conditions of Compromise and Failure (The Dickensian Aspect)' acts as a re-enactment of the common trope of television detective dramas. A result of the artist’s repeated immersions in the television program ‘The Wire’, the work forms a node-map of all the named characters featured on the show. While each coloured thread represents and connects together the Byzantine narrative between all of the characters, the sheer mass of connections obfuscates any clear reading at all.

A lower bound to the survival probability and an approximate first passage time distribution for Markovian and non-Markovian dynamics in phase space

We derive a very general expression of the survival probability and the first passage time distribution for a particle executing Brownian motion in full phase space with an absorbing boundary condition at a point in the position space, which is valid irrespective of the statistical nature of the dynamics. The expression, together with the Jensen's inequality, naturally leads to a lower bound to the actual survival probability and an approximate first passage time distribution. These are expressed in terms of the position-position, velocity-velocity, and position-velocity variances. Knowledge of these variances enables one to compute a lower bound to the survival probability and consequently the first passage distribution function. As examples, we compute these for a Gaussian Markovian process and, in the case of non-Markovian process, with an exponentially decaying friction kernel and also with a power law friction kernel. Our analysis shows that the survival probability decays exponentially at the long time irrespective of the nature of the dynamics with an exponent equal to the transition state rate constant.

Regulation of Kinin receptor Expression in Heart Failure with a Focus on Vascular Endothelium

Accumulating evidence show that kinins, notably bradykinin (BK) and kallidin, have cardioprotective effects. To these include reduction of left ventricular hypertrophy (LVH) and progression of heart failure. The effects are mediated through two G protein-coupled receptors- bradykinin type-2 receptor (BK-2R) and bradykinin type -1 receptor (BK-1R). The widely accepted cardioprotective effects of BK-receptors relate to triggering the production and release of vasodilating nitric oxide (NO) by endothelial cells. They also exert anti-proliferative effects on fibroblasts and anti-hypertrophic effects on myocytes, and thus may play an essential role in the cardioprotective response to myocardial injury. The role for BK-1Rs in HF is based on experimental animal models, where the receptors have been linked to cardioprotective- but also to cardiotoxic -effects. The BK-1Rs are induced under inflammatory and ischemic conditions, shown in animal models; no previous reports, concerning BK-1Rs in human heart failure, have been presented. The expression of BK-2Rs is down-regulated in human end-stage heart failure. Present results showed that, in these patients, the BK-1Rs were up-regulated, suggesting that also BK-1Rs are involved in the pathogenesis of human heart failure. The receptors were localized mainly in the endothelium of intramyocardial coronary vessels, and correlated with the increased TNF-α expression in the myocardial coronary vessels. Moreover, in cultured endothelial cells, TNF-α was a potent trigger of BK-1Rs. These results suggest that cytokines may be responsible for the up-regulation of BK-1Rs in human heart failure. A linear relationship between BK-2R mRNA and protein expression in normal and failing human left ventricles implies that the BK-2Rs are regulated on the transcriptional level, at least in human myocardium. The expression of BK-2Rs correlated positively with age in normal and dilated hearts (IDC). The results suggest that human hearts adapts to age-related changes, by up-regulating the expression of cardioprotective BK-2Rs. Also, in the BK-2R promoter polymorphism -58 T/C, the C-allele was accumulated in cardiomyopathy patients which may partially explain the reduced number of BK-2Rs. Statins reduce the level of plasma cholesterol, but also exert several non-cholesterol-dependent effects. These effects were studied in human coronary arterial endothelial cells (hCAEC) and incubation with lovastatin induced both BK-1 and BK-2Rs in a time and concentration-dependent way. The induced BK-2Rs were functionally active, thus NO production and cGMP signaling was increased. Induction was abrogated by mevalonate, a direct HMG-CoA metabolite. Lovastatin is known to inhibit Rho activation, and by a selective RhoA kinase inhibitor (Y27632), a similar induction of BK-2R expression as with lovastatin. Interestingly a COX-2-inhibitor (NS398) inhibited this lovastatin-induction of BK-2Rs, suggesting that COX-2 inhibitors may affect the endothelial BK-2Rs, in a negative fashion. Hypoxia is a common denominator in HF but also in other cardiovascular diseases. An induction of BK-2Rs in mild hypoxic conditions was shown in cultured hCAECs, which was abolished by a specific BK-2R inhibitor Icatibant. These receptors were functionally active, thus BK increased and Icatibant inhibited the production of NO. In rat myocardium the expression of BK-2R was increased in the endothelium of vessels, forming at the border zone, between the scar tissue and the healthy myocardium. Moreover, in in vitro wound-healing assay, endothelial cells were cultured under hypoxic conditions and BK significantly increased the migration of these cells and as Icatibant inhibited it. These results show, that mild hypoxia triggers a temporal expression of functionally active BK-2Rs in human and rat endothelial cells, supporting a role for BK-2Rs, in hypoxia induced angiogenesis. Our and previous results show, that BK-Rs have an impact on the cardiovascular diseases. In humans, at the end stage of heart failure, the BK-2Rs are down-regulated and BK-1Rs induced. Whether the up-regulation of BK-1Rs, is a compensatory mechanism against the down-regulation of BK-2Rs, or merely reflects the end point of heart failure, remains to bee seen. In a clinical point of view, the up-regulation of BK-2Rs, under hypoxic conditions or statin treatment, suggests that, the induction of BK-2Rs is protective in cardiovascular pathologies and those treatments activating BK-2Rs, might give additional tools in treating heart failure.

Conservative Design Optimization of Laminated Composite Structures Using Genetic Algorithms and Multiple Failure Criteria

This article analyzes the effect of devising a new failure envelope by the combination of the most commonly used failure criteria for the composite laminates, on the design of composite structures. The failure criteria considered for the study are maximum stress and Tsai-Wu criteria. In addition to these popular phenomenological-based failure criteria, a micromechanics-based failure criterion called failure mechanism-based failure criterion is also considered. The failure envelopes obtained by these failure criteria are superimposed over one another and a new failure envelope is constructed based on the lowest absolute values of the strengths predicted by these failure criteria. Thus, the new failure envelope so obtained is named as most conservative failure envelope. A minimum weight design of composite laminates is performed using genetic algorithms. In addition to this, the effect of stacking sequence on the minimum weight of the laminate is also studied. Results are compared for the different failure envelopes and the conservative design is evaluated, with respect to the designs obtained by using only one failure criteria. The design approach is recommended for structures where composites are the key load-carrying members such as helicopter rotor blades.

Mechanism of failure in a free-standing Pt-aluminide bond coat during tensile testing at room temperature

The room temperature (RT) tensile behaviour of a free-standing high activity Pt-aluminide bond coat has been evaluated by microtensile testing technique. The coating had a typical three-layer microstructure. The stress-strain plot for the free-standing coating was linear, indicating the coating to be brittle at RT. Different fracture features were observed across the coating layers, namely quasi-cleavage in the outer layer and inner interdiffusion zone, and cleavage in the intermediate layer. By employing interrupted tensile test and observing the cross-sectional microstructure of the tested specimens, it was determined that failure of the microtensile samples occurred by the initiation of a single crack in the intermediate layer of the coating and its subsequent inside-out propagation. Such a mechanism of failure has been explained in terms of the fracture features observed across the sample thickness. This mechanism of failure is consistent with fracture toughness values of the individual coating layers. (C) 2009 Elsevier B.V. All rights reserved.