Ticagrelor, a platelet aggregation inhibitor for the potential prevention and treatment of arterial thrombosis and acute coronary syndromes

Ticagrelor is an orally active ADP P2Y12 receptor antagonist in development by AstraZeneca plc for the reduction of recurrent ischemic events in patients with acute coronary syndromes (ACS). Prior to the development of ticagrelor, thienopyridine compounds, such as clopidogrel, were the focus of research into therapies for ACS. Although the thienopyridines are effective platelet aggregation inhibitors, they are prodrugs and, consequently, exert a slow onset of action. In addition, the variability in inter-individual metabolism of thienopyridine prodrugs has been associated with reduced efficacy in some patients. Ticagrelor is not a prodrug and exhibits a more rapid onset of action than the thienopyridine prodrugs. In clinical trials conducted to date, ticagrelor was a potent inhibitor of ADP-induced platelet aggregation and demonstrated effects that were comparable to clopidogrel. In a phase II, short-term trial, the bleeding profile of participants treated with ticagrelor was similar to that obtained with clopidogrel; however, an increased incidence of dyspnea was observed - an effect that has not been reported with the thienopyridines. Considering the occurrence of dyspnea, and the apparent non-superiority of ticagrelor to clopidogrel, it is difficult to justify a clear benefit to the continued development of ticagrelor. Outcomes from an ongoing phase III trial comparing ticagrelor with clopidogrel in 18,000 patients with ACS are likely to impact on the future development of ticagrelor.

What counts as evidence and equity?

Editorial introduction to Vol. 34 of Review of Research in Education (American Educational Research Association/Sage).

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Identifying large truck hot spots using crash counts and PDOEs

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

Kaolinite platelet orientation for XRD and AFM applications

The structure-building phenomena within clay aggregates are governed by forces acting between clay particles. The nature of such forces is important to understand in order to manipulate the aggregate structure for applications such as settling and dewatering. A parallel particle orientation is required when conducting force measurements acting between the basal planes of clay mineral platelets using atomic force microscopy (AFM). In order to prepare a film of clay particles with the optimal orientation for conducting AFM measurements, the influences of particle concentration in suspension, suspension pH and particle size on the clay platelet orientation were investigated using scanning electron microscopy (SEM) and X-ray diffraction (XRD) methods. From these investigations, we conclude that high clay (dry mass) concentrations and larger particle diameters (up to 5 µm) in suspension result in random orientation of platelets on the substrate. The best possible laminar orientation in the clay dried film as represented in the XRD by the 001/020 intensity ratio of more than 150 and by SE micrograph assessments, was obtained by drying thin layers from 0.2 wt% of -5 µm clay suspensions at pH 10.5. These dried films are stable and suitable for close-approach AFM studies in solution.

What information counts at the moment of practice? Information practices of renal nurses

Aims. This article is a report of a study done to identify how renal nurses experience information about renal care and the information practices that they used to support everyday practice. Background. What counts as nursing knowledge remains a contested area in the discipline yet little research has been undertaken. Information practice encompasses a range of activities such as seeking, evaluation and sharing of information. The ability to make informed judgement is dependent on nurses being able to identify relevant sources of information that inform their practice and those sources of information may enable the identification of what knowledge is important to nursing practice. Method. The study was philosophically framed from a practice perspective and informed by Habermas and Schatzki; it employed qualitative research techniques. Using purposive sampling six registered nurses working in two regional renal units were interviewed during 2009 and data was thematically analysed. Findings. The information practices of renal nurses involved mapping an information landscape in which they drew on information obtained from epistemic, social and corporeal sources. They also used coupling, a process of drawing together information from a range of sources, to enable them to practice. Conclusion. Exploring how nurses engage with information, and the role the information plays in situating and enacting epistemic, social and corporeal knowledge into everyday nursing practice is instructive because it indicates that nurses must engage with all three modalities in order to perform effectively, efficiently and holistically in the context of patient care. © 2011 The Authors. Journal of Advanced Nursing © 2011 Blackwell Publishing Ltd.

Your voice counts : Listening to the voice of high school students with autism spectrum disorder

Supporting students with Autism Spectrum Disorders (ASD) in inclusive settings presents both opportunities and significant challenges to school communities. This study, which explored the lived-experience of nine students with ASD in an inclusive high school in Australia, is based on the belief that by listening to the voices of students, school communities will be in a better position to collaboratively create supportive learning and social environments. The findings of this small-scale study deepen our knowledge from the student perspective of the inclusive educational practices that facilitate and constrain the learning and participation of students with ASD. The students’ perspectives were examined in relation to the characteristics of successful inclusive schools identified by Kluth. Implications for inclusive educational practice that meets the needs of students with ASD are presented.