Health state values for the HUI 2 descriptive system: results from a UK survey

This paper reports the results of a study to estimate a statistical health state valuation model for a revised version of the Health Utilities Index Mark 2, using Standard Gamble health state preference data. A sample of 51 health states were valued by a sample of the 198 members of the UK general population. Models are estimated for predicting health state valuations for all 8,000 states defined by the revised HUI2. The recommended model produces logical and significant coefficients for all levels of all dimensions in the HUI2. These coefficients appear to be robust across model specifications. This model performs well in predicting the observed health state values within the valuation sample and for a separate validation sample of health states. However, there are concerns over large prediction errors for two health states in the valuation sample. These problems must be balanced against concerns over the validity of using the VAS based health state valuation data of the original HUI2 valuation model.HUI2

Apomixis and hybridization drives reticulate evolution and phyletic differentiation in sorbus l.: Implications for conservation

This is the final version. Available from Frontiers Media via the DOI in this record. Hybridization and polyploidy are major forces in the evolution of plant diversity and the study of these processes is of particular interest to understand how novel taxa are formed and how they maintain genetic integrity. Sorbus is an example of a genus where active diversification and speciation are ongoing and, as such, represents an ideal model to investigate the roles of hybridization, polyploidy and apomixis in a reticulate evolutionary process. To elucidate breeding systems and evolutionary origins of a complex of closely related Sorbus taxa, we assessed genotypic diversity and population structure within and among taxa, combining data from nuclear DNA microsatellite markers and flow cytometry. Clonal analysis and low genotypic diversity within the polyploid taxa suggest apomixis is obligate. However, genetic variation has led to groups of ‘clone-mates’ within apomictic taxa that strongly suggest mutation is responsible for the genotypic diversity of these apomictic lineages. In addition, microsatellite profiles and site demographics suggest hybridization events among apomictic polyploid Sorbus may have contributed to the extant diversity of recognized taxa in this region. This research demonstrates that both macro- and micro-evolutionary processes are active within this reticulate Sorbus complex. Conservation measures should be aimed at maintaining this process and should therefore be prioritized for those areas of Sorbus species richness where the potential for interspecific gene flow is greatest.Whitley Wildlife Conservation TrustNational Botanic Garden of Wale

Theories of behaviour change synthesised into a set of theoretical groupings: Introducing a thematic series on the Theoretical Domains Framework

Behaviour change is key to increasing the uptake of evidence into healthcare practice. Designing behaviour-change interventions first requires problem analysis, ideally informed by theory. Yet the large number of partly overlapping theories of behaviour makes it difficult to select the most appropriate theory. The need for an overarching theoretical framework of behaviour change was addressed in research in which 128 explanatory constructs from 33 theories of behaviour were identified and grouped. The resulting Theoretical Domains Framework (TDF) appears to be a helpful basis for investigating implementation problems. Research groups in several countries have conducted TDF-based studies. It seems timely to bring together the experience of these teams in a thematic series to demonstrate further applications and to report key developments. This overview article describes the TDF, provides a brief critique of the framework, and introduces this thematic series. In a brief review to assess the extent of TDF-based research, we identified 133 papers that cite the framework. Of these, 17 used the TDF as the basis for empirical studies to explore health professionals’ behaviour. The identified papers provide evidence of the impact of the TDF on implementation research. Two major strengths of the framework are its theoretical coverage and its capacity to elicit beliefs that could signify key mediators of behaviour change. The TDF provides a useful conceptual basis for assessing implementation problems, designing interventions to enhance healthcare practice, and understanding behaviour-change processes. We discuss limitations and research challenges and introduce papers in this series

Health state values for the HUI 2 descriptive system: results from a UK survey

This paper reports the results of a study to estimate a statistical health state valuation model for a revised version of the Health Utilities Index Mark 2, using Standard Gamble health state preference data. A sample of 51 health states were valued by a sample of the 198 members of the UK general population. Models are estimated for predicting health state valuations for all 8,000 states defined by the revised HUI2. The recommended model produces logical and significant coefficients for all levels of all dimensions in the HUI2. These coefficients appear to be robust across model specifications. This model performs well in predicting the observed health state values within the valuation sample and for a separate validation sample of health states. However, there are concerns over large prediction errors for two health states in the valuation sample. These problems must be balanced against concerns over the validity of using the VAS based health state valuation data of the original HUI2 valuation model

Health state values for the HUI 2 descriptive system: results from a UK survey

This paper reports the results of a study to estimate a statistical health state valuation model for a revised version of the Health Utilities Index Mark 2, using Standard Gamble health state preference data. A sample of 51 health states were valued by a sample of the 198 members of the UK general population. Models are estimated for predicting health state valuations for all 8,000 states defined by the revised HUI2. The recommended model produces logical and significant coefficients for all levels of all dimensions in the HUI2. These coefficients appear to be robust across model specifications. This model performs well in predicting the observed health state values within the valuation sample and for a separate validation sample of health states. However, there are concerns over large prediction errors for two health states in the valuation sample. These problems must be balanced against concerns over the validity of using the VAS based health state valuation data of the original HUI2 valuation model

Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas

Joint registration of a stack of 2D histological sections to recover 3D structure ("3D histology reconstruction") finds application in areas such as atlas building and validation of in vivo imaging. Straightforward pairwise registration of neighbouring sections yields smooth reconstructions but has well-known problems such as "banana effect" (straightening of curved structures) and "z-shift" (drift). While these problems can be alleviated with an external, linearly aligned reference (e.g., Magnetic Resonance (MR) images), registration is often inaccurate due to contrast differences and the strong nonlinear distortion of the tissue, including artefacts such as folds and tears. In this paper, we present a probabilistic model of spatial deformation that yields reconstructions for multiple histological stains that that are jointly smooth, robust to outliers, and follow the reference shape. The model relies on a spanning tree of latent transforms connecting all the sections and slices of the reference volume, and assumes that the registration between any pair of images can be see as a noisy version of the composition of (possibly inverted) latent transforms connecting the two images. Bayesian inference is used to compute the most likely latent transforms given a set of pairwise registrations between image pairs within and across modalities. We consider two likelihood models: Gaussian (ℓ2 norm, which can be minimised in closed form) and Laplacian (ℓ1 norm, minimised with linear programming). Results on synthetic deformations on multiple MR modalities, show that our method can accurately and robustly register multiple contrasts even in the presence of outliers. The framework is used for accurate 3D reconstruction of two stains (Nissl and parvalbumin) from the Allen human brain atlas, showing its benefits on real data with severe distortions. Moreover, we also provide the registration of the reconstructed volume to MNI space, bridging the gaps between two of the most widely used atlases in histology and MRI. The 3D reconstructed volumes and atlas registration can be downloaded from https://openneuro.org/datasets/ds003590. The code is freely available at https://github.com/acasamitjana/3dhirest

Changes in body weight and food choice in those attempting smoking cessation: a cluster randomised controlled trial

<p><b>Background:</b> Fear of weight gain is a barrier to smoking cessation and significant cause of relapse for many people. The provision of nutritional advice as part of a smoking cessation programme may assist some in smoking cessation and perhaps limit weight gain. The aim of this study was to determine the effect of a structured programme of dietary advice on weight change and food choice, in adults attempting smoking cessation.</p> <p><b>Methods:</b> Cluster randomised controlled design. Classes randomised to intervention commenced a 24-week intervention, focussed on improving food choice and minimising weight gain. Classes randomised to control received "usual care".</p> <p><b>Results:</b> Twenty-seven classes in Greater Glasgow were randomised between January and August 2008. Analysis, including those who continued to smoke, showed that actual weight gain and percentage weight gain was similar in both groups. Examination of data for those successful at giving up smoking showed greater mean weight gain in intervention subjects (3.9 (SD 3.1) vs. 2.7 (SD 3.7) kg). Between group differences were not significant (p=0.23, 95% CI -0.9 to 3.5). In comparison to baseline improved consumption of fruit and vegetables and breakfast cereal were reported in the intervention group. A higher percentage of control participants continued smoking (74% vs. 66%).</p> <p><b>Conclusions:</b> The intervention was not successful at minimising weight gain in comparison to control but was successful in facilitating some sustained improvements in the dietary habits of intervention participants. Improved quit rates in the intervention group suggest that continued contact with advisors may have reduced anxieties regarding weight gain and encouraged cessation despite weight gain. Research should continue in this area as evidence suggests that the negative effects of obesity could outweigh the health benefits achieved through reductions in smoking prevalence.</p&gt

Transmission and dose–response experiments for social animals: a reappraisal of the colonization biology of Campylobacter jejuni in chickens

Dose-response experiments characterize the relationship between infectious agents and their hosts. These experiments are routinely used to estimate the minimum effective infectious dose for an infectious agent, which is most commonly characterized by the dose at which 50 per cent of challenged hosts become infected-the ID(50). In turn, the ID(50) is often used to compare between different agents and quantify the effect of treatment regimes. The statistical analysis of dose-response data typically makes the assumption that hosts within a given dose group are independent. For social animals, in particular avian species, hosts are routinely housed together in groups during experimental studies. For experiments with non-infectious agents, this poses no practical or theoretical problems. However, transmission of infectious agents between co-housed animals will modify the observed dose-response relationship with implications for the estimation of the ID(50) and the comparison between different agents and treatments. We derive a simple correction to the likelihood for standard dose-response models that allows us to estimate dose-response and transmission parameters simultaneously. We use this model to show that: transmission between co-housed animals reduces the apparent value of the ID(50) and increases the variability between replicates leading to a distinctive all-or-nothing response; in terms of the total number of animals used, individual housing is always the most efficient experimental design for ascertaining dose-response relationships; estimates of transmission from previously published experimental data for Campylobacter spp. in chickens suggest that considerable transmission occurred, greatly increasing the uncertainty in the estimates of dose-response parameters reported in the literature. Furthermore, we demonstrate that accounting for transmission in the analysis of dose-response data for Campylobacter spp. challenges our current understanding of the differing response of chickens with respect to host-age and in vivo passage of bacteria. Our findings suggest that the age-dependence of transmissibility between hosts-rather than their susceptibility to colonization-is the mechanism behind the 'lag-phase' reported in commercial flocks, which are typically found to be Campylobacter free for the first 14-21 days of life.A.J.K.C. is funded by DEFRA grant PU/T/WL/07/46 - SE3230, sponsored by the Veterinary Laboratories Agency. This research was developed during an earlier project funded by the Biotechnology and Biological Sciences Research Council/Defra Government Partnership Award, grants BB/500852/1 and BB/500936/1

What is the real impact of acute kidney injury?

Background: Acute kidney injury (AKI) is a common clinical problem. Studies have documented the incidence of AKI in a variety of populations but to date we do not believe the real incidence of AKI has been accurately documented in a district general hospital setting. The aim here was to describe the detected incidence of AKI in a typical general hospital setting in an unselected population, and describe associated short and long-term outcomes. Methods: A retrospective observational database study from secondary care in East Kent (adult catchment population of 582,300). All adult patients (18 years or over) admitted between 1st February 2009 and 31st July 2009, were included. Patients receiving chronic renal replacement therapy (RRT), maternity and day case admissions were excluded. AKI was defined by the acute kidney injury network (AKIN) criteria. A time dependent risk analysis with logistic regression and Cox regression was used for the analysis of in-hospital mortality and survival. Results: The incidence of AKI in the 6 month period was 15,325 pmp/yr (adults) (69% AKIN1, 18% AKIN2 and 13% AKIN3). In-hospital mortality, length of stay and ITU utilisation all increased with severity of AKI. Patients with AKI had an increase in care on discharge and an increase in hospital readmission within 30 days. Conclusions: This data comes closer to the real incidence and outcomes of AKI managed in-hospital than any study published in the literature to date. Fifteen percent of all admissions sustained an episode of AKI with increased subsequent short and long term morbidity and mortality, even in those with AKIN1. This confers an increased burden and cost to the healthcare economy, which can now be quantified. These results will furnish a baseline for quality improvement projects aimed at early identification, improved management, and where possible prevention, of AKI