Systematic review and meta-analysis of the growth and rupture rates of small abdominal aortic aneurysms: implications for surveillance intervals and their cost-effectiveness.

BACKGROUND: Small abdominal aortic aneurysms (AAAs; 3.0-5.4 cm in diameter) are usually asymptomatic and managed by regular ultrasound surveillance until they grow to a diameter threshold (commonly 5.5 cm) at which surgical intervention is considered. The choice of appropriate surveillance intervals is governed by the growth and rupture rates of small AAAs, as well as their relative cost-effectiveness. OBJECTIVES: The aim of this series of studies was to inform the evidence base for small AAA surveillance strategies. This was achieved by literature review, collation and analysis of individual patient data, a focus group and health economic modelling. DATA SOURCES: We undertook systematic literature reviews of growth rates and rupture rates of small AAAs. The databases MEDLINE, EMBASE on OvidSP, Cochrane Central Register of Controlled Trials 2009 Issue 4, ClinicalTrials.gov, and controlled-trials.com were searched from inception up until the end of 2009. We also obtained individual data on 15,475 patients from 18 surveillance studies. REVIEW METHODS: Systematic reviews of publications identified 15 studies providing small AAA growth rates, and 14 studies with small AAA rupture rates, up to December 2009 (later updated to September 2012). We developed statistical methods to analyse individual surveillance data, including the effects of patient characteristics, to inform the choice of surveillance intervals and provide inputs for health economic modelling. We updated an existing health economic model of AAA screening to address the cost-effectiveness of different surveillance intervals. RESULTS: In the literature reviews, the mean growth rate was 2.3 mm/year and the reported rupture rates varied between 0 and 1.6 ruptures per 100 person-years. Growth rates increased markedly with aneurysm diameter, but insufficient detail was available to guide surveillance intervals. Based on individual surveillance data, for each 0.5-cm increase in AAA diameter, growth rates increased by about 0.5 mm/year and rupture rates doubled. To control the risk of exceeding 5.5 cm to below 10% in men, on average a 7-year surveillance interval is sufficient for a 3.0-cm aneurysm, whereas an 8-month interval is necessary for a 5.0-cm aneurysm. To control the risk of rupture to below 1%, the corresponding estimated surveillance intervals are 9 years and 17 months. Average growth rates were higher in smokers (by 0.35 mm/year) and lower in patients with diabetes (by 0.51 mm/year). Rupture rates were almost fourfold higher in women than men, doubled in current smokers and increased with higher blood pressure. Increasing the surveillance interval from 1 to 2 years for the smallest aneurysms (3.0-4.4 cm) decreased costs and led to a positive net benefit. For the larger aneurysms (4.5-5.4 cm), increasing surveillance intervals from 3 to 6 months led to equivalent cost-effectiveness. LIMITATIONS: There were no clear reasons why the growth rates varied substantially between studies. Uniform diagnostic criteria for rupture were not available. The long-term cost-effectiveness results may be susceptible to the modelling assumptions made. CONCLUSIONS: Surveillance intervals of several years are clinically acceptable for men with AAAs in the range 3.0-4.0 cm. Intervals of around 1 year are suitable for 4.0-4.9-cm AAAs, whereas intervals of 6 months would be acceptable for 5.0-5.4-cm AAAs. These intervals are longer than those currently employed in the UK AAA screening programmes. Lengthening surveillance intervals for the smallest aneurysms was also shown to be cost-effective. Future work should focus on optimising surveillance intervals for women, studying whether or not the threshold for surgery should depend on patient characteristics, evaluating the usefulness of surveillance for those with aortic diameters of 2.5-2.9 cm, and developing interventions that may reduce the growth or rupture rates of small AAAs. FUNDING: The National Institute for Health Research Health Technology Assessment programme

Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening

Markov models are often used to evaluate the cost-effectiveness of new healthcare interventions but they are sometimes not flexible enough to allow accurate modeling or investigation of alternative scenarios and policies. A Markov model previously demonstrated that a one-off invitation to screening for abdominal aortic aneurysm (AAA) for men aged 65 y in the UK and subsequent follow-up of identified AAAs was likely to be highly cost-effective at thresholds commonly adopted in the UK (£20,000 to £30,000 per quality adjusted life-year). However, new evidence has emerged and the decision problem has evolved to include exploration of the circumstances under which AAA screening may be cost-effective, which the Markov model is not easily able to address. A new model to handle this more complex decision problem was needed, and the case of AAA screening thus provides an illustration of the relative merits of Markov models and discrete event simulation (DES) models. An individual-level DES model was built using the R programming language to reflect possible events and pathways of individuals invited to screening v. those not invited. The model was validated against key events and cost-effectiveness, as observed in a large, randomized trial. Different screening protocol scenarios were investigated to demonstrate the flexibility of the DES. The case of AAA screening highlights the benefits of DES, particularly in the context of screening studies

Cross-correlation analysis to quantify relative spatial distributions of fat and protein in super-resolution microscopy images of dairy gels

The advent of super-resolution microscopy allows microstructures of foods to be explored in new depths, which when coupled with quantitative image analysis can provide a powerful analytical tool. Herein, a methodology is presented and applied to use a 2D spatial cross-correlation analysis to investigate the relative spatial arrangement of protein and fat in acid induced whole milk gels where the milk is either non-homogenised or has been homogenised at either 10 or 25 MPa. Two-channel images were taken using super-resolution Stimulated Emission Depletion (STED) microscopy and confocal microscopy. A term has been derived to extract the typical distance from the fat droplet surface and to the local maximum protein distribution. The fat droplet size is determined through 2D spatial autocorrelation analysis. Methods of analysis are applied to global images and to region specific analysis focussing on individual fat droplets. Cross-correlation analysis has been empirically validated using generated images with precise spatial features corresponding to the features of interest in true microscopy images, over appropriate length scales. The protein microstructure, fat droplet size and distances between the fat droplets and protein network are characterised. There are significantly different distances between the fat droplets and protein network in the homogenised samples compared to the non-homogenised sample. The extracted separation distances are below the diffraction limit of light, highlighting the utility of super-resolution imaging

A smoother end to the dark ages

Independent lines of evidence suggest that the first stars, which ended the cosmic dark ages, came in pairs, rather than singly. This could change the prevailing view that the early Universe had a Swiss-cheese-like appearance.Comment: Nature News and Views, April 7, 201

A review of fMRI simulation studies

Simulation studies that validate statistical techniques for fMRI data are challenging due to the complexity of the data. Therefore, it is not surprising that no common data generating process is available (i.e. several models can be found to model BOLD activation and noise). Based on a literature search, a database of simulation studies was compiled. The information in this database was analysed and critically evaluated focusing on the parameters in the simulation design, the adopted model to generate fMRI data, and on how the simulation studies are reported. Our literature analysis demonstrates that many fMRI simulation studies do not report a thorough experimental design and almost consistently ignore crucial knowledge on how fMRI data are acquired. Advice is provided on how the quality of fMRI simulation studies can be improved

An intra-neural microstimulation system for ultra-high field magnetic resonance imaging and magnetoencephalography.

BACKGROUND: Intra-neural microstimulation (INMS) is a technique that allows the precise delivery of low-current electrical pulses into human peripheral nerves. Single unit INMS can be used to stimulate individual afferent nerve fibres during microneurography. Combining this with neuroimaging allows the unique monitoring of central nervous system activation in response to unitary, controlled tactile input, with functional magnetic resonance imaging (fMRI) providing exquisite spatial localisation of brain activity and magnetoencephalography (MEG) high temporal resolution. NEW METHOD: INMS systems suitable for use within electrophysiology laboratories have been available for many years. We describe an INMS system specifically designed to provide compatibility with both ultra-high field (7T) fMRI and MEG. Numerous technical and safety issues are addressed. The system is fully analogue, allowing for arbitrary frequency and amplitude INMS stimulation. RESULTS: Unitary recordings obtained within both the MRI and MEG screened-room environments are comparable with those obtained in 'clean' electrophysiology recording environments. Single unit INMS (current <7μA, 200μs pulses) of individual mechanoreceptive afferents produces appropriate and robust responses during fMRI and MEG. COMPARISON WITH EXISTING METHOD(S): This custom-built MRI- and MEG-compatible stimulator overcomes issues with existing INMS approaches; it allows well-controlled switching between recording and stimulus mode, prevents electrical shocks because of long cable lengths, permits unlimited patterns of stimulation, and provides a system with improved work-flow and participant comfort. CONCLUSIONS: We demonstrate that the requirements for an INMS-integrated system, which can be used with both fMRI and MEG imaging systems, have been fully met

Dynamic moisture loss explored through quantitative super-resolution microscopy, spatial micro-viscosity and macroscopic analyses in acid milk gels

Molecular interactions and dynamic changes at a range of length scales affect the structuring of food materials, as such it is essential to explore structure at a range of different length scales. Herein, four acid milk gel samples are produced from either fresh or reconstituted skim milk that either had no heat treatment or had undergone heat treatment at 85 °C for 10 min. Milk acid gels demonstrate complex structure on a range of length scales of interest in colloidal materials and exhibit different macroscopic and water binding properties. A method is presented to measure the dynamic moisture loss in these samples, without applying external force. Super-resolution microscopy images are quantitatively analysed to describe the gel microstructure with precise features. Fluorescent Lifetime Imaging Microscopy is used to spatially resolve differences in molecular confinement across the sample's microstructure, which is quantified for each sample. Moisture loss and microstructural analyses are correlated to bulk and macroscopic properties determined through rheological and texture analysis, pH and conductivity measurements. More severe thermal and processing treatments leads to a reduction in moisture loss over time. Differences in moisture loss and mechanical properties relate to different thermal processing histories, but are not fully explained by levels of denatured whey proteins, and appear related to changes in mineral balance. The methods presented provide a comprehensive and complementary overview of material properties across relevant length scales and relevant sample conditions

Anomalous Couplings in Double Higgs Production

The process of gluon-initiated double Higgs production is sensitive to non-linear interactions of the Higgs boson. In the context of the Standard Model, studies of this process focused on the extraction of the Higgs trilinear coupling. In a general parametrization of New Physics effects, however, an even more interesting interaction that can be tested through this channel is the (ttbar hh) coupling. This interaction vanishes in the Standard Model and is a genuine signature of theories in which the Higgs boson emerges from a strongly-interacting sector. In this paper we perform a model-independent estimate of the LHC potential to detect anomalous Higgs couplings in gluon-fusion double Higgs production. We find that while the sensitivity to the trilinear is poor, the perspectives of measuring the new (ttbar hh) coupling are rather promising.Comment: 22 pages, 9 figures. v2: plots of Figs.8 and 9 redone to include experimental uncertainty on the Higgs couplings, references adde

Using Habitat Classification to Assess Representativity of a Protected Area Network in a Large, Data-Poor Area Targeted for Deep-Sea Mining

Extractive activities in the ocean are expanding into the vast, poorly studied deep sea, with the consequence that environmental management decisions must be made for data-poor seafloor regions. Habitat classification can support marine spatial planning and inform decision-making processes in such areas. We present a regional, top–down, broad-scale, seafloor-habitat classification for the Clarion-Clipperton Fracture Zone (CCZ), an area targeted for future polymetallic nodule mining in abyssal waters in the equatorial Pacific Ocean. Our classification uses non-hierarchical, k-medoids clustering to combine environmental correlates of faunal distributions in the region. The classification uses topographic variables, particulate organic carbon flux to the seafloor, and is the first to use nodule abundance as a habitat variable. Twenty-four habitat classes are identified, with large expanses of abyssal plain and smaller classes with varying topography, food supply, and substrata. We then assess habitat representativity of the current network of protected areas (called Areas of Particular Environmental Interest) in the CCZ. Several habitat classes with high nodule abundance are common in mining exploration claims, but currently receive little to no protection in APEIs. There are several large unmanaged areas containing high nodule abundance on the periphery of the CCZ, as well as smaller unmanaged areas within the central CCZ, that could be considered for protection from mining to improve habitat representativity and safeguard regional biodiversity.</jats:p

Extraordinarily high biomass benthic community on Southern Ocean seamounts

We describe a previously unknown assemblage of seamount-associated megabenthos that has by far the highest peak biomass reported in the deep-sea outside of vent communities. The assemblage was found at depths of 2–2.5 km on rocky geomorphic features off the southeast coast of Australia, in an area near the Sub-Antarctic Zone characterised by high rates of surface productivity and carbon export to the deep-ocean. These conditions, and the taxa in the assemblage, are widely distributed around the Southern mid-latitudes, suggesting the high-biomass assemblage is also likely to be widespread. The role of this assemblage in regional ecosystem and carbon dynamics and its sensitivities to anthropogenic impacts are unknown. The discovery highlights the lack of information on deep-sea biota worldwide and the potential for unanticipated impacts of deep-sea exploitation