Type 2 Diabetes, Metabolic traits and Risk of Heart Failure:a Mendelian Randomization study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Fast interior point solution of quadratic programming problems arising from PDE-constrained optimization

Interior point methods provide an attractive class of approaches for solving linear, quadratic and nonlinear programming problems, due to their excellent efficiency and wide applicability. In this paper, we consider PDE-constrained optimization problems with bound constraints on the state and control variables, and their representation on the discrete level as quadratic programming problems. To tackle complex problems and achieve high accuracy in the solution, one is required to solve matrix systems of huge scale resulting from Newton iteration, and hence fast and robust methods for these systems are required. We present preconditioned iterative techniques for solving a number of these problems using Krylov subspace methods, considering in what circumstances one may predict rapid convergence of the solvers in theory, as well as the solutions observed from practical computations

Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations.

BACKGROUND: The high burden of malaria and limited funding means there is a necessity to maximize the allocative efficiency of malaria control programmes. Quantitative tools are urgently needed to guide budget allocation decisions. METHODS: A geospatial epidemic model was coupled with costing data and an optimization algorithm to estimate the optimal allocation of budgeted and projected funds across all malaria intervention approaches. Interventions included long-lasting insecticide-treated nets (LLINs), indoor residual spraying (IRS), intermittent presumptive treatment during pregnancy (IPTp), seasonal mass chemoprevention in children (SMC), larval source management (LSM), mass drug administration (MDA), and behavioural change communication (BCC). The model was applied to six geopolitical regions of Nigeria in isolation and also the nation as a whole to minimize incidence and malaria-attributable mortality. RESULTS: Allocative efficiency gains could avert approximately 84,000 deaths or 15.7 million cases of malaria in Nigeria over 5 years. With an additional US$300 million available, approximately 134,000 deaths or 37.3 million cases of malaria could be prevented over 5 years. Priority funding should go to LLINs, IPTp and BCC programmes, and SMC should be expanded in seasonal areas. To minimize mortality, treatment expansion is critical and prioritized over some LLIN funding, while to minimize incidence, LLIN funding remained a priority. For areas with lower rainfall, LSM is prioritized over IRS but MDA is not recommended unless all other programmes are established. CONCLUSIONS: Substantial reductions in malaria morbidity and mortality can be made by optimal targeting of investments to the right malaria interventions in the right areas

Optima Nutrition: an allocative efficiency tool to reduce childhood stunting by better targeting of nutrition-related interventions.

BACKGROUND: Child stunting due to chronic malnutrition is a major problem in low- and middle-income countries due, in part, to inadequate nutrition-related practices and insufficient access to services. Limited budgets for nutritional interventions mean that available resources must be targeted in the most cost-effective manner to have the greatest impact. Quantitative tools can help guide budget allocation decisions. METHODS: The Optima approach is an established framework to conduct resource allocation optimization analyses. We applied this approach to develop a new tool, 'Optima Nutrition', for conducting allocative efficiency analyses that address childhood stunting. At the core of the Optima approach is an epidemiological model for assessing the burden of disease; we use an adapted version of the Lives Saved Tool (LiST). Six nutritional interventions have been included in the first release of the tool: antenatal micronutrient supplementation, balanced energy-protein supplementation, exclusive breastfeeding promotion, promotion of improved infant and young child feeding (IYCF) practices, public provision of complementary foods, and vitamin A supplementation. To demonstrate the use of this tool, we applied it to evaluate the optimal allocation of resources in 7 districts in Bangladesh, using both publicly available data (such as through DHS) and data from a complementary costing study. RESULTS: Optima Nutrition can be used to estimate how to target resources to improve nutrition outcomes. Specifically, for the Bangladesh example, despite only limited nutrition-related funding available (an estimated $0.75 per person in need per year), even without any extra resources, better targeting of investments in nutrition programming could increase the cumulative number of children living without stunting by 1.3 million (an extra 5%) by 2030 compared to the current resource allocation. To minimize stunting, priority interventions should include promotion of improved IYCF practices as well as vitamin A supplementation. Once these programs are adequately funded, the public provision of complementary foods should be funded as the next priority. Programmatic efforts should give greatest emphasis to the regions of Dhaka and Chittagong, which have the greatest number of stunted children. CONCLUSIONS: A resource optimization tool can provide important guidance for targeting nutrition investments to achieve greater impact

Predicting Distribution of Aedes Aegypti and Culex Pipiens Complex, Potential Vectors of Rift Valley Fever Virus in Relation to Disease Epidemics in East Africa.

The East African region has experienced several Rift Valley fever (RVF) outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. DIVERSE ECOLOGICAL NICHE MODELLING TECHNIQUES HAVE BEEN DEVELOPED FOR THIS PURPOSE: we present a maximum entropy (Maxent) approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex) responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods

Matching Schur complement approximations for certain saddle-point systems

The solution of many practical problems described by mathematical models requires approximation methods that give rise to linear(ized) systems of equations, solving which will determine the desired approximation. This short contribution describes a particularly effective solution approach for a certain class of so-called saddle-point linear systems which arises in different contexts

Medication administration errors for older people in long-term residential care

Background Older people in long-term residential care are at increased risk of medication errors. The purpose of this study was to evaluate a computerised barcode medication management system designed to improve drug administrations in residential and nursing homes, including comparison of error rates and staff awareness in both settings. Methods All medication administrations were recorded prospectively for 345 older residents in thirteen care homes during a 3-month period using the computerised system. Staff were surveyed to identify their awareness of administration errors prior to system introduction. Overall, 188,249 attempts to administer medication were analysed to determine the prevalence of potential medication administration errors (MAEs). Error classifications included attempts to administer medication at the wrong time, to the wrong person or discontinued medication. Analysis compared data at residential and nursing home level and care and nursing staff groups. Results Typically each resident was exposed to 206 medication administration episodes every month and received nine different drugs. Administration episodes were more numerous (p < 0.01) in nursing homes (226.7 per resident) than in residential homes (198.7). Prior to technology introduction, only 12% of staff administering drugs reported they were aware of administration errors being averted in their care home. Following technology introduction, 2,289 potential MAEs were recorded over three months. The most common MAE was attempting to give medication at the wrong time. On average each resident was exposed to 6.6 potential errors. In total, 90% of residents were exposed to at least one MAE with over half (52%) exposed to serious errors such as attempts to give medication to the wrong resident. MAEs rates were significantly lower (p < 0.01) in residential homes than nursing homes. The level of non-compliance with system alerts was low in both settings (0.075% of administrations) demonstrating virtually complete error avoidance. Conclusion Potentially inappropriate administration of medication is a serious problem in long-term residential care. A computerised barcode system can accurately and automatically detect inappropriate attempts to administer drugs to residents. This tool can reliably be used by care staff as well as nurses to improve quality of care and patient safety

CMB Telescopes and Optical Systems

The cosmic microwave background radiation (CMB) is now firmly established as a fundamental and essential probe of the geometry, constituents, and birth of the Universe. The CMB is a potent observable because it can be measured with precision and accuracy. Just as importantly, theoretical models of the Universe can predict the characteristics of the CMB to high accuracy, and those predictions can be directly compared to observations. There are multiple aspects associated with making a precise measurement. In this review, we focus on optical components for the instrumentation used to measure the CMB polarization and temperature anisotropy. We begin with an overview of general considerations for CMB observations and discuss common concepts used in the community. We next consider a variety of alternatives available for a designer of a CMB telescope. Our discussion is guided by the ground and balloon-based instruments that have been implemented over the years. In the same vein, we compare the arc-minute resolution Atacama Cosmology Telescope (ACT) and the South Pole Telescope (SPT). CMB interferometers are presented briefly. We conclude with a comparison of the four CMB satellites, Relikt, COBE, WMAP, and Planck, to demonstrate a remarkable evolution in design, sensitivity, resolution, and complexity over the past thirty years.Comment: To appear in: Planets, Stars and Stellar Systems (PSSS), Volume 1: Telescopes and Instrumentatio