73 research outputs found
Estimating basis functions in massive fields under the spatial random effects model
Spatial prediction is commonly achieved under the assumption of a Gaussian random field (GRF) by obtaining maximum likelihood estimates of parameters, and then using the kriging equations to arrive at predicted values. For massive datasets, fixed rank kriging using the Expectation-Maximization (EM) algorithm for estimation has been proposed as an alternative to the usual but computationally prohibitive kriging method. The method reduces computation cost of estimation by redefining the spatial process as a linear combination of basis functions and spatial random effects. A disadvantage of this method is that it imposes constraints on the relationship between the observed locations and the knots. We develop an alternative method that utilizes the Spatial Mixed Effects (SME) model, but allows for additional flexibility by estimating the range of the spatial dependence between the observations and the knots via an Alternating Expectation Conditional Maximization (AECM) algorithm. Experiments show that our methodology improves estimation without sacrificing prediction accuracy while also minimizing the additional computational burden of extra parameter estimation. The methodology is applied to a temperature data set archived by the United States National Climate Data Center, with improved results over previous methodology
Use of mechanical circulatory support in patients with non-ischaemic cardiogenic shock
Aims Despite its high incidence and mortality risk, there is no evidence-based treatment for non-ischaemic cardiogenic shock (CS). The aim of this study was to evaluate the use of mechanical circulatory support (MCS) for non-ischaemic CS treatment.Methods and results In this multicentre, international, retrospective study, data from 890 patients with non-ischaemic CS, defined as CS due to severe de-novo or acute-on-chronic heart failure with no need for urgent revascularization, treated with or without active MCS, were collected. The association between active MCS use and the primary endpoint of 30-day mortality was assessed in a 1:1 propensity-matched cohort. MCS was used in 386 (43%) patients. Patients treated with MCS presented with more severe CS (37% vs. 23% deteriorating CS, 30% vs. 25% in extremis CS) and had a lower left ventricular ejection fraction at baseline (21% vs. 25%). After matching, 267 patients treated with MCS were compared with 267 patients treated without MCS. In the matched cohort, MCS use was associated with a lower 30-day mortality (hazard ratio 0.76, 95% confidence interval 0.59-0.97). This finding was consistent through all tested subgroups except when CS severity was considered, indicating risk reduction especially in patients with deteriorating CS. However, complications occurred more frequently in patients with MCS; e.g. severe bleeding (16.5% vs. 6.4%) and access-site related ischaemia (6.7% vs. 0%).Conclusion In patients with non-ischaemic CS, MCS use was associated with lower 30-day mortality as compared to medical therapy only, but also with more complications. Randomized trials are needed to validate these findings.[GRAPHICS
Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes
Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD
β-Amyloid neurotoxicity is mediated by a glutamate-triggered excitotoxic cascade in rat nucleus basalis
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