Risk factors for failure of outpatient parenteral antibiotic therapy (OPAT) in infective endocarditis

Objectives: To identify risk factors for failure of outpatient antibiotic therapy (OPAT) in infective endocarditis (IE). Patients and methods: We identified IE cases managed at a single centre over 12 years from a prospectively maintained database. ‘OPAT failure’ was defined as unplanned readmission or antibiotic switch due to adverse drug reaction or antibiotic resistance. We analysed patient and disease-related risk factors for OPAT failure by univariate and multivariate logistic regression. We also retrospectively collected follow-up data on adverse disease outcome (defined as IE-related death or relapse) and performed Kaplan–Meier survival analysis up to 36 months following OPAT. Results: We identified 80 episodes of OPAT in IE. Failure occurred in 25/80 episodes (31.3%). On multivariate analysis, cardiac or renal failure [pooled OR 7.39 (95% CI 1.84–29.66), P = 0.005] and teicoplanin therapy [OR 8.69 (95% CI 2.01–37.47), P = 0.004] were independently associated with increased OPAT failure. OPAT failure with teicoplanin occurred despite therapeutic plasma levels. OPAT failure predicted adverse disease outcome up to 36 months (P = 0.016 log-rank test). Conclusions: These data caution against selecting patients with endocarditis for OPAT in the presence of cardiac or renal failure and suggest teicoplanin therapy may be associated with suboptimal OPAT outcomes. Alternative regimens to teicoplanin in the OPAT setting should be further investigated

Transverse Permeability of OSB. Part II. Modeling the Effects of Density and Core Fines Content

In this work a simple rule of mixtures model to characterize the permeability of an OSB composite as a function of fines contents and density is presented. Strands and fines in the core of the board are considered to lie between two extremes, either stacked in a series configuration (series model) or side by side in a parallel configuration (parallel model), with the permeability of the composite, Ksystem, being a function of relative permeabilities of the series and parallel models. Equations for the permeability of these two configurations, Kparallel and Kseries, are developed as functions of the known permeability of 100% strands, Ks, and 100% fines, Kf, and the mass fraction of fines, Mf. Data on the permeability of the core of OSB compressed to three density classes and made with 0 and 100% fines content are used to determine the permeability of the parallel and series models, respectively. The series coefficient, α, which represents the contribution from the series model, is determined using least squares fits to the permeability data for different target densities and 25%, 50%, and 75% fines contents. α was fairly consistent, ranging from 0.47 to 0.49 for these fines contents. Kparallel increases linearly with increasing fines content and Kseries increases exponentially, in accord with the actual data. The data for the low and medium target density boards were well described by the Ksystem predictions, whereas the model underestimates the permeability of boards containing 75% or 100% fines and compressed to high target density. The model was most sensitive to changes in Mf, Kf, and Ks, with other parameters, α and density ratio (ρs/ρf), having smaller effects. The proposed model is general and could be applied to other composites of mixed particle sizes such as particleboard

Permeability of OSB. Part I. The Effects of Core Fines Content and Mat Density on Transverse Permeability

This paper reports on the effects of density and core fines content on the transverse permeability, K, of oriented strandboard (OSB), with the aim of using fines generated during the log stranding process to improve mat permeability and possibly press efficiency. Forty-five OSB panels were made in the laboratory containing five levels of fines content (0, 25, 50, 75, and 100%) and compressed to three target density levels (low—450, medium—550, and high—650 kg/m3). Both density and fines content and their interaction significantly influenced Kcore, which increased exponentially with fines content at each density level. Above 75% fines, density level no longer had any significant effect on Kcore, indicating that as the mat is compressed, the presence of fines maintains a more interconnected void system through which gas can pass. The rate of heat transfer to the core was affected by board thickness but contrary to expectations, not by fines content. Fines content did, however, affect the accumulation of gas pressure in the high target density heavily compressed boards; maximum core gas pressure was significantly reduced if core fines content was greater than 50%

Neighborhoods of trees in circular orderings

In phylogenetics, a common strategy used to construct an evolutionary tree for a set of species X is to search in the space of all such trees for one that optimizes some given score function (such as the minimum evolution, parsimony or likelihood score). As this can be computationally intensive, it was recently proposed to restrict such searches to the set of all those trees that are compatible with some circular ordering of the set X. To inform the design of efficient algorithms to perform such searches, it is therefore of interest to find bounds for the number of trees compatible with a fixed ordering in the neighborhood of a tree that is determined by certain tree operations commonly used to search for trees: the nearest neighbor interchange (nni), the subtree prune and regraft (spr) and the tree bisection and reconnection (tbr) operations. We show that the size of such a neighborhood of a binary tree associated with the nni operation is independent of the tree’s topology, but that this is not the case for the spr and tbr operations. We also give tight upper and lower bounds for the size of the neighborhood of a binary tree for the spr and tbr operations and characterize those trees for which these bounds are attained

IMPROVE-DD: Integrating Multiple Phenotype Resources Optimises Variant Evaluation in genetically determined Developmental Disorders

Diagnosing rare developmental disorders using genome-wide sequencing data commonly necessitates review of multiple plausible candidate variants, often using ontologies of categorical clinical terms. We show that Integrating Multiple Phenotype Resources Optimizes Variant Evaluation in Developmental Disorders (IMPROVE-DD) by incorporating additional classes of data commonly available to clinicians and recorded in health records. In doing so, we quantify the distinct contributions of sex, growth, and development in addition to Human Phenotype Ontology (HPO) terms and demonstrate added value from these readily available information sources. We use likelihood ratios for nominal and quantitative data and propose a classifier for HPO terms in this framework. This Bayesian framework results in more robust diagnoses. Using data systematically collected in the Deciphering Developmental Disorders study, we considered 77 genes with pathogenic/likely pathogenic variants in ≥10 individuals. All genes showed at least a satisfactory prediction by receiver operating characteristic when testing on training data (AUC ≥ 0.6), and HPO terms were the best predictor for the majority of genes, though a minority (13/77) of genes were better predicted by other phenotypic data types. Overall, classifiers based upon multiple integrated phenotypic data sources performed better than those based upon any individual source, and importantly, integrated models produced notably fewer false positives. Finally, we show that IMPROVE-DD models with good predictive performance on cross-validation can be constructed from relatively few individuals. This suggests new strategies for candidate gene prioritization and highlights the value of systematic clinical data collection to support diagnostic programs

The comparative clinical course of pregnant and non-pregnant women hospitalised with influenza A(H1N1)pdm09 infection

Introduction: The Influenza Clinical Information Network (FLU-CIN) was established to gather detailed clinical and epidemiological information about patients with laboratory confirmed A(H1N1)pdm09 infection in UK hospitals. This report focuses on the clinical course and outcomes of infection in pregnancy.Methods: A standardised data extraction form was used to obtain detailed clinical information from hospital case notes and electronic records, for patients with PCR-confirmed A(H1N1)pdm09 infection admitted to 13 sentinel hospitals in five clinical 'hubs' and a further 62 non-sentinel hospitals, between 11th May 2009 and 31st January 2010.Outcomes were compared for pregnant and non-pregnant women aged 15-44 years, using univariate and multivariable techniques.Results: Of the 395 women aged 15-44 years, 82 (21%) were pregnant; 73 (89%) in the second or third trimester. Pregnant women were significantly less likely to exhibit severe respiratory distress at initial assessment (OR?=?0.49 (95% CI: 0.30-0.82)), require supplemental oxygen on admission (OR?=?0.40 (95% CI: 0.20-0.80)), or have underlying co-morbidities (p-trend <0.001). However, they were equally likely to be admitted to high dependency (Level 2) or intensive care (Level 3) and/or to die, after adjustment for potential confounders (adj. OR?=?0.93 (95% CI: 0.46-1.92). Of 11 pregnant women needing Level 2/3 care, 10 required mechanical ventilation and three died.Conclusions: Since the expected prevalence of pregnancy in the source population was 6%, our data suggest that pregnancy greatly increased the likelihood of hospital admission with A(H1N1)pdm09. Pregnant women were less likely than non-pregnant women to have respiratory distress on admission, but severe outcomes were equally likely in both groups

The complexity of selection at the major primate β-defensin locus

BACKGROUND: We have examined the evolution of the genes at the major human β-defensin locus and the orthologous loci in a range of other primates and mouse. For the first time these data allow us to examine selective episodes in the more recent evolutionary history of this locus as well as the ancient past. We have used a combination of maximum likelihood based tests and a maximum parsimony based sliding window approach to give a detailed view of the varying modes of selection operating at this locus. RESULTS: We provide evidence for strong positive selection soon after the duplication of these genes within an ancestral mammalian genome. Consequently variable selective pressures have acted on β-defensin genes in different evolutionary lineages, with episodes both of negative, and more rarely positive selection, during the divergence of primates. Positive selection appears to have been more common in the rodent lineage, accompanying the birth of novel, rodent-specific β-defensin genes. These observations allow a fuller understanding of the evolution of mammalian innate immunity. In both the rodent and primate lineages, sites in the second exon have been subject to positive selection and by implication are important in functional diversity. A small number of sites in the mature human peptides were found to have undergone repeated episodes of selection in different primate lineages. Particular sites were consistently implicated by multiple methods at positions throughout the mature peptides. These sites are clustered at positions predicted to be important for the specificity of the antimicrobial or chemoattractant properties of β-defensins. Surprisingly, sites within the prepropeptide region were also implicated as being subject to significant positive selection, suggesting previously unappreciated functional significance for this region. CONCLUSIONS: Identification of these putatively functional sites has important implications for our understanding of β-defensin function and for novel antibiotic design

Manganese-Enhanced Magnetic Resonance Imaging in Takotsubo Syndrome

Acknowledgments The authors thank the Edinburgh Imaging Facility. Sources of Funding This work and T. Singh, S. Joshi, and Drs Dweck and Newby are supported by the British Heart Foundation (grants FS/17/19/32641, CS/17/1/32445, RG/16/10/32375, RE/18/5/34216, FS/ICRF/20/26002, and FS/SCRF/21/32010). T. Singh is supported by the Medical Research Council (grant MR/T029153/1). Dr Newby is the recipient of a Wellcome Trust Senior Investigator Award (WT103782AIA). Dr McCann is supported by an NIHR Research Professorship (08-2017-ST2-007). The Edinburgh Clinical Research Facilities and Edinburgh Imaging Facility are supported by the National Health Service Research Scotland through the National Health Service Lothian Health Board.Peer reviewe