Risk of death during and after opiate substitution treatment in primary care: prospective observational study in UK General Practice Research Database

Objective To investigate the effect of opiate substitution treatment at the beginning and end of treatment and according to duration of treatment

High Dimensional Integer Ambiguity Resolution: A First Comparison between LAMBDA and Bernese

The LAMBDA method for integer least-squares ambiguity resolution has been widely used in a great variety of Global Navigation Satellite System (GNSS) applications. The popularity of this method stems from its numerical efficiency and its guaranteed optimality in the sense of maximising the success probability of integer ambiguity estimation. In the past two decades, the LAMBDA method has been typically used in cases where the number of ambiguities is less than several tens. With the advent of denser network processing and the availability of multi-frequency, multi-GNSS systems, it is important to understand LAMBDA’s performance in high dimensional spaces. In this contribution, we will address this issue using real GPS data based on the Bernese software. We have embedded the LAMBDA method into the Bernese software and compared their ambiguity resolution performances.Twelve day dual frequency GPS data with a sampling interval of 30 s was used in the experiment, which was collected from a network of 19 stations in the Perth area of Western Australia with an average baseline length of 380 km. Different experimental scenarios were examined and tested with different observation spans, which represent the different ambiguity dimensions. The results showed that LAMBDA is still efficient even when the number of ambiguities is more than 100, and that the baseline repeatability obtained with the ambiguities resolved from the LAMBDA method agreed well with that of Bernese. Therefore, for future dense network processing, the easy-to-use LAMBDA method should be considered as an alternative to baseline-per-baseline methods as those used in e.g. the Bernese software

The impact of opiate substitution treatment on mortality risk in drug addicts: a natural experiment study

Background Opiate substitution treatment (OST) is the main treatment for people addicted to heroin and other opioid drugs. However, there is limited information on how the delivery of this treatment affects mortality risk.Objectives To investigate the associations of mortality risk with periods during treatment and following cessation of treatment, medication type, co-prescription of other medication and dosing regimens during titration and detoxification. The trends with time of prescribed medication, dose and treatment duration were also explored.Design Prospective longitudinal observational study.Setting UK primary care between 1998 and 2014.Participants A total of 12,780 patients receiving methadone, buprenorphine or dihydrocodeine.Main outcome measures All-cause mortality relating to 657 deaths and drug-related poisoning relating to 113 deaths.Data sources Clinical Practice Research Datalink with linked information on cause of death from the Office for National Statistics.Results For both outcomes, the lowest mortality risk was observed after 4 weeks of treatment and the highest risk was observed in the first 4 weeks following cessation of treatment [e.g. for drug-related poisoning, incidence rate ratio (IRR) 8.15, 95% confidence interval (CI) 5.45 to 12.19]. There was evidence that the treatment period risks varied with OST medication. The largest difference in risk was for the first 4 weeks of treatment for both outcomes, with patients on buprenorphine being at lower risk than those on methadone (e.g. for drug-related poisoning, IRR 0.08, 95% CI 0.01 to 0.48). The co-prescription of benzodiazepines was associated with linearly increasing the risk of drug-related deaths by dose (IRR 2.02, 95% CI 1.66 to 2.47), whereas z-drugs (zolpidem, zopiclone and zaleplon) were associated with increased risk of both all-cause (IRR 1.83, 95% CI 1.59 to 2.12) and drug-related (IRR 3.31, 95% CI 2.45 to 4.47) mortality. There was weak evidence that higher initial and final doses were associated with increased all-cause mortality risk. In the first 4 weeks of treatment, the risk increased by 4% for each 5-mg increment in methadone dose (1-mg increase in buprenorphine) (hazard ratio 1.04, 95% CI 1.00 to 1.09). In the first 4 weeks after treatment ceased, a similar increment in final dose increased the risk by 3% (hazard ratio 1.03, 95% CI 0.99 to 1.07). There were too few deaths to evaluate the effects on drug-related poisoning. The proportion of OST patients receiving buprenorphine increased between 1998 and 2006. Median treatment duration was consistently shorter for buprenorphine than for methadone for each year studied (overall median duration of 48 and 106 days, respectively).Limitations As this was an observational study, the possibility remains of bias from unmeasured factors, which covariate adjustment and inverse probability weighting can eliminate only partially.Conclusions Using buprenorphine as an alternative to methadone may not reduce mortality overall despite resulting in lower IRRs from shorter treatment duration. Clinical guidance needs to consider strengthening warnings about the co-prescription of a range of drugs for OST patients.Future work Our analyses need to be replicated using other clinical data sets in the UK and in other countries. New interventions and trials are required to investigate improving the retention of OST patients in primary care.Funding The National Institute for Health Research Health Services and Delivery Research programme

Intestinal fatty acid binding protein as a marker for intra-abdominal pressure-related complications in patients admitted to the intensive care unit

Background: Intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) have detrimental effects on all organ systems and are associated with increased morbidity and mortality in critically ill patients admitted to an intensive care unit. Intra-bladder measurement of the intra-abdominal pressure (IAP) is currently the gold standard. However, IAH is not always indicative of intestinal ischemia, which is an early and rapidly developing complication. Sensitive biomarkers for intestinal ischemia are needed to be able to intervene before damage becomes irreversible. Gut wall integrity loss, including epithelial cell disruption and tight junctions breakdown, is an early event in intestinal damage. Intestinal Fatty Acid Binding Protein (I-FABP) is excreted in urine and blood specifically from damaged intestinal epithelial cells. Claudin-3 is a specific protein which is excreted in urine following disruption of intercellular tight junctions. This study aims to investigate if I-FABP and Claudin-3 can be used as a diagnostic tool for identifying patients at risk for IAP-related complications. Methods/Design: In a multicenter, prospective cohort study 200 adult patients admitted to the intensive care unit with at least two risk factors for IAH as defined by the World Society of the Abdominal Compartment Syndrome (WSACS) will b

Stunted microbiota and opportunistic pathogen colonization in caesarean-section birth

Immediately after birth, newborn babies experience rapid colonization by microorganisms from their mothers and the surrounding environment1. Diseases in childhood and later in life are potentially mediated by the perturbation of the colonization of the infant gut microbiota2. However, the effects of delivery via caesarean section on the earliest stages of the acquisition and development of the gut microbiota, during the neonatal period (≤1 month), remain controversial3,4. Here we report the disrupted transmission of maternal Bacteroides strains, and high-level colonization by opportunistic pathogens associated with the hospital environment (including Enterococcus, Enterobacter and Klebsiella species), in babies delivered by caesarean section. These effects were also seen, to a lesser extent, in vaginally delivered babies whose mothers underwent antibiotic prophylaxis and in babies who were not breastfed during the neonatal period. We applied longitudinal sampling and whole-genome shotgun metagenomic analysis to 1,679 gut microbiota samples (taken at several time points during the neonatal period, and in infancy) from 596 full-term babies born in UK hospitals; for a subset of these babies, we collected additional matched samples from mothers (175 mothers paired with 178 babies). This analysis demonstrates that the mode of delivery is a significant factor that affects the composition of the gut microbiota throughout the neonatal period, and into infancy. Matched large-scale culturing and whole-genome sequencing of over 800 bacterial strains from these babies identified virulence factors and clinically relevant antimicrobial resistance in opportunistic pathogens that may predispose individuals to opportunistic infections. Our findings highlight the critical role of the local environment in establishing the gut microbiota in very early life, and identify colonization with antimicrobial-resistance-containing opportunistic pathogens as a previously underappreciated risk factor in hospital births

Analysis of a threshold model of social contagion on degree-correlated networks

We analytically determine when a range of abstract social contagion models permit global spreading from a single seed on degree-correlated random networks. We deduce the expected size of the largest vulnerable component, a network's tinderbox-like critical mass, as well as the probability that infecting a randomly chosen individual seed will trigger global spreading. In the appropriate limits, our results naturally reduce to standard ones for models of disease spreading and to the condition for the existence of a giant component. Recent advances in the distributed, infinite seed case allow us to further determine the final size of global spreading events, when they occur. To provide support for our results, we derive exact expressions for key spreading quantities for a simple yet rich family of random networks with bimodal degree distributions.Comment: 7 Pages, 1 figure, submitted to Phys. Rev.

Googling the brain: discovering hierarchical and asymmetric network structures, with applications in neuroscience

Hierarchical organisation is a common feature of many directed networks arising in nature and technology. For example, a well-defined message-passing framework based on managerial status typically exists in a business organisation. However, in many real-world networks such patterns of hierarchy are unlikely to be quite so transparent. Due to the nature in which empirical data is collated the nodes will often be ordered so as to obscure any underlying structure. In addition, the possibility of even a small number of links violating any overall “chain of command” makes the determination of such structures extremely challenging. Here we address the issue of how to reorder a directed network in order to reveal this type of hierarchy. In doing so we also look at the task of quantifying the level of hierarchy, given a particular node ordering. We look at a variety of approaches. Using ideas from the graph Laplacian literature, we show that a relevant discrete optimization problem leads to a natural hierarchical node ranking. We also show that this ranking arises via a maximum likelihood problem associated with a new range-dependent hierarchical random graph model. This random graph insight allows us to compute a likelihood ratio that quantifies the overall tendency for a given network to be hierarchical. We also develop a generalization of this node ordering algorithm based on the combinatorics of directed walks. In passing, we note that Google’s PageRank algorithm tackles a closely related problem, and may also be motivated from a combinatoric, walk-counting viewpoint. We illustrate the performance of the resulting algorithms on synthetic network data, and on a real-world network from neuroscience where results may be validated biologically