31 research outputs found

    Skewed X-inactivation is common in the general female population

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    X-inactivation is a well-established dosage compensation mechanism ensuring that X-chromosomal genes are expressed at comparable levels in males and females. Skewed X-inactivation is often explained by negative selection of one of the alleles. We demonstrate that imbalanced expression of the paternal and maternal X-chromosomes is common in the general population and that the random nature of the X-inactivation mechanism can be sufficient to explain the imbalance. To this end, we analyzed blood-derived RNA and whole-genome sequencing data from 79 female children and their parents from the Genome of the Netherlands project. We calculated the median ratio of the paternal over total counts at all X-chromosomal heterozygous single-nucleotide variants with coverage ≥10. We identified two individuals where the same X-chromosome was inactivated in all cells. Imbalanced expression of the two X-chromosomes (ratios ≤0.35 or ≥0.65) was observed in nearly 50% of the population. The empirically observed skewing is explained by a theoretical model where X-inactivation takes place in an embryonic stage in which eight cells give rise to the hematopoietic compartment. Genes escaping X-inactivation are expressed from both alleles and therefore demonstrate less skewing than inactivated genes. Using this characteristic, we identified three novel escapee genes (SSR4, REPS2, and SEPT6), but did not find support for many previously reported escapee genes in blood. Our collective data suggest that skewed X-inactivation is common in the general population. This may contribute to manifestation of symptoms in carriers of recessive X-linked disorders. We recommend that X-inactivation results should not be used lightly in the interpretation of X-linked variants

    Antibiotic stewardship: Measuring and improving antibiotic use in hospitals

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    Along with the emergence of antibiotic resistance, the steady decline in the discovery of new antibiotics creates one of the greatest current threats to human health. Antibiotic Stewardship Programs (ASPs) have been designed to monitor and improve the appropriateness of antibiotic use, which has been shown to be beneficially associated with patient outcomes, adverse events, resistance rates and costs. Current guidelines provide recommendations on three “building blocks” for successful stewardship stewardship prerequisites, stewardship objectives and improvement strategies. This thesis was divided into three main parts: First, we systematically developed a survey based on these three building blocks for ASPs and evaluated the current state of ASP in acute care hospitals in four European countries: the Netherlands, Slovenia, France and Italy. Second, we performed a cluster-randomized multicenter study to assess the difference in effect on length of hospital stay (LOS) and days of antibiotic therapy (DOT) between three recommended methods to measure and feedback information on hospital antibiotic use, when used as the first step of a stewardship intervention. Subsequently, we conducted a cost-benefit analysis alongside the cluster-randomized multicenter study. Third, we applied a modified-RAND Delphi procedure to systematically develop a set of four actionable quality indicators and one quantity metric for appropriate antibiotic use in adult ICUs, In addition, we developed an implementation toolbox, containing possible barriers that lead to poor performance on the selected indicators, and improvement strategies to overcome these specific barriers, with the aim to support stewardship actions aiming at increasing performance on antibiotic use. With this thesis we contributed to optimizing appropriate antibiotic use in hospitalized patients in order to reduce antibiotic resistance rates

    How to measure quantitative antibiotic use in order to support antimicrobial stewardship in acute care hospitals: a retrospective observational study

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    A cornerstone of antimicrobial stewardship programs (ASPs) is monitoring quantitative antibiotic use. Frequently used metrics are defined daily dose (DDD) and days of therapy (DOT). The purpose of this study was (1) to explore for the hospital setting the possibilities of quantitative data retrieval on the level of medical specialty and (2) to describe factors affecting the usability and interpretation of these quantitative metrics. We performed a retrospective observational study, measuring overall systemic antibiotic use at specialty level over a 1-year period, from December 1st 2014 to December 1st 2015, in one university and 13 non-university hospitals in the Netherlands. We distinguished surgical and non-surgical adult specialties. The association between DDDs, calculated from aggregated dispensing data, and DOTs, calculated from patient-level prescription data, was explored descriptively and related to organizational factors, data sources (prescription versus dispensing data), data registration, and data extraction. Twelve hospitals were able to extract dispensing data (DDD), three of which on the level of medical specialty; 13 hospitals were able to extract prescription data (DOT), 11 of which by medical specialty. A large variation in quantitative antibiotic use was found between hospitals and the correlation between DDDs and DOTs at specialty level was low. Differences between hospitals related to organizational factors, data sources, data registration, and data extraction procedures likely contributed to the variation in quantitative use and the low correlation between DDDs and DOTs. The differences in healthcare organization, data sources, data registration, and data extraction procedures contributed to the variation in reported quantitative use between hospitals. Uniform registration and extraction procedures are necessary for appropriate measurement and interpretation and benchmarking of quantitative antibiotic use
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