Inpatient urine cultures are frequently performed without urinalysis or microscopy: Findings from a large academic medical center

OBJECTIVETo describe the frequency of urine cultures performed in inpatients without additional testing for pyuriaDESIGNRetrospective cohort studySETTINGA 1,250-bed academic tertiary referral centerPATIENTSHospitalized adultsMETHODSThis study included urine cultures drawn on 4 medical and 2 surgical wards from 2009 to 2013 and in the medical and surgical intensive care units (ICUs) from 2012 to 2013. Patient and laboratory data were abstracted from the hospital’s medical informatics database. We identified catheter-associated urinary tract infections (CAUTIs) in the ICUs by routine infection prevention surveillance. Cultures without urinalysis or urine microscopy were defined as “isolated.” The primary outcome was the proportion of isolated urine cultures obtained. We used multivariable logistic regression to assess predictors of isolated cultures.RESULTSDuring the study period, 14,743 urine cultures were obtained (63.5 cultures per 1,000 patient days) during 11,820 patient admissions. Of these, 2,973 cultures (20.2%) were isolated cultures. Of the 61 CAUTIs identified, 31 (50.8%) were identified by an isolated culture. Predictors for having an isolated culture included male gender (adjusted odds ratio [aOR], 1.22; 95%; confidence interval [CI], 1.11–1.35], urinary catheterization (aOR, 2.15; 95% CI, 1.89–2.46), ICU admission (medical ICU aOR, 1.72; 95% CI, 1.47–2.00; surgical ICU aOR, 1.82; 95% CI, 1.51–2.19), and obtaining the urine culture ≥1 calendar day after admission (1–7 days aOR, 1.91; 95% CI. 1.71–2.12; &gt;7 days after admission aOR, 2.81; 95% CI, 2.37–3.34).CONCLUSIONSIsolated urine cultures are common in hospitalized patients, particularly in patients with urinary catheters and those in ICUs. Interventions targeting inpatient culturing practices may improve the diagnosis of urinary tract infections.Infect Control Hosp Epidemiol2017;38:455–460</jats:sec

The contribution of fibre components to water absorption of wheat grown in the UK

Background and objectives The water absorption (WA) of white wheat flour is a major factor affecting processing quality, and millers, therefore, process their wheat to achieve the required level. Although it is likely that WA is determined by the amounts and compositions of three major grain components, starch, protein, and arabinoxylan, the contribution of the latter is not agreed and not recognized in the widely used Farrand equation. Findings We have measured a range of parameters related to fiber amount and composition and tested the ability of these to improve the prediction of WA using a modified Farrand equation. The addition of a range of single fiber traits improved the prediction of WA from a baseline of 82.98% to a maximum of 86.78%, but inclusion of all fiber traits as PCs resulted in a further improvement to 90%. Inclusion of the PCs also accounted for variation in WA between harvest years. The greatest improvement from inclusion of a single trait was observed with β‐glucan, the inclusion of arabinogalactan peptide (AGP) also resulted in improved prediction of WA. Conclusions The study shows that fiber components contribute to variation in WA, including differences between harvest years, but that β‐glucan and AGP have similar or greater impacts than AX. Significance and novelty The study dissects the contributions of AX amount and composition to WA and demonstrates a contribution of b‐glucan for the first time

Consortium for the Study of Pregnancy Treatments (Co-OPT): An international birth cohort to study the effects of antenatal corticosteroids

BACKGROUND: Antenatal corticosteroids (ACS) are widely prescribed to improve outcomes following preterm birth. Significant knowledge gaps surround their safety, long-term effects, optimal timing and dosage. Almost half of women given ACS give birth outside the "therapeutic window" and have not delivered over 7 days later. Overtreatment with ACS is a concern, as evidence accumulates of risks of unnecessary ACS exposure. METHODS: The Consortium for the Study of Pregnancy Treatments (Co-OPT) was established to address research questions surrounding safety of medications in pregnancy. We created an international birth cohort containing information on ACS exposure and pregnancy and neonatal outcomes by combining data from four national/provincial birth registers and one hospital database, and follow-up through linked population-level data from death registers and electronic health records. RESULTS AND DISCUSSION: The Co-OPT ACS cohort contains 2.28 million pregnancies and babies, born in Finland, Iceland, Israel, Canada and Scotland, between 1990 and 2019. Births from 22 to 45 weeks' gestation were included; 92.9% were at term (≥ 37 completed weeks). 3.6% of babies were exposed to ACS (67.0% and 77.9% of singleton and multiple births before 34 weeks, respectively). Rates of ACS exposure increased across the study period. Of all ACS-exposed babies, 26.8% were born at term. Longitudinal childhood data were available for 1.64 million live births. Follow-up includes diagnoses of a range of physical and mental disorders from the Finnish Hospital Register, diagnoses of mental, behavioural, and neurodevelopmental disorders from the Icelandic Patient Registers, and preschool reviews from the Scottish Child Health Surveillance Programme. The Co-OPT ACS cohort is the largest international birth cohort to date with data on ACS exposure and maternal, perinatal and childhood outcomes. Its large scale will enable assessment of important rare outcomes such as perinatal mortality, and comprehensive evaluation of the short- and long-term safety and efficacy of ACS

Consortium for the Study of Pregnancy Treatments (Co-OPT) : An international birth cohort to study the effects of antenatal corticosteroids

Acknowledgments We are grateful to the Co-OPT collaborators from Finland, Iceland, Israel, Nova Scotia, and Scotland, who have provided high-quality patient data, without which the Co-OPT ACS cohort would not have been possible. We acknowledge Public Health Scotland for providing us with a secure data analytical platform in which to undertake this research and are particularly grateful to Anna Schneider who has been the data controller for this project. Co-OPT collaborators: Karel Allegaert (Belgium), Jasper Been (Netherlands), David Burgner (Australia), Sohinee Bhattacharya (UK), Kate Duhig (UK), Kristjana Einarsdóttir (Iceland), John Fahey (Canada), Lani Florian (UK), Abigail Fraser (UK), Mika Gissler (Finland), Cynthia Gyamfi-Bannerman (USA), Bo Jacobsson (Sweden), Eyal Krispin (Israel), Stefan Kuhle (Canada), Marius Lahti-Pulkkinen (Finland), Jessica Miller (Australia), Ben Mol (Australia), Sarah Murray (UK), Jane Norman (UK), Lars Henning Pedersen (Denmark), Richard Riley (UK), Devender Roberts (UK), Ewoud Schuit (Netherlands), Aziz Sheikh (UK), Ting Shi (UK), Joshua Vogel (Australia), Rachael Wood (UK), John Wright (UK), Helga Zoega (Australia). Funding Information: The Co-OPT ACS study is funded through a Wellcome Trust Clinical Career Development Fellowship grant (Funding Reference number 209560/Z/17) awarded to Sarah J Stock. The funders had no role in study design, data collection, data analysis, decision to publish, or preparation of the manuscript. The Sponsor of the study is the University of Edinburgh (www.ed.ac. uk), Sponsor reference AC19119. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.Peer reviewedPublisher PD

Державне регулювання системи факторів оцінки та мінімізації ризиків легалізації коштів, одержаних злочинним шляхом в процесі фінансового моніторингу комерційних банків України

Основною ціллю данної статті є формулювання важливості впливу чітко визначених факторів, які впливають на процеси фінансового моніторингу в комерційних банків України. Виходячи з поставлених цілей, завданнями даної статті є розроблення моделі оцінки ризиків банківської установи щодо протидії легалізації коштів одержаних злочинним шляхом в системі внутрішньобанківського фінансового моніторингу, та використання в подальшому запропонованих стратегій управління наслідками даних ризиків

STROBE-X: A probe-class mission for x-ray spectroscopy and timing on timescales from microseconds to years

We describe the Spectroscopic Time-Resolving Observatory for Broadband Energy X-rays (STROBE-X), a probeclass mission concept that will provide an unprecedented view of the X-ray sky, performing timing and spectroscopy over both a broad energy band (0.2-30 keV) and a wide range of timescales from microseconds to years. STROBE-X comprises two narrow-field instruments and a wide field monitor. The soft or low-energy band (0.2-12 keV) is covered by an array of lightweight optics (3-m focal length) that concentrate incident photons onto small solid-state detectors with CCD-level (85-175 eV) energy resolution, 100 ns time resolution, and low background rates. This technology has been fully developed for NICER and will be scaled up to take advantage of the longer focal length of STROBE-X. The higher-energy band (2-30 keV) is covered by large-area, collimated silicon drift detectors that were developed for the European LOFT mission concept. Each instrument will provide an order of magnitude improvement in effective area over its predecessor (NICER in the soft band and RXTE in the hard band). Finally, STROBE-X offers a sensitive wide-field monitor (WFM), both to act as a trigger for pointed observations of X-ray transients and also to provide high duty-cycle, high time-resolution, and high spectral-resolution monitoring of the variable X-ray sky. The WFM will boast approximately 20 times the sensitivity of the RXTE All-Sky Monitor, enabling multi-wavelength and multi-messenger investigations with a large instantaneous field of view. This mission concept will be presented to the 2020 Decadal Survey for consideration

Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants