The Potential Trajectory of Carbapenem-Resistant Enterobacteriaceae, an Emerging Threat to Health-Care Facilities, and the Impact of the Centers for Disease Control and Prevention Toolkit.

Carbapenem-resistant Enterobacteriaceae (CRE), a group of pathogens resistant to most antibiotics and associated with high mortality, are a rising emerging public health threat. Current approaches to infection control and prevention have not been adequate to prevent spread. An important but unproven approach is to have hospitals in a region coordinate surveillance and infection control measures. Using our Regional Healthcare Ecosystem Analyst (RHEA) simulation model and detailed Orange County, California, patient-level data on adult inpatient hospital and nursing home admissions (2011-2012), we simulated the spread of CRE throughout Orange County health-care facilities under 3 scenarios: no specific control measures, facility-level infection control efforts (uncoordinated control measures), and a coordinated regional effort. Aggressive uncoordinated and coordinated approaches were highly similar, averting 2,976 and 2,789 CRE transmission events, respectively (72.2% and 77.0% of transmission events), by year 5. With moderate control measures, coordinated regional control resulted in 21.3% more averted cases (n = 408) than did uncoordinated control at year 5. Our model suggests that without increased infection control approaches, CRE would become endemic in nearly all Orange County health-care facilities within 10 years. While implementing the interventions in the Centers for Disease Control and Prevention's CRE toolkit would not completely stop the spread of CRE, it would cut its spread substantially, by half

Producing valid statistics when legislation, culture, and medical practices differ for births at or before the threshold of survival: Report of a European workshop

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Continuous growth reference from 24th week of gestation to 24 months by gender

<p>Abstract</p> <p>Background</p> <p>Growth charts and child growth assessment have become prime global instruments in child health practice over the 30 years. An updated, continuous growth standard that bridges size at birth values with postnatal growth values can improve child growth screening and monitoring.</p> <p>Methods</p> <p>This novel growth chart was constructed from two sources of information. Size at birth (weight, length and head circumference) reference values were updated based on information of normal deliveries (i.e. singleton live births without severe congenital malformation, with healthy mothers and born vaginally) from the Swedish Medical Birth Registry, 1990–1999 (n = 810393). Weight was evaluated using logarithmic transformation as for postnatal weight. Standard deviations were estimated from data within the empirical mean ± 1.0 SD for each gestational week and gender. These values were smoothed by empirical curve-fitting together with values from our recently published postnatal growth reference including 3650 longitudinally followed children from birth to final height <abbrgrp><abbr bid="B9">9</abbr></abbrgrp>. Timescale and weight axes were made logarithmic in order to magnify the early time part of the graph.</p> <p>Results</p> <p>This study presents the first continuous gender specific growth chart from birth irrespective of gestational age at birth until 2 years of age for weight, length and head circumference. Birth weight at 40 weeks of gestation increased approximately 100 gram and length increased only 1 mm compared with earlier Swedish reference from 1977–81. The curve is now less S-shaped as compared with earlier curves and compared with 4 curves from other countries and with more constant variation over the whole range.</p> <p>Conclusion</p> <p>Our values picture the unrestricted pattern of growth improving the detection of a deviating growth pattern, when the growth of an individual infant is plotted on the charts. Especially for very preterm infants age corrected growth can be more easily evaluated although it must be recognized that the early comparison is with what is estimated as normal growth in uterus. The reference values are useful in child health care systems for population screening, but also in research or in the clinic for evaluating various growth promoting interventions – either nutritional, surgical or therapeutic – that might affect a child in early life.</p

Quantum Electrodynamics of the Helium Atom

Using singlet S states of the helium atom as an example, I describe precise calculation of energy levels in few-electron atoms. In particular, a complete set of effective operators is derived which generates O(m*alpha^6) relativistic and radiative corrections to the Schr"odinger energy. Average values of these operators can be calculated using a variational Schr"odinger wave function.Comment: 23 pages, revte

The association between the food environment and adherence to healthy diet quality: the Maastricht Study

Abstract Objective: The purpose of this study is to determine if healthier neighbourhood food environments are associated with healthier diet quality. Design: This was a cross-sectional study using linear regression models to analyse data from the Maastricht Study. Diet quality was assessed using data collected with a FFQ to calculate the Dutch Healthy Diet (DHD). A buffer zone encompassing a 1000 m radius was created around each participant home address. The Food Environment Healthiness Index (FEHI) was calculated using a Kernel density analysis within the buffers of available food outlets. The association between the FEHI and the DHD score was analysed and adjusted for socio-economic variables. Setting: The region of Maastricht including the surrounding food retailers in the Netherlands. Participants: 7367 subjects aged 40–75 years in the south of the Netherlands. Results: No relationship was identified between either the FEHI (B = 0·62; 95 % CI = –2·54, 3·78) or individual food outlets, such as fast food (B = –0·07; 95 % CI = –0·20, 0·07) and diet quality. Similar null findings using the FEHI were identified at the 500 m (B = 0·95; 95 % CI = –0·85, 2·75) and 1500 m (B = 1·57; 95 % CI = –3·30, 6·44) buffer. There was also no association between the food environment and individual items of the DHD including fruits, vegetables and sugar-sweetened beverages. Conclusion: The food environment in the Maastricht area appeared marginally unhealthy, but the differences in the food environment were not related to the quality of food that participants reported as intake

Perinatal health monitoring through a European lens: eight lessons from the Euro-Peristat report on 2015 births

International audienceNo abstract availabl

Childhood cancer in the offspring born in 1921–1984 to US radiologic technologists

We examined the risk of childhood cancer (<20 years) among 105 950 offspring born in 1921–1984 to US radiologic technologist (USRT) cohort members. Parental occupational in utero and preconception ionising radiation (IR) testis or ovary doses were estimated from work history data, badge dose data, and literature doses (the latter doses before 1960). Female and male RTs reported a total of 111 and 34 haematopoietic malignancies and 115 and 34 solid tumours, respectively, in their offspring. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards regression. Leukaemia (n=63) and solid tumours (n=115) in offspring were not associated with maternal in utero or preconception radiation exposure. Risks for lymphoma (n=44) in those with estimated doses of <0.2, 0.2–1.0, and >1.0 mGy vs no exposure were non-significantly elevated with HRs of 2.3, 1.8, and 2.7. Paternal preconception exposure to estimated cumulative doses above the 95th percentile (⩾82 mGy, n=6 cases) was associated with a non-significant risk of childhood cancer of 1.8 (95% CI 0.7–4.6). In conclusion, we found no convincing evidence of an increased risk of childhood cancer in the offspring of RTs in association with parental occupational radiation exposure

Predicting Hospital-Acquired Infections by Scoring System with Simple Parameters

BACKGROUND: Hospital-acquired infections (HAI) are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR) and validated by Artificial Neural Networks (ANN) simultaneously. METHODOLOGY/PRINCIPAL FINDINGS: A total of 476 patients from all the 806 HAI inpatients were included for the study between 2004 and 2005. A sample of 1,376 non-HAI inpatients was randomly drawn from all the admitted patients in the same period of time as the control group. External validation of 2,500 patients was abstracted from another academic teaching center. Sixteen variables were extracted from the Electronic Health Records (EHR) and fed into ANN and LR models. With stepwise selection, the following seven variables were identified by LR models as statistically significant: Foley catheterization, central venous catheterization, arterial line, nasogastric tube, hemodialysis, stress ulcer prophylaxes and systemic glucocorticosteroids. Both ANN and LR models displayed excellent discrimination (area under the receiver operating characteristic curve [AUC]: 0.964 versus 0.969, p = 0.507) to identify infection in internal validation. During external validation, high AUC was obtained from both models (AUC: 0.850 versus 0.870, p = 0.447). The scoring system also performed extremely well in the internal (AUC: 0.965) and external (AUC: 0.871) validations. CONCLUSIONS: We developed a scoring system to predict HAI with simple parameters validated with ANN and LR models. Armed with this scoring system, infectious disease specialists can more efficiently identify patients at high risk for HAI during hospitalization. Further, using parameters either by observation of medical devices used or data obtained from EHR also provided good prediction outcome that can be utilized in different clinical settings

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits