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Objectives: Studies suggest that impairments in some of the same domains of cognition occur in different neuropsychiatric conditions, including those known to share genetic liability. Yet, direct, multi-disorder cognitive comparisons are limited, and it remains unclear whether overlapping deficits are due to comorbidity. We aimed to extend the literature by examining cognition across different neuropsychiatric conditions and addressing comorbidity. Methods: Subjects were 486 youth consecutively referred for neuropsychiatric evaluation and enrolled in the Longitudinal Study of Genetic Influences on Cognition. First, we assessed general ability, reaction time variability (RTV), and aspects of executive functions (EFs) in youth with non-comorbid forms of attention-deficit/hyperactivity disorder (ADHD), mood disorders and autism spectrum disorder (ASD), as well as in youth with psychosis. Second, we determined the impact of comorbid ADHD on cognition in youth with ASD and mood disorders. Results: For EFs (working memory, inhibition, and shifting/ flexibility), we observed weaknesses in all diagnostic groups when participants’ own ability was the referent. Decrements were subtle in relation to published normative data. For RTV, weaknesses emerged in youth with ADHD and mood disorders, but trend-level results could not rule out decrements in other conditions. Comorbidity with ADHD did not impact the pattern of weaknesses for youth with ASD or mood disorders but increased the magnitude of the decrement in those with mood disorders. Conclusions: Youth with ADHD, mood disorders, ASD, and psychosis show EF weaknesses that are not due to comorbidity. Whether such cognitive difficulties reflect genetic liability shared among these conditions requires further study. (JINS, 2018, 24, 91–103)
The success of central line-associated bloodstream infection (CLABSI) prevention programs in intensive care units (ICUs) has led to the expansion of surveillance at many hospitals. We sought to compare non-ICU CLABSI (nCLABSI) rates with national reports and describe methods of surveillance at several participating US institutions.
An electronic survey of several medical centers about infection surveillance practices and rate data for non-ICU Patients.
Ten tertiary care hospitals.
In March 2011, a survey was sent to 10 medical centers. The survey consisted of 12 questions regarding demographics and CLABSI surveillance methodology for non-ICU patients at each center. Participants were also asked to provide available rate and device utilization data.
Hospitals ranged in size from 238 to 1,400 total beds (median, 815). All hospitals reported using Centers for Disease Control and Prevention (CDC) definitions. Denominators were collected by different means: counting patients with central lines every day (5 hospitals), indirectly estimating on the basis of electronic orders (n = 4), or another automated method (n = 1). Rates of nCLABSI ranged from 0.2 to 4.2 infections per 1,000 catheter-days (median, 2.5). The national rate reported by the CDC using 2009 data from the National Healthcare Surveillance Network was 1.14 infections per 1,000 catheter-days.
Only 2 hospitals were below the pooled CLABSI rate for inpatient wards; all others exceeded this rate. Possible explanations include differences in average central line utilization or hospital size in the impact of certain clinical risk factors notably absent from the definition and in interpretation and reporting practices. Further investigation is necessary to determine whether the national benchmarks are low or whether the hospitals surveyed here represent a selection of outliers.
Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene–nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient–genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countries.
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