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A Scoping Review of Electronic Health Records-Based Screening Algorithms for Familial Hypercholesterolemia.

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Division of Blood Disorders and Public Health Genomics, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

Background: Familial hypercholesterolemia (FH) is a common genetic disorder that is strongly associated with premature cardiovascular disease. Effective diagnosis and appropriate treatment of FH can reduce cardiovascular disease risk; however, FH is underdiagnosed. Electronic health record (EHR)-based FH screening tools have been previously described to enhance the detection of FH.

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Several studies suggest that children and adolescents with autism spectrum disorder (ASD) often present deficits in executive functions (EFs). The research on cold EF shows a high heterogeneity across different cohorts of patients as well as different study designs, while studies investigating hot EF and their relationship with different ASD phenotypes are still limited and related only to specific domains, although this concept could contribute to clarify the phenotypical variability by explaining the difficulties encountered by individuals with ASD in daily life, where stimuli are often emotionally charged. With the aim to identify specific neuropsychological profiles in children and adolescents with ASD without intellectual disability, we designed a study protocol comparing a clinical sample of individuals with ASD to aged-matched (10-17 years) typically developing controls (TDC) on a neuropsychological test battery investigating both "cold" and "hot" EF with the purpose of further investigating their relationships with ASD symptoms.

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Field studies of social behaviour are challenging due to the need to record or infer interactions between multiple individuals, often under suboptimal environmental conditions or with potential disturbance by observers. Due to the limited field techniques available, we present a novel method to quantify social behaviours in the field by comparing the counts of individuals caught in traps across multiple locations sampled simultaneously. The distribution of individuals between traps gives the extent of aggregation, and phenotypic data allow for inference of non-random assortment.

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