Translating Research to Practice for Children With Autism Spectrum Disorder: Part 2: Behavior Management in Home and Health Care Settings

Introduction Managing home and health care for children with autism spectrum disorder can be challenging because of the range of symptoms and behaviors exhibited. Method This article presents an overview of the emerging science related to the methods to foster family self-management of common concerns regarding activities of daily living and behaviors, as well as for the health care provider in primary and acute health care settings. Results Recommendations are provided to enhance the overall delivery of services, including understanding and managing a child\u27s challenging behaviors, and supporting family management of common activities of daily living and behaviors. Discussion Health care providers\u27 knowledge of evidence-based recommendations for providing care, supporting family self-management of common concerns, and referral heighten the likelihood of better outcomes for children with autism spectrum disorder

Translating Research to Practice for Children With Autism Spectrum Disorder: Part I: Definition, Associated Behaviors, Prevalence, Diagnostic Process, and Interventions

Introduction The number of children with autism spectrum disorder (ASD) is rising, along with the potential for challenging behaviors during health care encounters. Method We present an overview of the emerging science related to ASD diagnosis and interventions for children with ASD. Results Emerging science on ASD reveals common associated challenging behaviors, increasing prevalence, emphasis on early diagnosis at 18 to 24 months of age, changes in the diagnostic process with criteria from the Diagnostic and Statistical Manual of Mental Disorders, 5th edition, and interventions with medication, education, and behavior management. Discussion Family and health care provider preparation strategies facilitate care of children with ASD and their families. Early diagnosis at 18 to 24 months of age and evidence-based interventions contribute to best outcomes for children and families. Health care providers must be aware of the state of the science for diagnosis and best practices to provide family-centered care for this growing population

Vitamin K Supplementation in Postmenopausal Women with Osteopenia (ECKO Trial): A Randomized Controlled Trial

Angela Cheung and colleagues investigate whether vitamin K1 can prevent bone loss among postmenopausal women with osteopenia

Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder

Objective: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, evaluate, and validate an automated algorithm for determining an Autism Spectrum Disorder (ASD) patient cohort from EHR. We demonstrate its utility via the largest investigation to date of the co-occurrence patterns of medical comorbidities in ASD. Methods: We extracted ICD-9 codes and concepts derived from the clinical notes. A gold standard patient set was labeled by clinicians at Boston Children’s Hospital (BCH) (N = 150) and Cincinnati Children’s Hospital and Medical Center (CCHMC) (N = 152). Two algorithms were created: (1) rule-based implementing the ASD criteria from Diagnostic and Statistical Manual of Mental Diseases 4th edition, (2) predictive classifier. The positive predictive values (PPV) achieved by these algorithms were compared to an ICD-9 code baseline. We clustered the patients based on grouped ICD-9 codes and evaluated subgroups. Results: The rule-based algorithm produced the best PPV: (a) BCH: 0.885 vs. 0.273 (baseline); (b) CCHMC: 0.840 vs. 0.645 (baseline); (c) combined: 0.864 vs. 0.460 (baseline). A validation at Children’s Hospital of Philadelphia yielded 0.848 (PPV). Clustering analyses of comorbidities on the three-site large cohort (N = 20,658 ASD patients) identified psychiatric, developmental, and seizure disorder clusters. Conclusions: In a large cross-institutional cohort, co-occurrence patterns of comorbidities in ASDs provide further hypothetical evidence for distinct courses in ASD. The proposed automated algorithms for cohort selection open avenues for other large-scale EHR studies and individualized treatment of ASD

Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Using Incentives to Influence Children to Bring Fruit and Vegetables from Home for School Snack

Color poster with text, images, graphs, and tables.The United States Department of Agriculture (USDA) initiated its Fresh Fruit and Vegetable Program (FFVP) in 2002 as part of a broad effort to address poor nutrition and rising obesity rates among children. Previous research in Wisconsin found increased intake due to FFVP; however, even after six months of participating in the program, students did not bring fruit and vegetables from home to eat on days when one was not provided for free through the FFVP. This study investigates whether incentives can influence children to bring fruit and vegetables from home to eat on days when they were not served one for free.University of Wisconsin--Eau Claire Office of Research and Sponsored Programs; Xcel Energy of Eau Claire; Northwestern Bank of Chippewa Falls

Interview with Judy (Mike) Reinhold-Tucker (Class of 1975) by Aisha Rickford

Judy Mike Reinhold Tucker reflects on her one year at Bowdoin, during which she was a member of the first class of women at Bowdoin. She also talks about the transition, both in weather and academics, as she moved from Trinidad to the United States when she finished high school in 1969 in Washington D.C. and then came to Bowdoin on a full scholarship in 1970. Despite only attending Bowdoin for one year, Tucker talks about how Bowdoin shaped her path to be pre med, her passion for education, and the AfAm community at Bowdoin that made her feel at home for the short time that she was here