Accuracy of physical activity assessment during pregnancy: an observational study

BACKGROUND: Prenatal physical activity may improve maternal and infant health and lower future disease risk for both mother and baby; however, very few physical activity assessment methods have been validated for use during pregnancy. The purpose of this study was to evaluate the accuracy of a subjective physical activity record (PAR) and an objective activity monitor, against a reference standard to quantify moderate and vigorous physical activity (MVPA) in pregnant women. The reference standard was based on participant interviews to determine if a woman was an exerciser and confirmed with information obtained from the PAR and a heart rate monitor. METHODS: Fifty-two pregnant women completed a physical activity record (PAR) and wore a SenseWear(® )Mini Armband (SWA) activity monitor over a 7-day period at 18 weeks gestation. Total minutes spent in MVPA were totaled from both modalities and evaluated against the reference standard using contingency analysis and Pearson's chi-square test to evaluate the number of women meeting minimum prenatal physical activity recommendations (at least 3, 30 minute sessions of exercise per week). Both modalities were also tested individually and collectively to assess their ability as indicators of activity using empirically determined cut-offs as indicated by receiver-operator characteristic curves. These experimentally-derived criteria were also tested with Pearson's chi-square test. RESULTS: According to the reference standard, 13 of 52 participants (25%) met the criterion of 3, 30 minute sessions of volitional, moderate-intensity activity. When compared to the reference standard, both the PAR and SWA overestimated exercise status; 42 (81%) and 52 (100%) participants, respectively, achieved 90 minutes of MVPA (P < 0.0001 for both comparisons). Single-modality predictors of MVPA did not show a significant correlation. A composite predictor of MVPA offered the most favorable option for sensitivity and specificity (true positives, n = 8 and true negatives, n = 36) using cut-offs of 280 and 385 minutes/week for the PAR and SWA, respectively. CONCLUSION: Compared to the reference standard, time spent in MVPA obtained from the PAR or SWA overestimated the prevalence of women meeting prenatal exercise recommendations. The most accurate predictor of women meeting current prenatal exercise guidelines was identified by using the PAR and SWA collectively

Interprofessional communication with hospitalist and consultant physicians in general internal medicine : a qualitative study

This study helps to improve our understanding of the collaborative environment in GIM, comparing the communication styles and strategies of hospitalist and consultant physicians, as well as the experiences of providers working with them. The implications of this research are globally important for understanding how to create opportunities for physicians and their colleagues to meaningfully and consistently participate in interprofessional communication which has been shown to improve patient, provider, and organizational outcomes

DGIdb 2.0: Mining clinically relevant drug-gene interactions

The Drug–Gene Interaction Database (DGIdb, www. dgidb.org) is a web resource that consolidates dis-parate data sources describing drug–gene interac-tions and gene druggability. It provides an intuitive graphical user interface and a documented applica-tion programming interface (API) for querying these data. DGIdb was assembled through an extensive manual curation effort, reflecting the combined in-formation of twenty-seven sources. For DGIdb 2.0, substantial updates have been made to increase content and improve its usefulness as a resource for mining clinically actionable drug targets. Specif-ically, nine new sources of drug–gene interactions have been added, including seven resources specifi-cally focused on interactions linked to clinical trials. These additions have more than doubled the over-all count of drug–gene interactions. The total num-ber of druggable gene claims has also increased by 30%. Importantly, a majority of the unrestricted, publicly-accessible sources used in DGIdb are now automatically updated on a weekly basis, providing the most current information for these sources. Fi-nally, a new web view and API have been developed to allow searching for interactions by drug identifiers to complement existing gene-based search function-ality. With these updates, DGIdb represents a com-prehensive and user friendly tool for mining the druggable genome for precision medicine hypothe-sis generation

Physical Activity during Pregnancy: Impact of Applying Different Physical Activity Guidelines

Multiple guidelines and de�nitions of physical activity (PA) have been used to study the bene�ts of activity during pregnancy. e different guidelines lead to a wide range of prevalence estimates and this has led to con�icting reports about activity patterns during pregnancy. A longitudinal study was conducted to assess PA using a pattern-recognition monitor for a 7-day period at week 18 ( ) and week 35 ( ) of pregnancy. e amount of activity performed and the number of women meeting six different PA guidelines were evaluated. Adherence to PA guidelines ranged from 5 to 100% and 9 to 100% at weeks 18 and 35, respectively. All women achieved the 500 MET-minute guideline and nearly all women accumulated ≥150 minutes of weekly moderate-vigorous physical activity (MVPA) at both time points. Only 22% and 26% participated in ≥3 sessions of MVPA lasting ≥30 minutes at both time points and this further declined to 5% and 9% when the guideline was increased to ≥5 sessions of 30 minutes. e amount of PA during pregnancy varied drastically depending on which guideline was used. Further research is warranted to clearly identify the patterns of activity that are associated with healthy pregnancy outcomes

Best practices for bioinformatic characterization of neoantigens for clinical utility

Neoantigens are newly formed peptides created from somatic mutations that are capable of inducing tumor-specific T cell recognition. Recently, researchers and clinicians have leveraged next generation sequencing technologies to identify neoantigens and to create personalized immunotherapies for cancer treatment. To create a personalized cancer vaccine, neoantigens must be computationally predicted from matched tumor-normal sequencing data, and then ranked according to their predicted capability in stimulating a T cell response. This candidate neoantigen prediction process involves multiple steps, including somatic mutation identification, HLA typing, peptide processing, and peptide-MHC binding prediction. The general workflow has been utilized for many preclinical and clinical trials, but there is no current consensus approach and few established best practices. In this article, we review recent discoveries, summarize the available computational tools, and provide analysis considerations for each step, including neoantigen prediction, prioritization, delivery, and validation methods. In addition to reviewing the current state of neoantigen analysis, we provide practical guidance, specific recommendations, and extensive discussion of critical concepts and points of confusion in the practice of neoantigen characterization for clinical use. Finally, we outline necessary areas of development, including the need to improve HLA class II typing accuracy, to expand software support for diverse neoantigen sources, and to incorporate clinical response data to improve neoantigen prediction algorithms. The ultimate goal of neoantigen characterization workflows is to create personalized vaccines that improve patient outcomes in diverse cancer types

Psychosocial Predictors of Non-Adherence and Treatment Failure in a Large Scale Multi-National Trial of Antiretroviral Therapy for HIV: Data from the ACTG A5175/PEARLS Trial

Background: PEARLS, a large scale trial of antiretroviral therapy (ART) for HIV (n = 1,571, 9 countries, 4 continents), found that a once-daily protease inhibitor (PI) based regimen (ATV+DDI+FTC), but not a once-daily non-nucleoside reverse transcriptase inhibitor/nucleoside reverse transcriptase inhibitor (NNRTI/NRTI) regimen (EFV+FTC/TDF), had inferior efficacy compared to a standard of care twice-daily NNRTI/NRTI regimen (EFV+3TC/ZDV). The present study examined non-adherence in PEARLS. Methods: Outcomes: non-adherence assessed by pill count and by self-report, and time to treatment failure. Longitudinal predictors: regimen, quality of life (general health perceptions = QOL-health, mental health = QOL-mental health), social support, substance use, binge drinking, and sexual behaviors. “Life-Steps” adherence counseling was provided. Results: In both pill-count and self-report multivariable models, both once-a-day regimens had lower levels of non-adherence than the twice-a-day standard of care regimen; although these associations attenuated with time in the self-report model. In both multivariable models, hard-drug use was associated with non-adherence, living in Africa and better QOL-health were associated with less non-adherence. According to pill-count, unprotected sex was associated with non-adherence. According to self-report, soft-drug use was associated with non-adherence and living in Asia was associated with less non-adherence. Both pill-count (HR = 1.55, 95% CI: 1.15, 2.09, p<.01) and self-report (HR = 1.13, 95% CI: 1.08, 1.13, p<.01) non-adherence were significant predictors of treatment failure over 72 weeks. In multivariable models (including pill-count or self-report nonadherence), worse QOL-health, age group (younger), and region were also significant predictors of treatment failure. Conclusion: In the context of a large, multi-national, multi-continent, clinical trial there were variations in adherence over time, with more simplified regimens generally being associated with better adherence. Additionally, variables such as QOL-health, regimen, drug-use, and region play a role. Self-report and pill-count adherence, as well as additional psychosocial variables, such QOL-health, age, and region, were, in turn, associated with treatment failure

Genetic variants in RBFOX3 are associated with sleep latency

Time to fall asleep (sleep latency) is a major determinant of sleep quality. Chronic, long sleep latency is a major characteristic of sleep-onset insomnia and/or delayed sleep phase syndrome. In this study we aimed to discover common polymorphisms that contribute to the genetics of sleep latency. We performed a meta-analysis of genome-wide association studies (GWAS) including 2 572 737 single nucleotide polymorphisms (SNPs) established in seven European cohorts including 4242 individuals. We found a cluster of three highly correlated variants (rs9900428, rs9907432 and rs7211029) in the RNA-binding protein fox-1 homolog 3 gene (RBFOX3) associated with sleep latency (P-values=5.77 × 10-08, 6.59 × 10- 08 and 9.17 × 10- 08). These SNPs were replicated in up to 12 independent populations including 30 377 individuals (P-values=1.5 × 10- 02, 7.0 × 10- 03 and 2.5 × 10- 03; combined meta-analysis P-values=5.5 × 10-07, 5.4 × 10-07 and 1.0 × 10-07). A functional prediction of RBFOX3 based on co-expression with other genes shows that this gene is predominantly expressed in brain (P-value=1.4 × 10-316) and the central nervous system (P-value=7.5 × 10- 321). The predicted function of RBFOX3 based on co-expression analysis with other genes shows that this gene is significantly involved in the release cycle of neurotransmitte

Transition of care for adolescents from paediatric services to adult health services

BackgroundThere is evidence that the process of transition from paediatric (child) to adult health services is often associated with deterioration inthe health of adolescents with chronic conditions.Transitional care is the term used to describe services that seek to bridge this caregap. It has been defined as ‘the purposeful, planned movement of adolescents and young adults with chronic physical and medicalconditions from child-centred to adult-oriented health care systems’. In order to develop appropriate services for adolescents, evidenceof what works and what factors act as barriers and facilitators of effective interventions is needed.ObjectivesTo evaluate the effectiveness of interventions designed to improve the transition of care for adolescents from paediatric to adult healthservices.Search methodsWe searched The Cochrane Central Register of Controlled Trials 2015, Issue 1, (including the Cochrane Effective Practice andOrganisation of Care Group Specialised Register), MEDLINE, EMBASE, PsycINFO, and Web of Knowledge to 19 June 2015. Wealso searched reference lists of included studies and relevant reviews, and contacted experts and study authors for additional studies.Selection criteriaWe considered randomised controlled trials (RCTs), controlled before- and after-studies (CBAs), and interrupted time-series studies(ITSs) that evaluated the effectiveness of any intervention (care model or clinical pathway), that aimed to improve the transitionof care for adolescents from paediatric to adult health services. We considered adolescents with any chronic condition that requiredongoing clinical care, who were leaving paediatric services and going on to receive services in adult healthcare units, and their families.Participating providers included all health professionals responsible for the care of young people