Body Composition Measurement in Children with Cerebral Palsy, Spina Bifida and Spinal Cord Injury: A Systematic Review of the Literature

Pediatric obesity is a major health concern that has an increased prevalence in children with special needs. In order to categorize a child’s weight, an assessment of body composition is needed. Obtaining an accurate body composition measurement in children with special needs has many challenges associated with it. This perplexing scenario limits the provider’s ability to screen, prevent and treat an abnormal weight status in this vulnerable population. This systematic review summarizes common methods of body composition measurements, their strengths and limitations and reviews the literature when measurements were used in children with cerebral palsy, spina bifida and spinal cord injury. Following PRISMA guidelines, 222 studies were identified. The application of the inclusion and exclusion criteria yielded a final sample of nine studies included in this review. Overall, articles reinforced the inconsistencies of body composition measurement and methodology when used with children with special needs. Concerns include small sample sizes, the need to validate prediction equations for this population, and the lack of controlled trials and reporting of measurement methodology. Healthcare providers need to be aware of the complexities associated with measuring body composition in children with special needs and advocate for further testing of these measurements. Additional studies addressing the reliability and validity of these measures are needed to facilitate appropriate health promotion in children

Advancing the Empirical Research on Lobbying

This essay identifies the empirical facts about lobbying which are generally agreed upon in the literature. It then discusses challenges to empirical research in lobbying and provides examples of empirical methods that can be employed to overcome these challenges—with an emphasis on statistical measurement, identification, and casual inference. The essay then discusses the advantages, disadvantages, and effective use of the main types of data available for research in lobbying. It closes by discussing a number of open questions for researchers in the field and avenues for future work to advance the empirical research in lobbying

A Methodology for Information Flow Experiments

Information flow analysis has largely ignored the setting where the analyst has neither control over nor a complete model of the analyzed system. We formalize such limited information flow analyses and study an instance of it: detecting the usage of data by websites. We prove that these problems are ones of causal inference. Leveraging this connection, we push beyond traditional information flow analysis to provide a systematic methodology based on experimental science and statistical analysis. Our methodology allows us to systematize prior works in the area viewing them as instances of a general approach. Our systematic study leads to practical advice for improving work on detecting data usage, a previously unformalized area. We illustrate these concepts with a series of experiments collecting data on the use of information by websites, which we statistically analyze

Cognitive impairment and decline in cognitively normal older adults with high amyloid-β: A meta-analysis

AbstractIntroductionThis meta-analysis aimed to characterize the nature and magnitude of amyloid (Aβ)-related cognitive impairment and decline in cognitively normal (CN) older individuals.MethodMEDLINE Ovid was searched from 2012 to June 2016 for studies reporting relationships between cerebrospinal fluid or positron emission tomography (PET) Aβ levels and cognitive impairment (cross-sectional) and decline (longitudinal) in CN older adults. Neuropsychological data were classified into domains of episodic memory, executive function, working memory, processing speed, visuospatial function, semantic memory, and global cognition. Type of Aβ measure, how Aβ burden was analyzed, inclusion of control variables, and clinical criteria used to exclude participants, were considered as moderators. Random-effects models were used for analyses with effect sizes expressed as Cohen's d.ResultsA total of 38 studies met inclusion criteria contributing 30 cross-sectional (N = 5005) and 14 longitudinal (N = 2584) samples. Aβ-related cognitive impairment was observed for global cognition (d = 0.32), visuospatial function (d = 0.25), processing speed (d = 0.18), episodic memory, and executive function (both d's = 0.15), with decline observed for global cognition (d = 0.30), semantic memory (d = 0.28), visuospatial function (d = 0.25), and episodic memory (d = 0.24). Aβ-related impairment was moderated by age, amyloid measure, type of analysis, and inclusion of control variables and decline moderated by amyloid measure, type of analysis, inclusion of control variables, and exclusion criteria used.DiscussionCN older adults with high Aβ show a small general cognitive impairment and small to moderate decline in episodic memory, visuospatial function, semantic memory, and global cognition

Towards large-cohort comparative studies to define the factors influencing the gut microbial community structure of ASD patients.

Differences in the gut microbiota have been reported between individuals with autism spectrum disorders (ASD) and neurotypical controls, although direct evidence that changes in the microbiome contribute to causing ASD has been scarce to date. Here we summarize some considerations of experimental design that can help untangle causality in this complex system. In particular, large cross-sectional studies that can factor out important variables such as diet, prospective longitudinal studies that remove some of the influence of interpersonal variation in the microbiome (which is generally high, especially in children), and studies transferring microbial communities into germ-free mice may be especially useful. Controlling for the effects of technical variables, which have complicated efforts to combine existing studies, is critical when biological effect sizes are small. Large citizen-science studies with thousands of participants such as the American Gut Project have been effective at uncovering subtle microbiome effects in self-collected samples and with self-reported diet and behavior data, and may provide a useful complement to other types of traditionally funded and conducted studies in the case of ASD, especially in the hypothesis generation phase

Adaptive methods for Bayesian time-to-event point-of-care clinical trials

Point-of-care clinical trials are randomized clinical trials designed to maximize pragmatic design features. The goal is to integrate research into standard care such that the burden of research is minimized for patient and physician, including recruitment, randomization and study visits. When possible, these studies employ Bayesian adaptive methods and data collection through the medical record. Due to the passive and adaptive nature of these trials, a number of unique challenges may arise over the course of a study. In this dissertation, adaptive methodology for Bayesian time-to-event clinical trials is developed and evaluated for studies with limited censoring. Use of a normal approximation to the study parameter likelihood is proposed for trials in which the likelihood is not normally distributed and assessed with respect to frequentist type I and II errors. A previously developed method for choosing a normal prior distribution for analysis is applied with modifications to allow for adaptive randomization. This method of prior selection in conjunction with the normal parameter likelihood is used to estimate future data for the purpose of prediction of study success. A previously published method for future event estimation is modified to allow for adaptive randomization and inclusion of prior information. Accuracy of this method is evaluated against final study numbers under a range of study designs and parameter likelihood assumptions. With these future estimates, we predict study conclusions by calculating predicted probabilities of study outcome and compare them to actual study conclusions. Reliability of this method is evaluated considering prior distribution choice, study design, and use of an incorrect likelihood for analysis. The normal approximation to non-normally distributed data performs well here and is reliable when the underlying likelihood is known. The choice of analytic prior distribution agrees with previously published results when equal allocation is forced, but changes depending on the severity of adaptive allocation. Performance of event estimation and prediction vary, but can provide reliable estimates after only 25 subjects have been observed. Analysis and prediction can reliably be carried out in point-of-care studies when care is taken to ensure assumptions are reasonable