Moving Beyond the Stigma: Systematic Review of Video Games and Their Potential to Combat Obesity

Increasing epidemic proportions of overweight children in the United States presents formidable challenges for education and healthcare. Given the popularity and pervasiveness of video gaming culture in North American children, the perfect opportunity arises to investigate the potential of video games to promote healthful behaviour. Our objective was to systematically review the literature for possible benefits of active and educational video games targeting diet and physical activity in children. A review of English-language journal articles from 1998 to 2011 using EMBASE and PubMed was conducted. Thirty-four studies concerned with children, video games, physical, and/or nutritional outcomes were included. Results of these studies that showed some benefit (increased physical activity and nutritional knowledge as a result of gaming) demonstrate the possibility of video games to combat childhood obesity—looking beyond the stigma attached to gaming

A Checklist for Medication Compliance and Persistence Studies Using Retrospective Databases

The increasing number of retrospective database studies related to medication compliance and persistence (C&P), and the inherent variability within each, has created a need for improvement in the quality and consistency of medication C&P research. This article stems from the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) efforts to develop a checklist of items that should be either included, or at least considered, when a retrospective database analysis of medication compliance or persistence is undertaken. This consensus document outlines a systematic approach to designing or reviewing retrospective database studies of medication C&P. Included in this article are discussions on data sources, measures of C&P, results reporting, and even conflict of interests. If followed, this checklist should improve the consistency and quality of C&P analyses, which in turn will help providers and payers understand the impact of C&P on health outcomes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75562/1/j.1524-4733.2006.00139.x.pd

Bagging Ensembles for the Diagnosis and Prognostication of Alzheimer's Disease

Alzheimer's disease (AD) is a chronic neurodegenerative disease, which involves the degeneration of various brain functions, resulting in memory loss, cognitive disorder and death. Large amounts of multivariate heterogeneous medical test data are available for the analysis of brain deterioration. How to measure the deterioration remains a challenging problem. In this study, we first investigate how different regions of the human brain change as the patient develops AD. Correlation analysis and feature ranking are performed based on the feature vectors from different stages of the pathologic process in Alzheimer disease. Then, an automatic diagnosis system is presented, which is based on a hybrid manifold learning for feature embedding and the bootstrap aggregating (Bagging) algorithm for classification.We investigate two different tasks, i.e. diagnosis and progression prediction. Extensive comparison is made against Support Vector Machines (SVM), Random Forest (RF), Decision Tree (DT) and Random Subspace (RS) methods. Experimental results show that our proposed algorithm yields superior results when compared to the other methods, suggesting promising robustness for possible clinical applications

Healthy Cognitive Aging: A Hybrid Random Vector Functional-Link Model for the Analysis of Alzheimer’s Disease

Alzheimer's disease (AD) is a genetically complex neurodegenerative disease, which leads to irreversible brain damage, severe cognitive problems and ultimately death. A number of clinical trials and study initiatives have been set up to investigate AD pathology, leading to large amounts of high dimensional heterogeneous data (biomarkers) for analysis. This paper focuses on combining clinical features from different modalities, including medical imaging, cerebrospinal fluid (CSF), etc., to diagnose AD and predict potential progression. Due to privacy and legal issues involved with clinical research, the study cohort (number of patients) is relatively small, compared to thousands of available biomarkers (predictors). We propose a hybrid pathological analysis model, which integrates manifold learning and Random Vector functional-link network (RVFL) so as to achieve better ability to extract discriminant information with limited training materials. Furthermore, we model (current and future) cognitive healthiness as a regression problem about age. By comparing the difference between predicted age and actual age, we manage to show statistical differences between different pathological stages. Verification tests are conducted based on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Extensive comparison is made against different machine learning algorithms, i.e. Support Vector Machine (SVM), Random Forest (RF), Decision Tree and Multilayer Perceptron (MLP). Experimental results show that our proposed algorithm achieves better results than the comparison targets, which indicates promising robustness for practical clinical implementation

Hitting the ground running: Healthgrid deployment and adoption

We consider the issues of healthgrid development, deployment and adoption in health care and research environments. While healthgrid technology could be deployed to support advanced medical research, we are not seeing its wide adoption. Understanding why this technology is not being exploited is one purpose of this paper. We do so in light of the seminal Healthgrid White Paper and the SHARE roadmap. We also address barriers to adoption and successes by presenting experiences in North America and Europe. By critically appraising where we are, we hope that we can hit the ground running in the near futur

Effect of indomethacin plus ranitidine in advanced melanoma patients on high-dose interleukin-2

Preclinical models of advanced melanoma have shown that chronic indomethacin therapy combined with interleukin 2 (IL-2) can eradicate experimental metastases. A phase II trial was done in patients with advanced melanoma. Indomethacin and ranitidine were begun at least one week before IL-2. Of the objective responses in 3 patients, 2 were achieved on ranitidine and indomethacin alone, before start of IL-2. Indomethacin and ranitidine may be responsible for some responses in melanoma patients previously attributed to IL-2.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29902/1/0000259.pd

Impact of interventions on medication adherence and blood pressure control in patients with essential hypertension: a systematic review by the ISPOR medication adherence and persistence special interest group

AbstractObjectivesTo systematically review the evidence on the impact of interventions to improve medication adherence in adults prescribed antihypertensive medications.MethodsAn electronic search was undertaken of articles published between 1979 and 2009, without language restriction, that focused on interventions to improve antihypertensive medication adherence among patients (≥18 years) with essential hypertension. Studies must have measured adherence as an outcome of the intervention. We followed standard guidelines for the conduct and reporting of the review and conducted a narrative synthesis of reported data.ResultsNinety-seven articles were identified for inclusion; 35 (35 of 97, 36.1%) examined interventions to directly improve medication adherence, and the majority (58 of 97, 59.8%) were randomized controlled trials. Thirty-four (34 of 97, 35.1%) studies reported a statistically significant improvement in medication adherence.Discussion/ConclusionsInterventions aimed at improving patients’ knowledge of medications possess the greatest potential clinical value in improving adherence with antihypertensive therapy. However, we identified several limitations of these studies, and advise future researchers to focus on using validated adherence measures, well-designed randomized controlled trials with relevant adherence and clinical outcomes, and guidelines on the appropriate design and analysis of adherence research