bluuebunny/crossref_metadata_2025_split huggingface dataset:
Secure Research at scale
Authors: Thompson Simon 
Published: April 2017

ABSTRACT
BackgroundAs part of an initiative funded by FARR institute, Swansea University Health Informatics Unit embarked on the creation of the UK Secure e-Research Platform (UKSeRP) to both build on the experience developed by the SAIL databank over many years and to create an infrastructure that can support, at scale, multiple national research programmes.
MethodThe system was created utilising the in-house technical staff and combines multiple vender solutions all orchestrated through bespoke developments. The same team also developed the National Research Data Appliance (NRDA) and elements of this initiate were integrated into the core of this development.
ResultsThe system went live at the end of February 2016 and is already supporting five national level research programmes. The presentation will show now the system is architected and how it evolved over time as additional opportunities arose. It is imperative to both provide common architecture and systems that can scale to meet the research programmes needs and yet still allow for additional unique aspects to be provisioned that deliver against the programmes research goals and differing governance models.
The platform has gained an ISO 27001 accreditation which provided clear control and management over information security but also allows programmes utilising the platform to inherit these key controls and if desirable to gain their own accreditation easier, as the SAIL Databank has demonstrated.
The platform has an ambitus road map and is currently adding imaging capabilities supported by an imaging processing pipeline. Genomics handling, processing and analysis capabilities are being added in the next couple of months.
ConclusionThe demand for UKSeRP has been higher than initially envisaged and the possible use cases are constantly being imagined. We are also introducing an entry level UKSeRP to support individual projects and their requirements.
Educational outcomes are predictive of mental health diagnoses in adolescence
Authors: Wong Janice , Fletcher Janet , Glauert Rebecca , O'Donnell Melissa , Bayliss Donna 
Published: April 2017

ABSTRACTObjectivesAssociations between poor reading outcomes and attention/behavioural difficulties have been documented in the literature (e.g., Spira & Fischel, 2005), however the research regarding the relationship between reading achievement and internalising mental health disorders (e.g., mood disorders, anxiety) is scarce. As children experience a large proportion of their development in the school context, it is essential to understand the nature of this relationship, as it may inform a population based approach to reducing the risk of mental health disorders.
ApproachThis study was a retrospective cohort study, and utilised population level administrative data. Participants included all children born in Western Australia between 1992 and 1996. Individuals were followed until 2011 for their mental health outcomes. Using Cox regressions, variables reflecting child, family, and community factors, as well as factors from the school context were used to predict the risk of any mental health disorder, and also more specifically, an internalising or externalising mental health disorder.
ResultsAfter controlling for a number of demographic risk factors, poor reading achievement in Year 3 and Year 7 appeared to be associated with poor mental health when all mental health diagnostic codes were considered as a single entity. However, when mental health was grouped into internalising or externalising mental health disorders, findings showed that reading achievement in the top 20% of the cohort was associated with an increased risk of an internalising disorder, whilst reading achievement in the bottom 20% of the cohort was associated with an increased risk of an externalising disorder.
ConclusionThis study found that reading achievement is associated with mental health, but the nature of this relationship appears to be dependent on the type of mental health disorders that are considered. A more complex relationship between reading achievement and poor mental health was revealed when the mental health diagnoses were grouped into internalising and externalising disorders. Whilst further research is required to understand the factors that may mediate these relationships (e.g., perfectionism for high achieving students), the provision of support to both ends of the achievement spectrum may play a role in reducing the risk of adolescent mental health disorders.
The impact of the Population Health Research Network on linked data research capacity in Australia
Authors: Flack Felicity , Wray Natalie , Smith Merran 
Published: April 2017

ABSTRACTObjectivesIn 2009 Australian governments and academic institutions made a substantial investment to establish the Population Health Research Network (PHRN), a distributed research infrastructure network which provides Australian researchers with state-of-the-art data linkage facilities and services. The infrastructure operates on a collaborative, national, non-exclusive basis and enables Australian researchers to address key national and global challenges.
We have conducted a review of the PHRN’s progress over the last 6 years in achieving its objectives of:1. increasing the data linkage research capacity in Australia2. enabling research in national priority areas.
ApproachProgress with achieving the first objective was measured by comparing the data linkage facilities and services available in Australia in 2008-09 with those available in 2014-15. The following categories of services and facilities were used in the analysis:

Linkage facilities
Application, access and storage facilities
Information, training and education

Changes in usage of the data linkage infrastructure over the period 2008-09 to 2014-15 were measured.
The second objective was achieved by using bibliometrics to assess academic impact, in the form of citations, of peer-reviewed publications which arose from use of the PHRN infrastructure. The topics of all of the publications were compared to health priority areas to determine the extent to which the infrastructure has been used to inform national priorities.
ResultsThere has been a significant expansion of the data linkage facilities from a small number of jurisdictional data linkage units to a distributed network of data linkage units servicing researchers in every state and territory. A cross-jurisdictional data linkage capability has also been established as well as a national online data application system, a secure remote access laboratory and a secure file transfer system. A variety of information, training and education has been provided to stakeholders. The expansion of the facilities and services has seen usage of data linkage units triple since 2011-12.
The number of peer-reviewed publications resulting from the use of the PHRN infrastructure has increased every year since 2011-12. There were 111 publications in 2014-15. Areas of high burden of disease in Australia, cancer, cardiovascular and endocrine diseases are highly represented in the publications.
ConclusionThere has been a significant increase in data linkage research infrastructure in Australia from 2008-09 to 2014-15. This has resulted in an increase in both the number of research projects conducted using linked data and the number of related peer-reviewed publications.
Describing the Linkages of the Citizenship and Immigration Canada Permanent Resident Data and Vital Statistics—Death Registry to Ontario’s Administrative Health Database
Authors: Guttmann Astrid , Chiu Maria , Lebenbaum Michael , Lam Kelvin , Chong Nelson , Azimaee Mahmoud , Iron Karey , Manuel Doug 
Published: April 2017

ABSTRACTObjectives Ontario, the most populous province in Canada, has a universal healthcare system that routinely collects health administrative data on its 13 million legal residents that is used for health research. Record linkage has become a vital tool for this research by enriching this data with the Immigration, Refugees and Citizenship Canada (IRCC) Permanent Resident database and the Office of the Registrar General’s Vital Statistics-Death (VSD) registry. Our objectives were to estimate linkage rates and compare characteristics of individuals in the linked versus unlinked files.
Approach We used both deterministic and probabilistic linkage methods to link the IRCC database (1985-2012) and VSD registry (1990-2012) to the Ontario’s Registered Persons Database. Linkage rates were estimated and standardized differences were used to assess differences in socio-demographic and other characteristics between the linked and unlinked records.
Results The overall linkage rates for the IRCC database and VSD registry were 86.4% and 96.2%, respectively. The majority (68.2%) of the record linkages in IRCC were achieved after the three deterministic passes with the remaining 18.2% being linked probabilistically. Similarly the majority (79.8%) of the record linkages in the ORGD were linked using deterministic record linkage and the remaining 16.3% were linked after probabilistic and manual review. Unlinked and linked files were similar for most characteristics, such as age and marital status for IRCC and sex and most causes of death for VSD. However, lower linkage rates were observed among people born in East Asia (78%) in the IRCC database and certain causes of death in the VSD registry, namely perinatal conditions (61.3%) and congenital anomalies (81.3%).
Conclusion The linkages of immigration and vital statistics data to existing population-based healthcare data in Ontario, Canada will enable many novel cross-sectional and longitudinal studies to be conducted. Analytic techniques to account for sub-optimal linkage rates may be required in studies of certain ethnic groups or certain causes of death among children and infants.
Treatment choices for managing glucose control in impaired renal function: Interim Results
Authors: Davies Gareth , Stephens Jeff , Rice Sam , Chess James 
Published: April 2017

ABSTRACT
ObjectivesPatients with chronic kidney disease (CKD ≥3) and diabetes mellitus comprise approximately 25% patients with diabetes. These patients are at a higher risk of cardiovascular morbidity and mortality and furthermore therapies targeting glucose control are limited. The management of glycaemic control in type 2 diabetes and chronic renal disease is difficult with limited therapeutic choices. This issue has been a matter of longstanding debate. Following a number of joint Diabetes-Renal meetings between the Diabetes and Renal teams based in Hywel Dda and ABM University Health Boards, a proposal was put forward to the SAIL team to examine the relationship between diabetes therapies in relation to eGFR, as this may influence further practice and guidance for patients with type 2 diabetes and renal impairment.
ApproachLinkage and re-use of routinely collected anonymised clinical data held in the SAIL databank was employed, to identify a cohort of adult patients in Abertawe Bro Morgannwg Health Board (ABMU) having type 2 diabetes (excluding type 1 diabetes). Diagnosis of diabetes was achieved by use of National Health Service ‘Read’ codes. Creatinine, eGFR, age, gender, weight, height, cholesterol, LDL, HDL, TG, systolic blood pressure, diastolic blood pressure, diabetes medication prescriptions, the use of statins, ACEis, aspirin, CHD status, CVD status, duration of diabetes were identified in primary care GP and pathology datasets.
Results42170 (6.0%) of adults in ABMU were identified as having type 2 (excluding type 1) diabetes , 13369 of which had good GP registration coverage. The gender split was male 56%, female 44%. Duration of diabetes (years) was (mean/median/SD/IQR) 9.96/8.97/6.78/8.10; weight (Kg) was 86.94/85.00/21.23/28.19; age (years) 65.49/66.74/13.75/19.03; BMI 31.57/30.70/6.62/7.99. Incidence of CKD as defined by GP coded data was 24%, renal replacement therapy 0.4%, Ischaemic Heart Disease 22%. Prevalence of prescriptions during 2014 was: Anti-diabetic medication 72%, statins 75%, aspirin 34%, ACEi/ARB 61%. The import of pathology laboratory data into SAIL is currently pending, and is anticipated before April 2016. This will allow the accurate stratification of CKD status and detailed description of use of anti-diabetic agents.
ConclusionThe project methods and coding structure are well place to provide anticipated results as soon as pathology data arrives. The percentage of ABMU patients having type 2 diabetes is in line with other literature for adults in the UK.
A Systems Dynamic Approach to Alzheimer’s Disease Prevention
Authors: Sabounchi Nasim S. 
Published: April 2017

ABSTRACT
ObjectivesAs estimated there are about 5.3 million who suffer from Alzheimer’s disease in United States. The incidence is increasing as the population is aging. Due to the increasing trend of Alzheimer’s disease, there is a lot of discussion on prevention efforts or slowing the incidence. Also, models that could predict individual risk of cognitive impairment are needed to assist in prevention efforts.
In general dementia development has been associated with growth in various vascular, lifestyle and other risk factors. Epidemiological research provides evidence of some vascular, lifestyle and psychological risk factors that are modifiable and protective of disease incidence either independently or while interacting with other factors. However, as reported by National Institute of Aging, it is not yet clear whether health or lifestyle factors can prevent Alzheimer’s disease.
The objective of this research project is to adopt a system dynamics modeling approach to study the interaction of several key factors including vascular, lifestyle and psychological aspects over the life course of individuals, to gain further understanding of Alzheimer’s disease incidence and evaluate prevention strategies. Both datasets of ‘Alzheimer's Disease Neuroimaging Initiative (ADNI)’ and ‘Health and Retirement Study (HRS)’ will be used for model development and validation.
ApproachA system dynamics approach is an optimal choice for addressing the goal of this proposal because different key factors interact over time and make Alzheimer’s disease incidence a complex problem. Furthermore, system dynamics approaches focus on understanding the relationship between the structure of a system and the resulting dynamic behaviors generated through multiple interacting feedback loops. Such an approach could be invaluable in studying dynamic problems arising in complex health, social, economic, or ecological systems.
ResultsFor the purpose of the proposal, the following stages are planned:1. Develop a system dynamics simulation model at individual level that predicts the Alzheimer’s disease incidence over the life course, and aggregates individual level models to predict population level trends
2. Calibrate the resulting simulation model based upon longitudinal data trends employed from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Both cohorts with Alzheimer’s disease and control subjects from this database will be used to fine-tune the simulation model.
ConclusionThe final validated model would be used to test different hypotheses and evaluate various strategies and/or their combinations to help evaluate the efficacy of prevention strategies on Alzheimer’s disease incidence and its growth.
Weighted multiple imputation of ethnicity data that are missing not at random in primary care databases
Authors: Pham Tra My , Petersen Irene , Carpenter James , Morris Tim 
Published: April 2017

ABSTRACT
BackgroundEthnicity is an important factor to be considered in health research because of its association with inequality in disease prevalence and the utilisation of healthcare. Ethnicity recording has been incorporated in primary care electronic health records, and hence is available in large UK primary care databases such as The Health Improvement Network (THIN). However, since primary care data are routinely collected for clinical purposes, a large amount of data that are relevant for research including ethnicity is often missing. A popular approach for missing data is multiple imputation (MI). However, the conventional MI method assuming data are missing at random does not give plausible estimates of the ethnicity distribution in THIN compared to the general UK population. This might be due to the fact that ethnicity data in primary care are likely to be missing not at random. ObjectivesI propose a new MI method, termed ‘weighted multiple imputation’, to deal with data that are missing not at random in categorical variables.MethodsWeighted MI combines MI and probability weights which are calculated using external data sources. Census summary statistics for ethnicity can be used to form weights in weighted MI such that the correct marginal ethnic breakdown is recovered in THIN. I conducted a simulation study to examine weighted MI when ethnicity data are missing not at random. In this simulation study which resembled a THIN dataset, ethnicity was an independent variable in a survival model alongside other covariates. Weighted MI was compared to the conventional MI and other traditional missing data methods including complete case analysis and single imputation.ResultsWhile a small bias was still present in ethnicity coefficient estimates under weighted MI, it was less severe compared to MI assuming missing at random. Complete case analysis and single imputation were inadequate to handle data that are missing not at random in ethnicity.ConclusionsAlthough not a total cure, weighted MI represents a pragmatic approach that has potential applications not only in ethnicity but also in other incomplete categorical health indicators in electronic health records.
Generation Scotland: using data linkage for longitudinal studies
Authors: Campbell Archie 
Published: April 2017

ABSTRACTObjectivesGeneration Scotland: Scottish Family Health Study (GS:SFHS) is a family-based genetic epidemiology study of ~24,000 volunteers from ~7000 families recruited across Scotland between 2006 and 2011 with the capacity for follow-up through record linkage and re-contact.
ApproachParticipants completed a demographic, health and lifestyle questionnaire and provided biological samples including DNA, and 90% underwent detailed clinical assessment, including anthropometric, cardiovascular, respiratory, cognition and mental health. The biological samples, phenotype and genotype data collected form a resource with broad consent for academic and commercial research on the genetics of health, disease and quantitative traits of current and projected public health importance. Features include the family-based recruitment; breadth and depth of phenotype information, with detailed data on cognition, personality and mental health. GWAS and exome genotype data is available on most of the cohort. These features maximise the power of the resource to identify, replicate or control for genetic factors associated with a wide spectrum of illnesses and risk factors. By linkage to routine NHS hospital, lab tests, prescribing and dental records this has become a longitudinal dataset, using the Scottish Community Health Index (CHI).
Results Researchers are now able to use the dataset to find prevalent and incidental disease cases, and healthy controls, to test research hypotheses on a stratified population. They can also do targeted recruitment of participants to new studies, utilising the NHS CHI register for up to date contact details. There are 6 published papers on a variety of conditions and currently around 10 ongoing studies based on our record linkage capabilities.
ConclusionWe have thoroughly tested the linkage process and plan to extend it to include primary care data (GP records) in the next year. There are current or planned collaborations looking into heart disease, diabetes, breast and colon cancers, depression, neuropathic pain, Alzheimer’s disease and dementia. Generation Scotland is also a contributor to major international consortia. The resources are available to academic and commercial researchers through a managed access process.
El premio nobel alrededor del ADN
Authors: Delgadillo-Álvarez Dulce María 
Published: April 2017

El Premio Nobel es un galardón internacional otorgado cada año a personas o instituciones que hayan realizado investigaciones, descubrimientos o contribuciones a la humanidad en el año inmediato anterior o en el transcurso de su vida. Los premios se instituyeron en 1895 como última voluntad del químico sueco Alfred Nobel y comenzaron a entregarse en 1901. Dos de las especialidades en las que el Premio es otorgado son en Química y en Fisiología o Medicina. El objetivo de esta breve revisión es hacer un recuento de aquellos investigadores que han sido merecedores de este galardón en las disciplinas citadas desde hace 114 años y cuyos trabajos han orbitado alrededor del ácido desoxirribonucleico o ADN. Se mencionan estudios sobre su descubrimiento, estructura y caracterización molecular tanto de esta como de las moléculas que, en coordinación con él lo hacen ser la molécula encargada de almacenar y transmitir la información genética de todos los organismos que habitan nuestro planeta.Palabras clave: Premio Nobel, ácido desoxirribonucleico, descubrimiento, estructura, biología molecular
Clasificación de dos tareas mentales haciendo uso mapas autoorganizativos de kohonen (SOM)
Authors: Diaz Sotelo Wilber , Joya Gonzalo , García-Lagos Francisco 
Published: April 2017

En este trabajo se llevó a cabo la clasificación de patrones correspondientes a dos tareas mentales, obtenidos mediante un sistema BCI (Brain Computer Interface). Para ello se utilizó el paradigma neuronal de los Mapas Autorganizativos de Kohonen (SOM, por Self-Organizing Maps). Los patrones utilizados en cada clasificador se obtuvieron mediante la aplicación de la Transformada Rápida de Fourier a las señales EEG directamente proporcionadas por el sistema BCI. En una primera fase, las capturas de los patrones se realizaron a lo largo de ocho segundos, pero una red SOM es implementada y entrenada de manera independiente para cada segundo. La SOM con el mejor rendimiento se usó en la segunda fase (fase de trabajo), para clasificar todos los segundos. Los resultados obtenidos en las pruebas de validación proporcionan un porcentaje de error entre 3.75%, (para los segundos 5° y 6°), y 11.25% para el 8°. Estos errores son menores o similares a los resultados obtenidos en otros trabajos de referencia.Palabras claves: Interfaz Cerebro Computadora BCI, Mapas Autorganizativos de Kohonen, Fast Fourier Transform FFT, electroencefalograma EEG, Clasificación de tareas mentales.