857 resultados para High Risk


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Background: Patients with Crohn’s disease (CD) often require surgery at some stage of disease course. Prediction of CD outcome is influenced by clinical, environmental, serological, and genetic factors (eg, NOD2). Being able to identify CD patients at high risk of surgical intervention should assist clinicians to decide whether or not to prescribe early aggressive treatment with immunomodulators. Methods: We performed a retrospective analysis of selected clinical (age at diagnosis, perianal disease, active smoking) and genetic (NOD2 genotype) data obtained for a population-based CD cohort from the Canterbury Inflammatory Bowel Disease study. Logistic regression was used to identify predictors of complicated outcome in these CD patients (ie, need for inflammatory bowel disease-related surgery). Results: Perianal disease and the NOD2 genotype were the only independent factors associated with the need for surgery in this patient group (odds ratio=2.84 and 1.60, respectively). By combining the associated NOD2 genotype with perianal disease we generated a single “clinicogenetic” variable. This was strongly associated with increased risk of surgery (odds ratio=3.84, P=0.00, confidence interval, 2.28-6.46) and offered moderate predictive accuracy (positive predictive value=0.62). Approximately 1/3 of surgical outcomes in this population are attributable to the NOD2+PA variable (attributable risk=0.32). Conclusions: Knowledge of perianal disease and NOD2 genotype in patients presenting with CD may offer clinicians some decision-making utility for early diagnosis of complicated CD progression and initiating intensive treatment to avoid surgical intervention. Future studies should investigate combination effects of other genetic, clinical, and environmental factors when attempting to identify predictors of complicated CD outcomes.

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The high risk of metabolic disease traits in Polynesians may be partly explained by elevated prevalence of genetic variants involved in energy metabolism. The genetics of Polynesian populations has been shaped by island hoping migration events which have possibly favoured thrifty genes. The aim of this study was to sequence the mitochondrial genome in a group of Maoris in an effort to characterise genome variation in this Polynesian population for use in future disease association studies. We sequenced the complete mitochondrial genomes of 20 non-admixed Maori subjects using Affymetrix technology. DNA diversity analyses showed the Maori group exhibited reduced mitochondrial genome diversity compared to other worldwide populations, which is consistent with historical bottleneck and founder effects. Global phylogenetic analysis positioned these Maori subjects specifically within mitochondrial haplogroup - B4a1a1. Interestingly, we identified several novel variants that collectively form new and unique Maori motifs – B4a1a1c, B4a1a1a3 and B4a1a1a5. Compared to ancestral populations we observed an increased frequency of non-synonymous coding variants of several mitochondrial genes in the Maori group, which may be a result of positive selection and/or genetic drift effects. In conclusion, this study reports the first complete mitochondrial genome sequence data for a Maori population. Overall, these new data reveal novel mitochondrial genome signatures in this Polynesian population and enhance the phylogenetic picture of maternal ancestry in Oceania. The increased frequency of several mitochondrial coding variants makes them good candidates for future studies aimed at assessment of metabolic disease risk in Polynesian populations.

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Migraine is a common neurovascular disorder with a complex envirogenomic aetiology. In an effort to identify migraine susceptibility genes, we conducted a study of the isolated population of Norfolk Island, Australia. A large portion of the permanent inhabitants of Norfolk Island are descended from 18th Century English sailors involved in the infamous mutiny on the Bounty and their Polynesian consorts. In total, 600 subjects were recruited including a large pedigree of 377 individuals with lineage to the founders. All individuals were phenotyped for migraine using International Classification of Headache Disorders-II criterion. All subjects were genotyped for a genome-wide panel of microsatellite markers. Genotype and phenotype data for the pedigree were analysed using heritability and linkage methods implemented in the programme SOLAR. Follow-up association analysis was performed using the CLUMP programme. A total of 154 migraine cases (25%) were identified indicating the Norfolk Island population is high-risk for migraine. Heritability estimation of the 377-member pedigree indicated a significant genetic component for migraine (h2 = 0.53, P = 0.016). Linkage analysis showed peaks on chromosome 13q33.1 (P = 0.003) and chromosome 9q22.32 (P = 0.008). Association analysis of the key microsatellites in the remaining 223 unrelated Norfolk Island individuals showed evidence of association, which strengthen support for the linkage findings (P ≤ 0.05). In conclusion, a genome-wide linkage analysis and follow-up association analysis of migraine in the genetic isolate of Norfolk Island provided evidence for migraine susceptibility loci on chromosomes 9q22.22 and 13q33.1.

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Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

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Chronic kidney disease (CKD) is a major health problem in Saudi Arabia. The number of people requiring kidney replacement therapy in Saudi Arabia is growing, which poses challenges for health professionals and increases the burden on the health care system. However, there is a paucity of nursing literature about CKD in the Middle Eastern region, including Saudi Arabia. The purpose of this review is to describe the epidemiology, risk factors, treatment modalities and the implications for nursing practice of CKD in Saudi Arabia. Improving nurses’ knowledge and awareness about CKD and the risk factors in Saudi Arabia will help them to determine high risk groups and provide early management to delay progression of the disease.

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Aim Collisions between trains and pedestrians are the most likely to result in severe injuries and fatalities when compared to other types of rail crossing accidents. Currently, there is a growing emphasis towards developing effective interventions designed to reduce the prevalence of train–pedestrian collisions. This paper reviews what is currently known regarding the personal and environmental factors that contribute to train–pedestrian collisions, particularly among high-risk groups. Method Studies that reported on the prevalence and characteristics of pedestrian accidents at railway crossings up until June 2012 were searched in electronic databases. Results Males, school children and older pedestrians (and those with disabilities) are disproportionately represented in fatality databases. However, a main theme to emerge is that little is known about the origins of train–pedestrian collisions (especially compared to train–vehicle collisions). In particular, whether collisions result from engaging in deliberate violations versus making decisional errors. This subsequently limits the corresponding development of effective and targeted interventions for high-risk groups as well as crossing locations. Finally, it remains unclear what combination of surveillance and deterrence-based and education-focused campaigns are required to produce lasting reductions in train–pedestrian fatality rates. This paper provides direction for future research into the personal and environmental origins of collisions as well as the development of interventions that aim to attract pedestrians’ attention and ensure crossing rules are respected.

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This study examined the association between socio-environmental factors and suicide in Australia. The high risk areas were identified using advanced spatial analysis methods. Higher proportion of Indigenous population, unemployment rate and bigger temperature difference appeared to be among the main socio-environmental drivers of suicide across different places. Both temperature difference and unemployment were positively associated with suicide over time in general. Temperature difference seemed to affect suicide more in months when unemployment rates were high compared with the periods when unemployment rates were low. The findings may provide useful information for determining the socio-environmental impact on suicide and designing effective suicide control and prevention programs.

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This thesis is a population-based epidemiological study to explore the spatial and temporal pattern of malaria, and to assess the relationship between socio-ecological factors and malaria in Yunnan, China. Geospatial and temporal approaches were applied; the high risk areas of the disease were identified; and socio-ecological drivers of malaria were assessed. These findings will provide important evidence for the control and prevention of malaria in China and other countries with a similar situation of endemic malaria.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

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Objective To analyze the epidemiological trend of hepatitis B from 1990 to 2007 in Shandong province, and to find the high risk population so as to explore the further control strategy. Methods Based on the routine reporting incidence data of hepatitis B and demographic data of Shandong province, the incidence rates and sex - specific, age - specific incidence rates of hepatitis B were calculated and statistically analyzed in the simple linear regression model. Results The total number of hepatitis B was 437 094, the annual average morbidity was 27132 per 100 000 population during 1990 to 2007. The incidence of men (38142 per 100 000) was higher than that for women (15183 per 100 000) 1The annual incidence rate of hepatitis B indicated an increasing trend for the whole population, while a decreased trend for the 0~9 year - old children p resented in the past 18 years. It showed that the average age of onset moved to the older. Conclusion Young adult men are the high-risk groups for the onset of hepatitis B. For the prevention of hepatitis B, the immunization of hepatitis B vaccine should be enhanced for other groups, especially for the high - risk population on the basis of imp roving the immunization coverage rate for newborns.

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Whilst there is an excellent and growing body of literature around female criminality underpinned by feminist methodologies, the nitty gritty of the methodological journey is nowhere as well detailed as it is in the context of the Higher Degree Research (HDR) thesis. Thus the purpose of this paper is threefold: i) to explore a range of feminist methodologies underpinning 20 Australian HDR theses focussing on female criminality; ii) to identify and map the governance/ethics tensions experienced by these researchers whilst undertaking high risk research in the area of female offending; and iii) to document strategies drawn from negotiations, resolutions and outcomes to a range of gate-keeping issues. By exploring the strategies used by these researchers, this paper aims to: promote discussion on feminist methodologies; highlight pathways that may be created when negotiating the challenging process of accessing data pertinent to this relatively understudied area; contribute to a community of practice; and provide useful insights into what Mason & Stubbs (2010:16) refer to as “the open and honest reflexivity through the research process by describing the assumptions, and hiccups” for future researchers navigating governance landscapes.

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Background Substantial changing trends in women’s alcohol consumption show increased proportions women drinking at risky/ high risk levels. Not confined to the younger female population, these increases are also occurring in older female age groups (aged 35 and over), posing a set of risks differing to those of their male counterparts. However, little research investigates the influences behind these changing trends. The current research examined multiple level influences (i.e. cultural, social and psychosocial on women’s drinking across a range of age groups. Methods Semi-structured telephone interviews were conducted with thirty-five women (aged 18-55) residing in Australia. Interview development was guided by an adaptation of Bronfenbrenner’s Bioecological Model of Development to assess multiple areas of influences from cultural through to psychosocial (i.e. intra-individual). Each interview took approximately 1 hour to complete. Findings Bronfenbrenner’s Bioecological Model could account for multiple-level factors impacting women’s drinking with multidirectional influences interacting across each level. Cultural influences included gender roles and national identity. Exosystem influences (e.g. infrastructure, legislation, and media) and microsystem influences (e.g. drinking context, family, partner and peer influence) were clearly identified as impacting drinking behaviours. Finally, at the psychosocial level, attitudes and expectations around the disinhibiting effects of alcohol and social facilitation emerged as key influences. Discussion The outcomes indicated the importance of these influences as women’s alcohol-related attitudes and behaviours changed across a woman’s life span and across age cohorts. Future research will build on these initial findings in order to underpin targeted interventions of the key factors influencing women’s drinking.

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The European Early Lung Cancer (EUELC) project aims to determine if specific genetic alterations occurring in lung carcinogenesis are detectable in the respiratory epithelium. In order to pursue this objective, nonsmall cell lung cancer (NSCLC) patients with a very high risk of developing progressive lung cancer were recruited from 12 centres in eight European countries: France, Germany, southern Ireland, Italy, the Netherlands, Poland, Spain and the UK. In addition, NSCLC patients were followed up every 6 months for 36 months. A European Bronchial Tissue Bank was set up at the University of Liverpool (Liverpool, UK) to optimise the use of biological specimens. The molecular - pathological investigations were subdivided into specific work packages that were delivered by EUELC Partners. The work packages encompassed mutational analysis, genetic instability, methylation profiling, expression profiling utilising immunohistochemistry and chip-based technologies, as well as in-depth analysis of FHIT and RARβ genes, the telomerase catalytic subunit hTERT and genotyping of susceptibility genes in specific pathways. The EUELC project engendered a tremendous collaborative effort, and it enabled the EUELC Partners to establish protocols for assessing molecular biomarkers in early lung cancer with the view to using such biomarkers for early diagnosis and as intermediate end-points in future chemopreventive programmes. Copyright©ERS Journals Ltd 2009.

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Despite positive results in large scale chemoprevention trials, many physicians are unaware of the potential cancer preventive properties of drugs in common usage. The antioestrogen tamoxifen and the selective cyclo-oxygenase-2 inhibitor celecoxib have been licensed in the USA for the chemoprevention of breast and colorectal cancers respectively in selected high risk individuals. Similarly, folate and retinol have been shown to decrease the incidence of colorectal cancer and squamous cell carcinoma of the skin respectively in large scale intervention trials. Other retinoids have proved efficacious in the tertiary chemoprevention of cancers of the breast and head/neck. Epidemiological evidence also exists in favour of aspirin, nonsteroidal anti-inflammatory drugs, and angiotensin converting enzyme inhibitors preventing certain cancers. Phytochemicals may represent less toxic alternatives to these agents. Although some of these drugs are available without prescription and most are not yet licensed for use in cancer chemoprevention, physicians and students of medicine should be aware of this accumulating evidence base. Practitioners should be amenable to patient referral to discuss complex issues such as risk estimation or potential benefit from intervention.