The incidence of all stroke and stroke subtype in the United Kingdom, 1985 to 2008: a systematic review

<p>Abstract</p> <p>Background</p> <p>There is considerable geographic variation in stroke mortality around the United Kingdom (UK). Whether this is due to geographical differences in incidence or case-fatality is unclear. We conducted a systematic review of high-quality studies documenting the incidence of any stroke and stroke subtypes, between 1985 and 2008 in the UK. We aimed to study geographic and temporal trends in relation to equivalent mortality trends.</p> <p>Methods</p> <p>MEDLINE and EMBASE were searched, reference lists inspected and authors of included papers were contacted. All rates were standardised to the European Standard Population for those over 45, and between 45 and 74 years. Stroke mortality rates for the included areas were then calculated to produce rate ratios of stroke mortality to incidence for each location.</p> <p>Results</p> <p>Five papers were included in this review. Geographic variation was narrow but incidence appeared to largely mirror mortality rates for all stroke. For men over 45, incidence (and confidence intervals) per 100,000 ranged from 124 (109-141) in South London, to 185 (164-208) in Scotland. For men, premature (45-74 years) stroke incidence per 100,000 ranged from 79 (67-94) in the North West, to 112 (95-132) in Scotland. Stroke subtype data was more geographically restricted, but did suggest there is no sizeable variation in incidence by subtype around the country. Only one paper, based in South London, had data on temporal trends. This showed that there has been a decline in stroke incidence since the mid 1990 s. This could not be compared to any other locations in this review.</p> <p>Conclusions</p> <p>Geographic variations in stroke incidence appear to mirror variations in mortality rates. This suggests policies to reduce inequalities in stroke mortality should be directed at risk factor profiles rather than treatment after a first incident event. More high quality stroke incidence data from around the UK are needed before this can be confirmed.</p

Effect of an Education Programme for South Asians with Asthma and Their Clinicians: A Cluster Randomised Controlled Trial (OEDIPUS).

BACKGROUND: People with asthma from ethnic minority groups experience significant morbidity. Culturally-specific interventions to reduce asthma morbidity are rare. We tested the hypothesis that a culturally-specific education programme, adapted from promising theory-based interventions developed in the USA, would reduce unscheduled care for South Asians with asthma in the UK. METHODS: A cluster randomised controlled trial, set in two east London boroughs. 105 of 107 eligible general practices were randomised to usual care or the education programme. Participants were south Asians with asthma aged 3 years and older with recent unscheduled care. The programme had two components: the Physician Asthma Care Education (PACE) programme and the Chronic Disease Self Management Programme (CDSMP), targeted at clinicians and patients with asthma respectively. Both were culturally adapted for south Asians with asthma. Specialist nurses, and primary care teams from intervention practices were trained using the PACE programme. South Asian participants attended an outpatient appointment; those registered with intervention practices received self-management training from PACE-trained specialist nurses, a follow-up appointment with PACE-trained primary care practices, and an invitation to attend the CDSMP. Patients from control practices received usual care. Primary outcome was unscheduled care. FINDINGS: 375 south Asians with asthma from 84 general practices took part, 183 registered with intervention practices and 192 with control practices. Primary outcome data were available for 358/375 (95.5%) of participants. The intervention had no effect on time to first unscheduled attendance for asthma (Adjusted Hazard Ratio AHR = 1.19 95% CI 0.92 to 1.53). Time to first review in primary care was reduced (AHR = 2.22, (1.67 to 2.95). Asthma-related quality of life and self-efficacy were improved at 3 months (adjusted mean difference -2.56, (-3.89 to -1.24); 0.44, (0.05 to 0.82) respectively. CONCLUSIONS: A multi-component education programme adapted for south Asians with asthma did not reduce unscheduled care but did improve follow-up in primary care, self-efficacy and quality of life. More effective interventions are needed for south Asians with asthma

Iliou Machine Learning Data Preprocessing Method for Stress Level Prediction

Part 7: Medical IntelligenceInternational audienceData pre-processing is an important step in the data mining process. Data preparation and filtering steps can take considerable amount of processing time. Data pre-processing includes cleaning, normalization, transformation, feature extraction and selection. In this paper, Iliou and PCA data preprocessing methods evaluated in a data set of 103 students, aged 18–25, who were experiencing anxiety problems. The performance of Iliou and PCA data preprocessing methods was evaluated using the 10-fold cross validation method assessing seven classification algorithms, IB1, J48, Random Forest, MLP, SMO, JRip and FURIA, respectively. The classification results indicate that Iliou data preprocessing algorithm consistently and substantially outperforms PCA data preprocessing method, achieving 98.6% against 92.2% classification performance, respectively

Mining biomarker information in biomedical literature

<p>Abstract</p> <p>Background</p> <p>For selection and evaluation of potential biomarkers, inclusion of already published information is of utmost importance. In spite of significant advancements in text- and data-mining techniques, the vast knowledge space of biomarkers in biomedical text has remained unexplored. Existing named entity recognition approaches are not sufficiently selective for the retrieval of biomarker information from the literature. The purpose of this study was to identify textual features that enhance the effectiveness of biomarker information retrieval for different indication areas and diverse end user perspectives.</p> <p>Methods</p> <p>A biomarker terminology was created and further organized into six concept classes. Performance of this terminology was optimized towards balanced selectivity and specificity. The information retrieval performance using the biomarker terminology was evaluated based on various combinations of the terminology's six classes. Further validation of these results was performed on two independent corpora representing two different neurodegenerative diseases.</p> <p>Results</p> <p>The current state of the biomarker terminology contains 119 entity classes supported by 1890 different synonyms. The result of information retrieval shows improved retrieval rate of informative abstracts, which is achieved by including clinical management terms and evidence of gene/protein alterations (e.g. gene/protein expression status or certain polymorphisms) in combination with disease and gene name recognition. When additional filtering through other classes (e.g. diagnostic or prognostic methods) is applied, the typical high number of unspecific search results is significantly reduced. The evaluation results suggest that this approach enables the automated identification of biomarker information in the literature. A demo version of the search engine SCAIView, including the biomarker retrieval, is made available to the public through <url>http://www.scaiview.com/scaiview-academia.html</url>.</p> <p>Conclusions</p> <p>The approach presented in this paper demonstrates that using a dedicated biomarker terminology for automated analysis of the scientific literature maybe helpful as an aid to finding biomarker information in text. Successful extraction of candidate biomarkers information from published resources can be considered as the first step towards developing novel hypotheses. These hypotheses will be valuable for the early decision-making in the drug discovery and development process.</p