National Standards for Children's Residential Centres

The Department of Health and Children and the Social Services Inspectorate in conjunction with representatives of the Health Boards have developed these National Standards for the inspection of childrenâ?Ts residential centres, both statutory and nonstatutory Download the Report here

The Swiss Systemic lupus erythematosus Cohort Study (SSCS) - cross-sectional analysis of clinical characteristics and treatments across different medical disciplines in Switzerland.

OBJECTIVES: To describe disease characteristics and treatment modalities in a multidisciplinary cohort of systemic lupus erythematosus (SLE) patients in Switzerland. METHODS: Cross-sectional analysis of 255 patients included in the Swiss SLE Cohort and coming from centres specialised in Clinical Immunology, Internal Medicine, Nephrology and Rheumatology. Clinical data were collected with a standardised form. Disease activity was assessed using the Safety of Estrogens in Lupus Erythematosus National Assessment-SLE Disease Activity Index (SELENA-SLEDAI), an integer physician's global assessment score (PGA) ranging from 0 (inactive) to 3 (very active disease) and the erythrocyte sedimentation rate (ESR). The relationship between SLE treatment and activity was assessed by propensity score methods using a mixed-effect logistic regression with a random effect on the contributing centre. RESULTS: Of the 255 patients, 82% were women and 82% were of European ancestry. The mean age at enrolment was 44.8 years and the median SLE duration was 5.2 years. Patients from Rheumatology had a significantly later disease onset. Renal disease was reported in 44% of patients. PGA showed active disease in 49% of patients, median SLEDAI was 4 and median ESR was 14 millimetre/first hour. Prescription rates of anti-malarial drugs ranged from 3% by nephrologists to 76% by rheumatologists. Patients regularly using anti-malarial drugs had significantly lower SELENA-SLEDAI scores and ESR values. CONCLUSION: In our cohort, patients in Rheumatology had a significantly later SLE onset than those in Nephrology. Anti-malarial drugs were mostly prescribed by rheumatologists and internists and less frequently by nephrologists, and appeared to be associated with less active SLE.

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

"Michael's Game," a card game for the treatment of psychotic symptoms.

Objective: "Michael's Game" is a card game which aims at familiarizing healthcare professionals and patients with cognitive therapy of psychotic symptoms. The present study tests the feasibility and the impact of the intervention in naturalistic settings.Methods: 135 patients were recruited in 11 centres. They were assessed pre- and post-tests with the Beck Cognitive Insight Scale (BCIS) and the Peters Delusion Inventory-21 items (PDI-21).Results: Data about 107 patients were included in the entire analyses. Significant improvements were observed on BCIS subscales as well as a reduction of severity of conviction and preoccupation scores on the PDI-21. The intervention has a moderate effect on the PDI-21 preoccupation and conviction as well as the BCIS subscales. Patients who benefit the most from the program are patients who have a low degree of self-reflectiveness and patients who are concomitantly preoccupied by their symptoms.Conclusion: The present study supports the feasibility and effectiveness of "Michael's Game" in naturalistic settings.Practical implications: The game seems to be a useful tool for patients with psychotic disorders. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Selecting control genes for RT-QPCR using public microarray data.

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

Disseny i implementació d'una base de dades relacional per al manteniment d'aparells d'una empresa

Aquest projecte neix de la necessitat de la nostra empresa client de controlar la gestió del manteniment de tots els equips que té instal·lats en 32 centres i del qual s'encarreguen diverses empreses de serveis especialitzades. Així, per una banda, es tracta de fer l'anàlisi i disseny de la base de dades operacional, els scripts de creació necessaris per a crear la base de dades e implementar els procediments mitjançant els quals es gestionarà i accedirà a la informació de la base de dades. I per una altra banda, es tracta de fer l'anàlisi, disseny e implementació d'un magatzem de dades, per tal de poder explotar la informació per a la presa de decisions.

Disseny i implementació d'una base de dades relacional per al manteniment d'aparells d'una empresa

Una empresa ens contracta ja que té la necessitat de controlar la gestió del manteniment de tots els aparells que té instal·lats en els 32 centres de treball de que disposa (com poden ser extintors, calderes, aire condicionat, fotocopiadores, escàners, impressores, plotters, etc.), i el manteniment el porten a terme diferents empreses de serveis especialitzades. Aquesta gestió i l'accés a tota la informació necessària es realitzarà mitjançant procediments de Base de Dades.La Base de Dades que es crearà ha de ser capaç de portar a terme la gestió de manteniment de tot el maquinari existent en cadascun dels centres de l'empresa, i ha de disposar d'eines que permetin, per una banda, tractar correctament la informació referent als diferents tipus de manteniment (preventiu, correctiu, adaptatiu) que es pot aplicar als diferents equips, i per l'altra, que li permetin incorporar a la Base de Dades aquelles necessites futures, és a dir, que li permetin ser escalable.Aquesta Base de Dades també disposarà de mecanismes que li permetin tractar possibles problemes d'integració amb la resta del sistema, com per exemple, la creació d'un log de les diferents accions fetes amb la Base de Dades, o diferents mecanismes per fer diversos tests de les funcionalitats del sistema.A part de la gestió de manteniment, es disposarà també un magatzem de dades (DataWarehouse) per tal de poder analitzar la informació que conté la Base de Dades anteriorment esmentada, amb l'objectiu d'ajudar a prendre decisions sobre les dades existents en un moment donat.El projecte està dividit en dos blocs principals, on el primer es dissenyarà i s'implementarà una Base de Dades relacional, amb la seva definició de requeriments, l'anàlisi i disseny, desenvolupament de procediments de base de dades i proves per testejar el correcte funcionament, mentre que el segon es dissenyarà i s'implementarà un magatzem de dades (DataWarehouse) per explotar les dades existents en la base de dades relacional.

HIV and STI surveillance in Northern Ireland 2010: An analysis of data for the calendar year 2009

This annual analysis of data provides an overview of HIV and STI epidemiology in Northern Ireland for the calendar year 2009. Information from a variety of sources is collated and analysed in detail, while any evident trends over time are highlightedwithgraphs and tables. As well as a general summary of STI diagnoses and a number of overall conclusions, the report looks specifically at each of the following STIs: chlamydia, gonorrhoea, genital herpes, genital warts, syphilis, lymphogranuloma venereum (LGV) and HIV.