5 resultados para GALAXIES: GROUPS: GENERAL

em CentAUR: Central Archive University of Reading - UK


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The prevalence of the metabolic syndrome (MetS), CVD and type 2 diabetes (T2D) is known to be higher in populations from the Indian subcontinent compared with the general UK population. While identification of this increased risk is crucial to allow for effective treatment, there is controversy over the applicability of diagnostic criteria, and particularly measures of adiposity in ethnic minorities. Diagnostic cut-offs for BMI and waist circumference have been largely derived from predominantly white Caucasian populations and, therefore, have been inappropriate and not transferable to Asian groups. Many Asian populations, particularly South Asians, have a higher total and central adiposity for a similar body weight compared with matched Caucasians and greater CVD risk associated with a lower BMI. Although the causes of CVD and T2D are multi-factorial, diet is thought to make a substantial contribution to the development of these diseases. Low dietary intakes and tissue levels of long-chain (LC) n-3 PUFA in South Asian populations have been linked to high-risk abnormalities in the MetS. Conversely, increasing the dietary intake of LC n-3 PUFA in South Asians has proved an effective strategy for correcting such abnormalities as dyslipidaemia in the MetS. Appropriate diagnostic criteria that include a modified definition of adiposity must be in place to facilitate the early detection and thus targeted treatment of increased risk in ethnic minorities.

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The UK700 trial failed to demonstrate an overall benefit of intensive case management (ICM) in patients with severe psychotic illness. This does not discount a benefit for particular subgroups, and evidence of a benefit of ICM for patients of borderline intelligence has been presented. The aim of this study is to investigate whether this effect is part of a general benefit for patients with severe psychosis complicated by additional needs. In the UK700 trial patients with severe psychosis were randomly allocated to ICM or standard case management. For each patient group with complex needs the effect of ICM is compared with that in the rest of the study cohort. Outcome measures are days spent in psychiatric hospital and the admission and discharge rates. ICM may be of benefit to patients with severe psychosis complicated by borderline intelligence or depression, but may cause patients using illicit drugs to spend more time in hospital. There was no convincing evidence of an effect of ICM in a further seven patient groups. ICM is not of general benefit to patients with severe psychosis complicated by additional needs. The benefit of ICM for patients with borderline intelligence is an isolated effect which should be interpreted cautiously until further data are available.

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The clusters [Fe3(CO)11(RCN)] (1: R = Me, C3H5, C6H5, or C6H4-2-Me) have been prepared at low temperature from [Fe3(CO)12] and RCN in the presence of Me3NO. Compounds 1 react essentially quantitatively with a wide range of two-electron donors, L, (viz.: CO, PPh3, P(OMe)3, PPh2H, PPh2Me, PF3, CyNC (Cy = cyclohexyl), P(OEt)3, SbPh3, PBu3, AsPh3, or SnR2 (R = CH(SiMe3)2)) to give [Fe3(CO)11L] (2). In some cases (2), on treatment with Me3NO and then L′ (L′ = a second two-electron donor) yields [Fe3(CO)10LL′] in high yield. The crystal and molecular structures of 1 (L = NCC6H4Me-2) have been determined by a full single crystal structure analysis, and shown to have an axial nitrile coordinated at the unique iron atom, with two CO groups bridging the other two metal atoms.

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Aim: To determine the prevalence and nature of prescribing errors in general practice; to explore the causes, and to identify defences against error. Methods: 1) Systematic reviews; 2) Retrospective review of unique medication items prescribed over a 12 month period to a 2% sample of patients from 15 general practices in England; 3) Interviews with 34 prescribers regarding 70 potential errors; 15 root cause analyses, and six focus groups involving 46 primary health care team members Results: The study involved examination of 6,048 unique prescription items for 1,777 patients. Prescribing or monitoring errors were detected for one in eight patients, involving around one in 20 of all prescription items. The vast majority of the errors were of mild to moderate severity, with one in 550 items being associated with a severe error. The following factors were associated with increased risk of prescribing or monitoring errors: male gender, age less than 15 years or greater than 64 years, number of unique medication items prescribed, and being prescribed preparations in the following therapeutic areas: cardiovascular, infections, malignant disease and immunosuppression, musculoskeletal, eye, ENT and skin. Prescribing or monitoring errors were not associated with the grade of GP or whether prescriptions were issued as acute or repeat items. A wide range of underlying causes of error were identified relating to the prescriber, patient, the team, the working environment, the task, the computer system and the primary/secondary care interface. Many defences against error were also identified, including strategies employed by individual prescribers and primary care teams, and making best use of health information technology. Conclusion: Prescribing errors in general practices are common, although severe errors are unusual. Many factors increase the risk of error. Strategies for reducing the prevalence of error should focus on GP training, continuing professional development for GPs, clinical governance, effective use of clinical computer systems, and improving safety systems within general practices and at the interface with secondary care.

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Aim: To examine the causes of prescribing and monitoring errors in English general practices and provide recommendations for how they may be overcome. Design: Qualitative interview and focus group study with purposive sampling and thematic analysis informed by Reason’s accident causation model. Participants: General practice staff participated in a combination of semi-structured interviews (n=34) and six focus groups (n=46). Setting: Fifteen general practices across three primary care trusts in England. Results: We identified seven categories of high-level error-producing conditions: the prescriber, the patient, the team, the task, the working environment, the computer system, and the primary-secondary care interface. Each of these was further broken down to reveal various error-producing conditions. The prescriber’s therapeutic training, drug knowledge and experience, knowledge of the patient, perception of risk, and their physical and emotional health, were all identified as possible causes. The patient’s characteristics and the complexity of the individual clinical case were also found to have contributed to prescribing errors. The importance of feeling comfortable within the practice team was highlighted, as well as the safety of general practitioners (GPs) in signing prescriptions generated by nurses when they had not seen the patient for themselves. The working environment with its high workload, time pressures, and interruptions, and computer related issues associated with mis-selecting drugs from electronic pick-lists and overriding alerts, were all highlighted as possible causes of prescribing errors and often interconnected. Conclusion: This study has highlighted the complex underlying causes of prescribing and monitoring errors in general practices, several of which are amenable to intervention.