146 resultados para Managing Arthritis
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Introduction: Methotrexate (MTX) is a cornerstone of treatment in a wide variety of inflammatory conditions, including juvenile idiopathic arthritis (JIA) and juvenile dermatomyositis (JDM). However, owing to its narrow therapeutic index and the considerable interpatient variability in clinical response, monitoring of adherence to MTX is important. The present study demonstrates the feasibility of using methotrexate polyglutamates (MTXPGs) as a biomarker to measure adherence to MTX treatment in children with JIA and JDM.
Methods: Data were collected prospectively from a cohort of 48 children (median age 11.5 years) who received oral or subcutaneous (SC) MTX therapy for JIA or JDM. Dried blood spot samples were obtained from children by finger pick at the clinic or via self- or parent-led sampling at home, and they were analysed to determine the variability in MTXPG concentrations and assess adherence to MTX therapy.
Results: Wide fluctuations in MTXPG total concentrations (>2.0-fold variations) were found in 17 patients receiving stable weekly doses of MTX, which is indicative of nonadherence or partial adherence to MTX therapy. Age (P = 0.026) and route of administration (P = 0.005) were the most important predictors of nonadherence to MTX treatment. In addition, the study showed that MTX dose and route of administration were significantly associated with variations in the distribution of MTXPG subtypes. Higher doses and SC administration of MTX produced higher levels of total MTXPGs and selective accumulation of longer-chain MTXPGs (P < 0.001 and P < 0.0001, respectively).
Conclusions: Nonadherence to MTX therapy is a significant problem in children with JIA and JDM. The present study suggests that patients with inadequate adherence and/or intolerance to oral MTX may benefit from SC administration of the drug. The clinical utility of MTXPG levels to monitor and optimise adherence to MTX in children has been demonstrated.Trial Registration: ISRCTN Registry identifier: ISRCTN93945409 . Registered 2 December 2011.
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Perfect information is seldom available to man or machines due to uncertainties inherent in real world problems. Uncertainties in geographic information systems (GIS) stem from either vague/ambiguous or imprecise/inaccurate/incomplete information and it is necessary for GIS to develop tools and techniques to manage these uncertainties. There is a widespread agreement in the GIS community that although GIS has the potential to support a wide range of spatial data analysis problems, this potential is often hindered by the lack of consistency and uniformity. Uncertainties come in many shapes and forms, and processing uncertain spatial data requires a practical taxonomy to aid decision makers in choosing the most suitable data modeling and analysis method. In this paper, we: (1) review important developments in handling uncertainties when working with spatial data and GIS applications; (2) propose a taxonomy of models for dealing with uncertainties in GIS; and (3) identify current challenges and future research directions in spatial data analysis and GIS for managing uncertainties.
Resumo:
Background/Purpose:Juvenile idiopathic arthritis (JIA) comprises a poorly understood group of chronic, childhood onset, autoimmune diseases with variable clinical outcomes. We investigated whether profiling of the synovial fluid (SF) proteome by a fluorescent dye based, two-dimensional gel (DIGE) approach could distinguish the subset of patients in whom inflammation extends to affect a large number of joints, early in the disease process. The post-translational modifications to candidate protein markers were verified by a novel deglycosylation strategy.Methods:SF samples from 57 patients were obtained around time of initial diagnosis of JIA. At 1 year from inclusion patients were categorized according to ILAR criteria as oligoarticular arthritis (n=26), extended oligoarticular (n=8) and polyarticular disease (n=18). SF samples were labeled with Cy dyes and separated by two-dimensional electrophoresis. Multivariate analyses were used to isolate a panel of proteins which distinguish patient subgroups. Proteins were identified using MALDI-TOF mass spectrometry with vitamin D binding protein (VDBP) expression and siaylation further verified by immunohistochemistry, ELISA test and immunoprecipitation. Candidate biomarkers were compared to conventional inflammation measure C-reactive protein (CRP). Sialic acid residues were enzymatically cleaved from immunopurified SF VDBP, enriched by hydrophilic interaction liquid chromatography (HILIC) and analysed by mass spectrometry.Results:Hierarchical clustering based on the expression levels of a set of 23 proteins segregated the extended-to-be oligoarticular from the oligoarticular patients. A cleaved isoform of VDBP, spot 873, is present at significantly reduced levels in the SF of oligoarticular patients at risk of disease extension, relative to other subgroups (p<0.05). Conversely total levels of vitamin D binding protein are elevated in plasma and ROC curves indicate an improved diagnostic sensitivity to detect patients at risk of disease extension, over both spot 873 and CRP levels. Sialysed forms of intact immunopurified VDBP were more prevalent in persistent oligoarticular patient synovial fluids.Conclusion:The data indicate that a subset of the synovial fluid proteome may be used to stratify patients to determine risk of disease extension. Reduced conversion of VDBP to a macrophage activation factor may represent a novel pathway contributing to increased risk of disease extension in JIA patients.
Resumo:
Objective The aim of this study was to collate and compare data on the training of Specialty Registrars in Restorative Dentistry (StRs) in the management of head and neck cancer (HANC) patients across different training units within the UK and Ireland. Methods Current trainees were invited to complete an online questionnaire by the Specialty Registrars in Restorative Dentistry Group (SRRDG). Participants were asked to rate their confidence and experience of assessing and planning treatment for HANC patients, attending theatre alone and manufacturing surgical obturators, and providing implants for appropriate cases. Respondents were also asked to appraise clinical and didactic teaching at their unit, and to rate their confidence of passing a future Intercollegiate Specialty Fellowship Examination (ISFE)-station assessing knowledge of head and neck cancer. Results Responses were obtained from 21 StRs (n=21) training within all five countries of the British Isles. Most respondents were based in England (76%), with one StR in each of Scotland, Wales, Northern Ireland and the Republic of Ireland. A third (33%) were in their 5th year of training. Almost half of the StRs indicated that they were confident of independently assessing (48%) new patients with HANC, with fewer numbers reporting confidence in treatment planning (38%). The majority (52%) of respondents indicated that they were not confident of attending theatre alone and manufacturing a surgical obturator. A third (33%) rated their experience of treating HANC patients with implants as ‘poor’ or ‘very poor’, including three StRs in their 5th year of training. Less than one third (<33%) rated didactic teaching in maxillofacial prosthodontics at their unit as ‘good’ or ‘excellent’, and only 7 StRs indicated that they were confident of passing an ISFE-station focused on HANC. Conclusion Experience and training regarding patients with head and neck cancer is inconsistent for StRs across the UK and Ireland with a number of trainees reporting a lack of clinical exposure.
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In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis of both soil measurements and climatic variables gathered by several autonomous nodes deployed in field. This enables a closed loop control scheme to adapt the decision support system to local perturbations and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in the South-East of Spain. Performance is tested against decisions taken by a human expert.
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Abstract
Complexity and environmental uncertainty in public sector systems requires leaders to balance the administrative practices necessary to be aligned and efficient in the management of routine challenges, and the adaptive practices required to respond to complex and dynamic circumstances. Conventional notions of leadership in the field of public administration do not fully explain the role of leadership in enabling and balancing the entanglement of formal, top-down, administrative functions and informal, emergent, adaptive functions within public sector settings with different levels of complexity. Drawing on and extending existing complexity leadership constructs, this paper explores how change was enabled over the duration of three urban regeneration projects, each representing high, medium and low levels of project complexity. The data reveals six distinct yet interconnected functions of enabling leadership that were identified within the three urban regeneration projects. The paper contributes to our understanding of how leadership is enacted and poses questions for those engaged in leading in complex public sector settings.