36 resultados para arm


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In spite of its different cantonal jurisdictions and traditions, the development of religious education in Switzerland over the past decade has taken a common direction: the state has assumed a more active role in the field of religious education in public (state-run) schools. In this article, we ask the question: How do key social actors interpret these reforms and how do these interpretations relate to the social structure of religion in Switzerland, in particular with respect to the majority category of the so-called distanced Christians? Drawing on qualitative interviews with members of the schools’ teaching staff, school administrators, and church representatives, the article highlights a dominant interpretative pattern that frames the socially accepted representation of religion in public schools. Thus, rather than addressing the pedagogical dimension of religious education, we discuss the significance of this pattern for the debate on the public presence of religion in Switzerland and Europe.

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BACKGROUND Prostate cancer (PCa) is the second most common disease among men worldwide. It is important to know survival outcomes and prognostic factors for this disease. Recruitment for the largest therapeutic randomised controlled trial in PCa-the Systemic Therapy in Advancing or Metastatic Prostate Cancer: Evaluation of Drug Efficacy: A Multi-Stage Multi-Arm Randomised Controlled Trial (STAMPEDE)-includes men with newly diagnosed metastatic PCa who are commencing long-term androgen deprivation therapy (ADT); the control arm provides valuable data for a prospective cohort. OBJECTIVE Describe survival outcomes, along with current treatment standards and factors associated with prognosis, to inform future trial design in this patient group. DESIGN, SETTING, AND PARTICIPANTS STAMPEDE trial control arm comprising men newly diagnosed with M1 disease who were recruited between October 2005 and January 2014. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Overall survival (OS) and failure-free survival (FFS) were reported by primary disease characteristics using Kaplan-Meier methods. Hazard ratios and 95% confidence intervals (CIs) were derived from multivariate Cox models. RESULTS AND LIMITATIONS A cohort of 917 men with newly diagnosed M1 disease was recruited to the control arm in the specified interval. Median follow-up was 20 mo. Median age at randomisation was 66 yr (interquartile range [IQR]: 61-71), and median prostate-specific antigen level was 112 ng/ml (IQR: 34-373). Most men (n=574; 62%) had bone-only metastases, whereas 237 (26%) had both bone and soft tissue metastases; soft tissue metastasis was found mainly in distant lymph nodes. There were 238 deaths, 202 (85%) from PCa. Median FFS was 11 mo; 2-yr FFS was 29% (95% CI, 25-33). Median OS was 42 mo; 2-yr OS was 72% (95% CI, 68-76). Survival time was influenced by performance status, age, Gleason score, and metastases distribution. Median survival after FFS event was 22 mo. Trial eligibility criteria meant men were younger and fitter than general PCa population. CONCLUSIONS Survival remains disappointing in men presenting with M1 disease who are started on only long-term ADT, despite active treatments being available at first failure of ADT. Importantly, men with M1 disease now spend the majority of their remaining life in a state of castration-resistant relapse. PATIENT SUMMARY Results from this control arm cohort found survival is relatively short and highly influenced by patient age, fitness, and where prostate cancer has spread in the body.

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In this paper, we propose a new method for stitching multiple fluoroscopic images taken by a C-arm instrument. We employ an X-ray radiolucent ruler with numbered graduations while acquiring the images, and the image stitching is based on detecting and matching ruler parts in the images to the corresponding parts of a virtual ruler. To achieve this goal, we first detect the regular spaced graduations on the ruler and the numbers. After graduation labeling, for each image, we have the location and the associated number for every graduation on the ruler. Then, we initialize the panoramic X-ray image with the virtual ruler, and we “paste” each image by aligning the detected ruler part on the original image, to the corresponding part of the virtual ruler on the panoramic image. Our method is based on ruler matching but without the requirement of matching similar feature points in pairwise images, and thus, we do not necessarily require overlap between the images. We tested our method on eight different datasets of X-ray images, including long bones and a complete spine. Qualitative and quantitative experiments show that our method achieves good results.