290 research outputs found

    A holistic multi-methodology for sustainable renovation

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    A review of the barriers for building renovation has revealed a lack of methodologies, which can promote sustainability objectives and assist various stakeholders during the design stage of building renovation/retrofitting projects. The purpose of this paper is to develop a Holistic Multi-methodology for Sustainable Renovation, which aims to deal with complexity of renovation projects. It provides a framework through which to involve the different stakeholders in the design process to improve group learning and group decision-making, and hence make the building renovation design process more robust and efficient. Therefore, the paper discusses the essence of multifaceted barriers in building renovation regarding cultural changes and technological/physical changes. The outcome is a proposal for a multi-methodology framework, which is developed by introducing, evaluating and mixing methods from Soft Systems Methodologies (SSM) with Multiple Criteria Decision Making (MCDM). The potential of applying the proposed methodology in renovation projects is demonstrated through a case study

    Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

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    Abstract Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.http://deepblue.lib.umich.edu/bitstream/2027.42/78272/1/1748-5908-4-50.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/2/1748-5908-4-50-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/3/1748-5908-4-50-S3.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/4/1748-5908-4-50-S4.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/5/1748-5908-4-50.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/6/1748-5908-4-50-S2.PDFPeer Reviewe

    Early prediction of response to radiotherapy and androgen-deprivation therapy in prostate cancer by repeated functional MRI: a preclinical study

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    <p>Abstract</p> <p>Background</p> <p>In modern cancer medicine, morphological magnetic resonance imaging (MRI) is routinely used in diagnostics, treatment planning and assessment of therapeutic efficacy. During the past decade, functional imaging techniques like diffusion-weighted (DW) MRI and dynamic contrast-enhanced (DCE) MRI have increasingly been included into imaging protocols, allowing extraction of intratumoral information of underlying vascular, molecular and physiological mechanisms, not available in morphological images. Separately, pre-treatment and early changes in functional parameters obtained from DWMRI and DCEMRI have shown potential in predicting therapy response. We hypothesized that the combination of several functional parameters increased the predictive power.</p> <p>Methods</p> <p>We challenged this hypothesis by using an artificial neural network (ANN) approach, exploiting nonlinear relationships between individual variables, which is particularly suitable in treatment response prediction involving complex cancer data. A clinical scenario was elicited by using 32 mice with human prostate carcinoma xenografts receiving combinations of androgen-deprivation therapy and/or radiotherapy. Pre-radiation and on days 1 and 9 following radiation three repeated DWMRI and DCEMRI acquisitions enabled derivation of the apparent diffusion coefficient (ADC) and the vascular biomarker <it>K</it><sup>trans</sup>, which together with tumor volumes and the established biomarker prostate-specific antigen (PSA), were used as inputs to a back propagation neural network, independently and combined, in order to explore their feasibility of predicting individual treatment response measured as 30 days post-RT tumor volumes.</p> <p>Results</p> <p>ADC, volumes and PSA as inputs to the model revealed a correlation coefficient of 0.54 (p < 0.001) between predicted and measured treatment response, while <it>K</it><sup>trans</sup>, volumes and PSA gave a correlation coefficient of 0.66 (p < 0.001). The combination of all parameters (ADC, <it>K</it><sup>trans</sup>, volumes, PSA) successfully predicted treatment response with a correlation coefficient of 0.85 (p < 0.001).</p> <p>Conclusions</p> <p>We have in a preclinical investigation showed that the combination of early changes in several functional MRI parameters provides additional information about therapy response. If such an approach could be clinically validated, it may become a tool to help identifying non-responding patients early in treatment, allowing these patients to be considered for alternative treatment strategies, and, thus, providing a contribution to the development of individualized cancer therapy.</p

    The Extended Learning Curve for Laparoscopic Fundoplication: A Cohort Analysis Of 400 Consecutive Cases

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    Many studies have looked at the learning curve associated with laparoscopic Nissen fundoplication (LNF) in a given institution. This study looks at the learning curve of a single surgeon with a large cohort of patients over a 10-year period. Prospective data were collected on 400 patients undergoing laparoscopic fundoplication for over 10 years. The patients were grouped consecutively into cohorts of 50 patients. The operating time, the length of postoperative hospital stay, the conversion rate to open operation, the postoperative dilatation rate, and the reoperation rate were analyzed. Results showed that the mean length of operative time decreased from 143 min in the first 50 patients to 86 min in the last 50 patients. The mean postoperative length of hospital stay decreased from 3.7 days initially to 1.2 days latterly. There was a 14% conversion to open operation rate in the first cohort compared with a 2% rate in the last cohort. Fourteen percent of patients required reoperation in the first cohort and 6% in the last cohort. Sixteen percent required postoperative dilatation in the first cohort. None of the last 150 patients required dilatation. In conclusion, laparoscopic fundoplication is a safe and effective operation for patients with gastroesophageal reflux disease. New techniques and better instrumentation were introduced in the early era of LNF. The learning curve, however, continues well beyond the first 20 patients

    Diffusion-weighted whole-body imaging with background body signal suppression (DWIBS): features and potential applications in oncology

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    Diffusion-weighted magnetic resonance imaging (DWI) provides functional information and can be used for the detection and characterization of pathologic processes, including malignant tumors. The recently introduced concept of “diffusion-weighted whole-body imaging with background body signal suppression” (DWIBS) now allows acquisition of volumetric diffusion-weighted images of the entire body. This new concept has unique features different from conventional DWI and may play an important role in whole-body oncological imaging. This review describes and illustrates the basics of DWI, the features of DWIBS, and its potential applications in oncology
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