17 research outputs found

    Multidimensional prognostic indices for use in COPD patient care. A systematic review

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    Contains fulltext : 98117.pdf (publisher's version ) (Open Access)BACKGROUND: A growing number of prognostic indices for chronic obstructive pulmonary disease (COPD) is developed for clinical use. Our aim is to identify, summarize and compare all published prognostic COPD indices, and to discuss their performance, usefulness and implementation in daily practice. METHODS: We performed a systematic literature search in both Pubmed and Embase up to September 2010. Selection criteria included primary publications of indices developed for stable COPD patients, that predict future outcome by a multidimensional scoring system, developed for and validated with COPD patients only. Two reviewers independently assessed the index quality using a structured screening form for systematically scoring prognostic studies. RESULTS: Of 7,028 articles screened, 13 studies comprising 15 indices were included. Only 1 index had been explored for its application in daily practice. We observed 21 different predictors and 7 prognostic outcomes, the latter reflecting mortality, hospitalization and exacerbation. Consistent strong predictors were FEV1 percentage predicted, age and dyspnoea. The quality of the studies underlying the indices varied between fairly poor and good. Statistical methods to assess the predictive abilities of the indices were heterogenic. They generally revealed moderate to good discrimination, when measured. Limitations: We focused on prognostic indices for stable disease only and, inevitably, quality judgment was prone to subjectivity. CONCLUSIONS: We identified 15 prognostic COPD indices. Although the prognostic performance of some of the indices has been validated, they all lack sufficient evidence for implementation. Whether or not the use of prognostic indices improves COPD disease management or patients' health is currently unknown; impact studies are required to establish this

    How SEIDET achieved success - an exploration from the perspective of innovation theory

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    The purpose of this chapter is to assess SEIDET's achievements in the first 10 years of its existence, and to explore the main factors that drove its attainments. There is no doubt that the project has indeed become very successful. Judging by the results of the analysis in Chapter 4, its participants certainly seem to think so. The response from the entire community to the project from its inception has been beyond expectation, indicating that there was a need for it, and that the need was perceived as such by the community. Teaching has been expanding ever since the first classes started back in 1992. New programmes have been added, new branches have been established, and computer literacy courses have been made part of the programme. Currently SEIDET owns a community education centre in Siyabuswa, while two other branches of the project are hosted at other institutions. The main centre in Siyabuswa has grown into a multi-purpose facility providing a variety of educational services and developmental programmes to the local community in association with several other institutions, including the South African Department of Education. ICT was introduced at SEIDET in 1994, when the Executive Committee approached the Department of Informatics at the University of Pretoria. Ever since, a mutually beneficial relationship has existed between the department and SEIDET. The first full computer laboratory was established in 1998, and the computers on the main centre were connected to a LAN and the Internet in 2000. At the time of our research (in 2003) there were plans for establishing an IT support centre and to provide Internet and end-user services to the general public on a commercial basis

    Remedial education for black children in rural South Africa : an exploration of success using evolutionary innovation theory

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    Why people volunteer for SEIDET : an analysis of motivations

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    In the previous chapter we described in detail the manner in which SEIDET was initiated and developed. We noted a striking resemblance with the evolution of open source software projects like Linux and Apache, which rely on loosely coordinated ongoing incremental innovation and learning among interacting members of innovation groups. Many of these members are volunteers. The evolutionary learning process by which SEIDET was born and grew up was examined using conceptual insights from evolutionary innovation theory, notably Boru Douthwaite’s Learning Selection model, which is inspired by Raymond’s ‘bazaar-type’ model of open source innovation
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