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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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What factors influence pain scores following Corticosteroid injection in patients with Greater Trochanteric Pain Syndrome? A systematic ReviewFoxcroft, B., Stephens, G., Woodhead, T., Ayre, Colin A. 17 February 2024 (has links)
Yes / Background:
Cortico-steroid Injections (CSI) are commonly used to treat patients with Greater Trochanteric Pain Syndrome (GTPS) but it is unclear which patients will experience improvements in pain
Objectives: To identify factors that influence improvements in pain for patients with GTPS treated with CSI
Design: Systematic review
Methods: A search was undertaken of AMED, CINAHL, Cochrane Library, EMBASE, Medline and PEDro databases. Studies were eligible for inclusion of they investigated factors that influenced changes in pain experienced by patients who received a CSI. Studies needed to include relevant summary statistics and tests of clinical significance. Risk Of Bias in Non-randomised Trials Of Interventions (ROBINS-I) and Risk of Bias 2 (ROB2) tools were used to assess bias.
Results: The search identified 466 studies, 8 were included in the final review with a total of 643 participants. There was no association between demographic variables such as age, sex, symptom duration or obesity and pain outcomes post-CSI. Having a co-existing musculoskeletal (MSK) condition such as knee osteoarthritis or sacroiliac/lumbar spine pain was associated with less pain reduction post-CSI. Injections into the Trochanteric Bursa were associated with longer lasting pain reduction than Gluteus Medius Bursa or extra-bursal injections. Image guidance of CSI maintained lower pain scores at six months but did not increase the duration of the therapeutic effect past six months. The presence of specific ultrasound scan features was not associated with differences in pain scores.
Conclusions: Patients with co-existing MSK conditions may not respond to CSI as well as those without. Injections into the Greater Trochanteric Bursa may have longer lasting benefit. Further research is needed on the use of USS imaging findings and image guidance. / This work was completed as part of a pre-doctoral fellowship funded by the National Institute of Health Research [NIHR301938, 2021].
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Introducing Generative Artificial Intelligence in Tech Organizations : Developing and Evaluating a Proof of Concept for Data Management powered by a Retrieval Augmented Generation Model in a Large Language Model for Small and Medium-sized Enterprises in Tech / Introducering av Generativ Artificiell Intelligens i Tech Organisationer : Utveckling och utvärdering av ett Proof of Concept för datahantering förstärkt av en Retrieval Augmented Generation Model tillsammans med en Large Language Model för små och medelstora företag inom TechLithman, Harald, Nilsson, Anders January 2024 (has links)
In recent years, generative AI has made significant strides, likely leaving an irreversible mark on contemporary society. The launch of OpenAI's ChatGPT 3.5 in 2022 manifested the greatness of the innovative technology, highlighting its performance and accessibility. This has led to a demand for implementation solutions across various industries and companies eager to leverage these new opportunities generative AI brings. This thesis explores the common operational challenges faced by a small-scale Tech Enterprise and, with these challenges identified, examines the opportunities that contemporary generative AI solutions may offer. Furthermore, the thesis investigates what type of generative technology is suitable for adoption and how it can be implemented responsibly and sustainably. The authors approach this topic through 14 interviews involving several AI researchers and the employees and executives of a small-scale Tech Enterprise, which served as a case company, combined with a literature review. The information was processed using multiple inductive thematic analyses to establish a solid foundation for the investigation, which led to the development of a Proof of Concept. The findings and conclusions of the authors emphasize the high relevance of having a clear purpose for the implementation of generative technology. Moreover, the authors predict that a sustainable and responsible implementation can create the conditions necessary for the specified small-scale company to grow. When the authors investigated potential operational challenges at the case company it was made clear that the most significant issue arose from unstructured and partially absent documentation. The conclusion reached by the authors is that a data management system powered by a Retrieval model in a LLM presents a potential path forward for significant value creation, as this solution enables data retrieval functionality from unstructured project data and also mitigates a major inherent issue with the technology, namely, hallucinations. Furthermore, in terms of implementation circumstances, both empirical and theoretical findings suggest that responsible use of generative technology requires training; hence, the authors have developed an educational framework named "KLART". Moving forward, the authors describe that sustainable implementation necessitates transparent systems, as this increases understanding, which in turn affects trust and secure use. The findings also indicate that sustainability is strongly linked to the user-friendliness of the AI service, leading the authors to emphasize the importance of HCD while developing and maintaining AI services. Finally, the authors argue for the value of automation, as it allows for continuous data and system updates that potentially can reduce maintenance. In summary, this thesis aims to contribute to an understanding of how small-scale Tech Enterprises can implement generative AI technology sustainably to enhance their competitive edge through innovation and data-driven decision-making.
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