Background: Axial spondyloarthritis (axSpA) is an inflammatory disease associated with significant diagnostic delays and is commonly missed in assessments of persistent back pain.Objective: To explore musculoskeletal physiotherapists' awareness, knowledge and confidence in screening for signs, symptoms and risk factors of suspected axSpA and criteria for rheumatology referral.Design: An online UK survey was undertaken combining back pain vignettes (reflecting axSpA, non-specific back pain and radicular syndrome) and questioning on features of suspected axSpA. Recruitment utilised online professional forums and social media. Data analysis included descriptive statistics and conceptual content analysis for free text responses.Results: 132 survey responses were analysed. Only 67% (88/132) of respondents identified inflammatory pathologies as a possible cause of persistent back pain. Only 60% (79/132) recognised the axSpA vignette compared to non-specific low back pain (94%) and radicular syndrome (80%). Most suspecting axSpA would refer for specialist assessment (77/79; 92%). Awareness of national referral guidance was evident in only 50% of 'clinical reasoning' and 20% of 'further subjective screening' responses. There was misplaced confidence in recognising clinical features of axSpA (≥7/10) compared to knowledge levels shown, including high importance given to inflammatory markers and human leucocyte antigen B27 (median ¼ 8/10).Conclusions: Musculoskeletal physiotherapists may not be giving adequate consideration to axSpA in back pain assessments. Awareness of national referral guidance was also limited. Professional education on screening and referral for suspected axSpA is needed to make axSpA screening and referral criteria core knowledge in musculoskeletal clinical practice, supporting earlier diagnosis and better outcomes.
Background: Axial Spondyloarthritis is an inflammatory disease associated with significant diagnostic delays. Steen et al. (2021) found inadequate consideration of axial Spondyloarthritis (axSpA) in physiotherapists back pain assessments. Since the previous survey, increased professional education on axSpA has occurred and First Contact Practitioners (FCPs), now widely established in General Practice, are key in supporting earlier recognition. Objectives: (1) To re-evaluate physiotherapists' and evaluate FCPs' awareness, knowledge, and confidence in screening for and recognising features of axSpA and criteria prompting referral to rheumatology. (2) To compare these results to previous research (Steen et al., 2021). Design: As per Steen et al. (2021), an online survey was undertaken combining back pain vignettes (reflecting axSpA, non-specific low back pain [NSLBP] and radicular syndrome) and questioning on features of suspected axSpA. Results: 165 surveys were analysed. Only 73% (n = 120/165) of respondents recognised the axSpA vignette compared to NSLBP 91% (n = 80/88) and radicular syndrome 88% (n = 68/77). An improvement in axSpA recognition was demonstrated compared with previous data. FCPs performed slightly better with 77% (n = 67/87) of respondents recognising the axSpA vignette. Adequate awareness of national referral guidance was evident in only 55% of 'clinical reasoning' and 6% of 'further subjective screening' responses. There was still misplaced confidence in recognising clinical features of axSpA compared to knowledge levels shown, including high importance given to inflammatory markers. Conclusion(s):Musculoskeletal physiotherapists demonstrate some improved knowledge and awareness of axSpA compared with previous study findings.Consideration of axSpA is still not universal in musculoskeletal physiotherapists' or FCPs' approaches to persistent back pain assessments and awareness of national referral guidance remains limited. This study highlights the continued need for professional education. Enhanced knowledge of screening and referral criteriaThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
The North Kuwait Carbonate (NKJG) reservoirs are currently under development by KOC (Kuwait Oil Company). In addition to the matrix heterogeneity, natural fracturing poses extra challenges for the optimization of the field development planning. The presence of open, connected fractures presents opportunities for infill drilling but increases the risk of water invasion and drilling related issues. Numerous fracture modelling studies have been supporting both appraisal and development strategies of the fields. The translation of the field observation and detailed fracture characterization using static BHI (bore hole image) and core data yields a series of geological concepts. These concepts capture end members of the spatial distribution of the major conductive features and provide a range of realizations for the geometrical extent of the fracture zones. Given the large uncertainty in the dynamic properties of the fracture; pressure transient analysis (PTA), complemented by core data, has proven to be key in narrowing the range of fracture equivalent permeabilities and porosities that are carried forward in the history matching step. This paper focuses on illustrating the integration of different aspects of Pressure Transient Analysis data to pre-condition the discrete fracture network (DFN) model realizations. Comparison between KH from well test and log data allows to discriminate fractured from matrix wells. Dedicated sector models around fractured wells are built to assess the impact of the matrix, faults and fracture properties on the transient pressure response. Numerical simulations are conducted directly on the static model with the fractures explicitly captured as discrete surface features. For each DFN configuration, a sensitivity analysis of the fracture properties is performed and the characteristics of the resulting pressure derivatives are then compared against the well test data to select the plausible realizations that honor both geological and flow data. In this paper, a series of examples demonstrating the application of the methodology are presented for different areas of the field.
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