Repairing boundaries along pathways to tuberculosis case detection: a qualitative synthesis of intervention designs

Background Tuberculosis case-finding interventions often involve several activities to enhance patient pathways, and it is unclear which activity defines the type of case-finding intervention. When conducting studies to identify the most effective case-finding intervention it is important to have a clear understanding of these interventions for meaningful comparisons. This review aimed to construct a systems-based logic model of all pathways to tuberculosis case detection through a synthesis of intervention designs. Methods We identified an existing systematic review on the effectiveness of interventions to increase tuberculosis case detection and updated the search from December 2016 to October 2020. We included randomized controlled trials, as these designs encourage detailed description of interventions. Taking each study in turn, intervention descriptions were read in detail. The texts were analysed qualitatively by constantly comparing emerging codes to construct patient journeys, visualized as logical chains. Actions taken as part of interventions were positioned along patient journeys to theorize the sequence of outcomes. Patient journeys formed the basis of the model, which was refined through discussion. Results Based on intervention descriptions from 17 randomized controlled trials, our model distinguishes two care-seeking pathways and four screening pathways. An open invitation to people with tuberculosis symptoms creates care-seeking pathways. On care-seeking pathways, systematic screening can be conducted at general health services, but not at specific TB care services. People invited to tuberculosis services regardless of symptoms follow tuberculosis screening pathways and may be identified with presumptive tuberculosis even if they do not seek care for tuberculosis symptoms. Tuberculosis screening pathways include screening offered to all people accessing care at general health services, screening at a mobile clinic or health facility with open invitation to a whole population or tuberculosis contacts, screening personally offered to a whole population or tuberculosis contacts at home, work or school, and screening offered to people receiving care for human immunodeficiency virus or other clinical risk-group care. Conclusion This systems-based logic model of tuberculosis case-finding pathways may support standardized terminology, consistency, transparency and improved communication among researchers, policy-makers, health workers and community members when implementing and evaluating interventions to improve tuberculosis case detection.

Family involvement in advance care planning for people living with advanced cancer: A systematic mixed-methods review

Background: Advance care planning is important for people with advanced cancer. Family involvement in advance care planning may be instrumental to achieving goal-concordant care since they frequently become surrogate decision-makers. Aim: To examine components, contexts, effects and linkages with intended outcomes of involving family members in advance care planning. Design: A mixed-methods systematic review, in which quantitative and qualitative data were extracted and synthesised using thematic synthesis leading to a logic model. Prospectively registered on PROSPERO (CRD42020208143). Data sources: Primary quantitative and qualitative research regarding family-involved advance care planning for people with advanced cancer were identified using Medline, Embase, PsycINFO and CINAHL from inception to September 2020. Quality appraisal was performed with ‘QualSyst’. Results: Fourteen articles were included. The synthesis identified perceptions of individuals and family members concerning family involvement in advance care planning and presents components for family-integrated advance care planning intervention. The logic model includes (i) addressing family members’ concerns and emotions and (ii) facilitating communication between individuals and family members which are distinctive when healthcare professionals engage with individuals as well as family members. Conclusions: This review provides a comprehensive understanding of family involvement in advance care planning and could inform its assessment and implementation in clinical practice. The number of included articles was limited. Therefore future research must focus on family integration and exploration of stakeholders’ perceptions to identify additional components and linkages between them within family-integrated advance care planning.

Oil health index calculation and incipient fault diagnosis in power transformers using fuzzy logic

In this paper, a new fuzzy logic (FL) model is proposed for assessing the health status of power transformers. In addition, the detection of incipient faults is achieved where two or more faults exist simultaneously. The process is carried out by integrating a fuzzy logic model with the conventional International Electric Committee (IEC) ratio codes method. As transformer oil insulation deteriorates, excess percentages of dissolved gases such as hydrogen, methane, ethane, acetylene and ethylene are induced within the trasnformer. The status of oil health is generally assessed using these gas concentrations. Therefore, in the proposed model, 31 fuzzy rules are designed based on the severity levels of these gases in order to determine the health index (HI) of the oil. Similarly, any incipient faults along with their severity are also detected using the proposed fuzzy logic model with 22 expert rules. To validate the proposed fuzzy logic model, the data for dissolved gases in 50 working transformers operated by the Himachal Pradesh State Electricity Board (HPSEB), India, are collected. Over the years, calculations for the health index have been performed using conventional dissolved gas analysis (DGA) interpretation methods. The shortcomings of these methods, such as non-reliability and inaccuracy, are successfully overcome using the proposed model. The detection of incipient faults is normally performed using key gas, Rogers ratios, the Duval triangle, Dornenburg ratios, modified Rogers ratios and the IEC ratio codes methods. The shortcomings of these conventional ratio code methods in identifying incipient faults in some typical cases, ie multiple incipient fault cases, are overcome by the proposed fuzzy logic model.

Taguchi based fuzzy logic model for optimisation and prediction of surface roughness during AWJM of DRCUFP composites

From last two decades, plant fiber reinforced polymer/polyester composites have been effectively used in structural and automotive applications. Researchers and manufacturers are looking forward for an effective utilization of these composites. However, despite the outstanding properties in terms of load bearing capacity and environmental sustainability of plant fibers the uptake of these composites are limited due to its poor machinability characteristics. Hence in this paper, Taguchi based fuzzy logic model for the optimization and prediction of process output variable such as surface roughness during Abrasive Water Jet Machining (AWJM) of new class of plant fiber reinforced polyester composites i.e., Discontinuously Reinforced Caryota Urens Fiber Polyester (DRCUFP) composites has been explored. Initially machining experiments has been carried out using L27 orthogonal array obtained from Taguchi Design of Experiments (TDOE). Finally, Taguchi based fuzzy logic model has been developed for optimisation and prediction of surface roughness. From the extensive experimentation using TDOE it was observed that the optimum cutting conditions for obtaining minimum surface roughness value, water pressure (A): 300 bar, traverse speed (B): 50 mm, stand of distance: 1 mm, abrasive flow rate: 12 g/s, depth of cut (C): 5 mm and Abrasive Size:200 microns. Further from FLM, it is observed that minimum water pressure (A): 100 bar, traverse speed (B): 50 mm, stand of distance: 1 mm, abrasive flow rate: 8 g/s, depth of cut (C): 5 mm and abrasive size:100 microns gave higher surface roughness values (3.47 microns) than that at maximum water pressure (A): 300 bar, traverse speed (B): 150 mm, stand of distance: 4 mm, abrasive flow rate: 12 g/s, depth of cut (C): 15 mm and abrasive size:200 microns the surface roughness values (3.25 microns).