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Donor insulin therapy in intensive care predicts early outcomes after pancreas transplantation
No full textIntroduction: Approximately 50% of organ donors develop hyperglycaemia on intensive care, which is managed with insulin therapy. We aimed to determine the relationships between donor insulin use (DIU) and graft failure in pancreas transplantation. Methods: United Kingdom (UK) Transplant Registry organ donor data were linked with national data from the UK solid pancreas transplant programme. All pancreas transplants performed between 2004 and 2016 with complete follow-up data were included. Logistic regression models determined associations between DIU and causes of graft failure within 3 months. Area under Receiver Operating Characteristic (ROC) curves and Net Reclassification Improvement (NRI) assessed the added value of DIU as a predictor of graft failure. Results: In 2168 pancreas transplant recipients (mean [SD] age: 42 [8] years; body mass index [BMI]: 23.5 [3.4] kg/m2), 1112 (51%) donors were insulin-treated. DIU was associated with a higher risk of graft loss from isolated islet failure: Odds Ratio, 95% CI 1.79 (1.05-3.07), p=0.03 and this relationship was duration/dose-dependent. DIU was also associated with a higher risk of graft loss from anastomotic leak 2.72 [1.07-6.92], p=0.04 and a lower risk of graft loss from thrombosis (0.62 [0.39-0.96], p=0.03), although duration/dose-dependent relationships was only identified in pancreas transplant alone/pancreas after kidney transplant (PTA/PAK) recipients with grafts failing due to thrombosis (0.86 [0.74-0.99], p=0.03). The relationship between donor insulin characteristics and isolated islet failure remained significant after adjusting for potential confounders: DIU 1.75 1.02-2.99), p=0.04; duration 1.08 (1.01-1.16), p=0.03. In multivariable analyses, donor insulin characteristics remained significant predictors of lower risk of graft thrombosis in PTA/PAK recipients: DIU (0.34 [0.13-0.90], p=0.03); insulin duration/dose 0.02 (0.001-0.85), p=0.04. When data on insulin was added to models predicting isolated islet failure a significant improvement in discrimination and risk reclassification was observed in all models: no DIU aROC 0.56; DIU aROC 0.57, p=0.86; NRI 0.28, p<0.00001; insulin duration aROC 0.60, p=0.47; NRI 0.35, p<0.00001. Conclusions: DIU predicts graft survival in pancreas transplant recipients. This assessment could help improve donor selection and thereby improve patient and graft outcomes
The Relation between Rheumatoid Arthritis and Diabetes Mellitus: a Systematic Review and Meta-Analysis
No full textObjectives This systematic review and meta-analysis was conducted to investigate the relationship between rheumatoid arthritis (RA) and the incidence of diabetes mellitus (DM). Methods A comprehensive search was conducted up to March 10, 2020 in Medline (via Ovid), Embase (via Ovid) and Web of science core collection to identify cohort studies comparing the risk of DM incidence in people with RA with the general population. The I2 statistic was used to test heterogeneity. Pooled relative risks (RR) were calculated using random-effects models. Publication bias was assessed using funnel plot, Egger’s test and Begg’s test. Results The initial search provided 3,669 articles. Of those, five journal articles and two conference abstracts comprising 1,629,854 participants were included in this study. The funnel plot showed potential publication bias, proven by Egger’s test (-3.15, P<0.01), but not Begg’s test (-0.05, P=1.00). Heterogeneity was observed in I2 test (I2=96%, P<0.01). We found that RA was associated with a higher risk of DM incidence (pooled RR 1.23; 95% CI 1.07-1.40). Exploration of potential sources of heterogeneity found significant heterogeneity among different countries or regions (P=0.002), but heterogeneity was not significant for differing study designs (P=0.30). Sensitivity analyses confirmed that the association between rheumatoid arthritis and diabetes mellitus incidence was robust. Conclusion RA is associated with an increased risk of diabetes incidence. This finding supports the notion that inflammatory pathways are involved in the pathogenesis of diabetes. More intensive intervention to target diabetes risk factors should be considered in people with RA
Patient social functioning in acute mental health inpatient wards: the role of emotional regulation, attachment styles and nurse-patient relationships
No full textBackground: Improvement in social functioning is an important aspect of recovery from severe mental health problems. Nurses on acute mental health wards play an important role in facilitating this recovery. It is therefore important to explore potential predictors of social functioning and the quality of nurse-patient relationships. Objectives: To explore associations between patient social functioning, nurse-patient therapeutic alliance, emotional regulation, attachment style and nurse distress in acute mental health settings. Design: Questionnaire-based, cross-sectional study with correlational and regression analyses. Settings: Acute mental health inpatient wards across four NHS trusts in the North-West of England. Participants: Fifty nurse-patient dyads. Methods: Patients and nurses completed questionnaires regarding demographic information, emotional regulation, attachment style and alliance. Nurses also rated patient social functioning and their own distress.Results: Patient anxious attachment style was associated with difficulties in regulating emotions. Patient emotion regulation, patient insecure attachment and the patient-rated alliance predicted nurse-rated patient social functioning. Nurse emotion regulation, nurse insecure attachment style and nurse-rated alliance did not significantly predict nurse-rated patient social functioning and correlations were non-significant. Nurse distress was associated with nurse emotion regulation, nurse anxious attachment and nurse-rated alliance. These factors significantly predicted nurse distress. Conclusions: Patient social functioning is predicted by emotion regulation, attachment and alliance. Similarly, nurse distress is predicted by nurse emotion regulation, attachment style and alliance. Interventions targeting emotion regulation or attachment informed wards would be beneficial. <br/
Fostering Energy Transition in Smart Cities: DLTs for Peer-to-Peer Electricity Trading
No full textThis paper explores the applications of Distributed Ledger Technologies (DLTs) in Peer-to-Peer (P2P) electricity trading. It highlights the challenges and trade-offs of applying three different DLTs: Blockchain, Directed Acyclic Graph (DAG), and Holochain. First, the study introduces the energy transition concept in the smart city context. Second, P2P electricity trading and its supporting trading mechanisms are introduced. Third, DLTs are defined and three different types of DLTs are introduced. Forth, possibilities, challenges, and consequences of applying DLTs in electricity trading are explained. Last, applying DLTs for P2P electricity trading from different aspects are discussed. This paper provides a benchmark for applying DLTs to foster energy transition in smart cities. It highlights how this type of technology can serve smart circular economy
Response to letter regarding 'Systemic therapies in advanced hepatocellular carcinoma: How do older patients fare?'
No full textRecent advances in phosphoric acid–based membranes for high–temperature proton exchange membrane fuel cells
No full textHigh‐temperature proton exchange membrane fuel cells (HT‐PEMFCs) are pursued worldwide as efficient energy conversion devices. Great efforts have been made in the area of designing and developing phosphoric acid (PA)–based proton exchange membrane (PEM) of HT‐PEMFCs. This review focuses on recent advances in the limitations of acid–based PEM (acid leaching, oxidative degradation, and mechanical degradation) and the approaches mitigating the membrane degradation. Preparing multilayer or polymers with continuous network, adding hygroscopic inorganic materials, and introducing PA doping sites or covalent interactions with PA can effectively reduce acid leaching. Membrane oxidative degradation can be alleviated by synthesizing crosslinked or branched polymers, and introducing antioxidative groups or highly oxidative stable materials. Crosslinking to get a compact structure, blending with stable polymers and inorganic materials, preparing polymer with high molecular weight, and fabricating the polymer with PA doping sites away from backbones, are recommended to improve the membrane mechanical strength. Also, by comparing the running hours and decay rate, three current approaches, 1. crosslinking via thermally curing or polymeric crosslinker, 2. incorporating hygroscopic inorganic materials, 3. increasing membrane layers or introducing strong basic groups and electron–withdrawing groups, have been concluded to be promising approaches to improve the durability of HT–PEMFCs. The overall aim of this review is to explore the existing degradation challenges and opportunities to serve as a solid basis for the deployment in the fuel cell market
Number and Quality of Diagrams in Scholarly Publications is Associated with Number of Citations
No full textDiagrams are often used in scholarly communication. We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings (ACL 2017), and find inclusion of a system diagram to be correlated with higher numbers of citations after three years. Inclusion of more than three diagrams in this 8-page limit conference was found to correlate with a lower citation count. Focusing on neural network system diagrams, we find a correlation between highly cited papers and \good diagramming practice" quantified by level of compliance with a set of diagramming guidelines. This study suggests that diagrams may be a useful source of quality data for predicting citations, and that \graphicacy" is a key skill for scholars with insufficient support at present
Service Research Priorities: Designing Sustainable Service Ecosystems
No full textThis article utilizes input from service scholars, practitioners, reviews of published literature, and influential policy documents to identify service research priorities that push the boundaries of extant research. In a companion piece (Ostrom et al. 2021), we focused on four service research priorities related to managing and delivering service in turbulent times. Further, we identified a set of stakeholder-wants from the literature and included research questions that tie key stakeholder-wants to each of the three priorities in this article and the four priorities in the companion article. Here, we highlight the critical importance of scholarship and practice related to the design of sustainable service ecosystems and discuss three key service research priorities: large-scale and complex service ecosystems for transformative impact (SRP5), platform ecosystems and marketplaces (SRP6), and services for disadvantaged consumers and communities (SRP7). We call for an engaged service scholarship that considers the interrelationships among consumers, organizations, employees, platforms, and societal institutions and pursues transformative goals
Towards a fairer reimbursement system for burn patients using cost-sensitive classification
No full textThe adoption of the Prospective Payment System (PPS) in the UK National Health Service (NHS) has led to the creation of patient groups called Health Resource Groups (HRG). HRGs aim to identify groups of clinically similar patients that share similar resource usage for reimbursement purposes. These groups are predominantly identified based on expert advice, with homogeneity checked using the length of stay (LOS). However, for complex patients such as those encountered in burn care, LOS is not a perfect proxy of resource usage, leading to incomplete homogeneity checks. To improve homogeneity in resource usage and severity, we propose a data-driven model and the inclusion of patient-level costing. We investigate whether a data-driven approach that considers additional measures of resource usage can lead to a more comprehensive model. In particular, a cost-sensitive decision tree model is adopted to identify features of importance and rules that allow for a focused segmentation on resource usage (LOS and patient-level cost) and clinical similarity (severity of burn). The proposed approach identified groupswith increased homogeneity compared to the current HRG groups, allowing for a more equitable reimbursement of hospital care costs if adopted