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Atrial fibrillation (AF) is the most common sustained heart arrhythmia. However, as many cases are asymptomatic, a large proportion of patients remain undiagnosed until serious complications arise. Efficient, cost-effective detection of the undiagnosed may be supported by risk-prediction models relating patient factors to AF risk. However, there exists a need for an implementable risk model that is contemporaneous and informed by routinely collected patient data, reflecting the real-world pathology of AF. This study sought to develop and evaluate novel and conventional statistical and machine learning models for risk-predication of AF. This was a retrospective, cohort study of adults (aged ≥30 years) without a history of AF, listed on the Clinical Practice Research Datalink, from January 2006 to December 2016. Models evaluated included published risk models (Framingham, ARIC, CHARGE-AF), machine learning models, which evaluated baseline and time-updated information (neural network, LASSO, random forests, support vector machines), and Cox regression. Analysis of 2,994,837 individuals (3.2% AF) identified time-varying neural networks as the optimal model achieving an AUROC of 0.827 vs. 0.725, with number needed to screen of 9 vs. 13 patients at 75% sensitivity, when compared with the best existing model CHARGE-AF. The optimal model confirmed known baseline risk factors (age, previous cardiovascular disease, antihypertensive medication usage) and identified additional time-varying predictors (proximity of cardiovascular events, body mass index (both levels and changes), pulse pressure, and the frequency of blood pressure measurements). The optimal time-varying machine learning model exhibited greater predictive performance than existing AF risk models and reflected known and new patient risk factors for AF.

Functional magnetic resonance imaging of brain responses to biological motion in children with autism spectrum disorder (ASD), unaffected siblings (US) of children with ASD, and typically developing (TD) children has revealed three types of neural signatures: (i) state activity, related to the state of having ASD that characterizes the nature of disruption in brain circuitry; (ii) trait activity, reflecting shared areas of dysfunction in US and children with ASD, thereby providing a promising neuroendophenotype to facilitate efforts to bridge genomic complexity and disorder heterogeneity; and (iii) compensatory activity, unique to US, suggesting a neural system—level mechanism by which US might compensate for an increased genetic risk for developing ASD. The distinct brain responses to biological motion exhibited by TD children and US are striking given the identical behavioral profile of these two groups. These findings offer far-reaching implications for our understanding of the neural systems underlying autism.

Background Chronic kidney disease (CKD) is a progressive condition that leads to irreversible damage to the kidneys and is associated with an increased incidence of cardiovascular events and mortality. As novel interventions become available, estimates of economic and clinical outcomes are needed to guide payer reimbursement decisions. Objective The aim of the present study was to systematically review published economic models that simulated long-term outcomes of kidney disease to inform cost-effectiveness evaluations of CKD treatments. Methods The review was conducted across four databases (MEDLINE, Embase, the Cochrane library and EconLit) and health technology assessment agency websites. Relevant information on each model was extracted. Transition and mortality rates were also extracted to assess the choice of model parameterisation on disease progression by simulating patient’s time with end-stage renal disease (ESRD) and time to ESRD/death. The incorporation of cardiovascular disease in a population with CKD was qualitatively assessed across identified models. Results The search identified 101 models that met the criteria for inclusion. Models were classified into CKD models ( n  = 13), diabetes models with nephropathy ( n  = 48), ESRD-only models ( n  = 33) and cardiovascular models with CKD components ( n  = 7). Typically, published models utilised frameworks based on either (estimated or measured) glomerular filtration rate (GFR) or albuminuria, in line with clinical guideline recommendations for the diagnosis and monitoring of CKD. Generally, two core structures were identified, either a microsimulation model involving albuminuria or a Markov model utilising CKD stages and a linear GFR decline (although further variations on these model structures were also identified). Analysis of parameter variability in CKD disease progression suggested that mean time to ESRD/death was relatively consistent across model types (CKD models 28.2 years; diabetes models with nephropathy 24.6 years). When evaluating time with ESRD, CKD models predicted extended ESRD survival over diabetes models with nephropathy (mean time with ESRD 8.0 vs. 3.8 years). Discussion This review provides an overview of how CKD is typically modelled. While common frameworks were identified, model structure varied, and no single model type was used for the modelling of patients with CKD. In addition, many of the current methods did not explicitly consider patient heterogeneity or underlying disease aetiology, except for diabetes. However, the variability of individual patients’ GFR and albuminuria trajectories perhaps provides rationale for a model structure designed around the prediction of individual patients’ GFR trajectories. Frameworks of future CKD models should be informed and justified based on clinical rationale and availability of data to ensure validity of model results. In addition, further clinical and observational research is warranted to provide a better understanding of prognostic factors and data sources to improve economic modelling accuracy in CKD.

NKG2D plays a major role in controlling immune responses through the regulation of natural killer (NK) cells, αβ and γδ T-cell function. This activating receptor recognizes eight distinct ligands (the MHC Class I polypeptide-related sequences (MIC) A andB, and UL16-binding proteins (ULBP)1-6) induced by cellular stress to promote recognition cells perturbed by malignant transformation or microbial infection. Studies into human cytomegalovirus (HCMV) have aided both the identification and characterization of NKG2D ligands (NKG2DLs). HCMV immediate early (IE) gene up regulates NKGDLs, and we now describe the differential activation of ULBP2 and MICA/B by IE1 and IE2 respectively. Despite activation by IE functions, HCMV effectively suppressed cell surface expression of NKGDLs through both the early and late phases of infection. The immune evasion functions UL16, UL142, and microRNA(miR)-UL112 are known to target NKG2DLs. While infection with a UL16 deletion mutant caused the expected increase in MICB and ULBP2 cell surface expression, deletion of UL142 did not have a similar impact on its target, MICA. We therefore performed a systematic screen of the viral genome to search of addition functions that targeted MICA. US18 and US20 were identified as novel NK cell evasion functions capable of acting independently to promote MICA degradation by lysosomal degradation. The most dramatic effect on MICA expression was achieved when US18 and US20 acted in concert. US18 and US20 are the first members of the US12 gene family to have been assigned a function. The US12 family has 10 members encoded sequentially through US12-US21; a genetic arrangement, which is suggestive of an 'accordion' expansion of an ancestral gene in response to a selective pressure. This expansion must have be an ancient event as the whole family is conserved across simian cytomegaloviruses from old world monkeys. The evolutionary benefit bestowed by the combinatorial effect of US18 and US20 on MICA may have contributed to sustaining the US12 gene family.

Patients with chronic kidney disease, especially those receiving hemodialysis (HD), are at risk of hyperkalemia (HK). This systematic review aimed to evaluate the prevalence of HK in patients with renal disease receiving HD and collate evidence on the effect of HK and differing HD patterns (i.e., long vs. short inter-dialytic intervals [LIDI and SIDI, respectively] in a thrice weekly schedule) on mortality. Comprehensive searches were conducted across six databases and selected conference proceedings by two independent reviewers up to September 2020. A hundred and two studies reporting frequency of HK, mortality, or cardiovascular (CV) outcomes in adult patients with acute, chronic or end-stage renal disease in receipt of HD were included. Narrative synthesis of results was undertaken with key findings presented in tables and figures. Median prevalence of HK in patients with renal disease receiving HD was 21.6% and increased in patients receiving concomitant medications - mainly renin-angiotensin-aldosterone system inhibitors and potassium-sparing diuretics. Associations between elevated potassium levels and increased risk of both all-cause and CV mortality in the HD population were consistent across the included studies. In addition, there was a rise in all-cause and CV mortality on the day following LIDI compared with the day after the two SIDIs in patients on HD. Evidence identified in this systematic review indicates a relationship between HK and LIDI with mortality in patients with renal disease receiving HD, emphasizing the need for effective monitoring and management to control potassium levels both in emergency and chronic HD settings.

Background and Objective Recent advances in hepatitis C virus (HCV) diagnostic testing methods allow for a one-stop simplified ‘test and cure’ approach. The cost effectiveness of incorporating this simplified approach into HCV screening in Iraq remains uncertain. This study aimed to compare the cost effectiveness of different HCV testing and diagnostic approaches, and screening strategies in Iraq from a health service perspective. Methods A cost-effectiveness analysis was undertaken using a hybrid model comprising a screening decision tree linked to a lifetime Markov model to estimate outcomes in HCV-infected people. Cost and utility estimates were sourced from the published literature and expert guidance provided by clinicians and policy makers in Iraq. Cost estimates were reported in 2019 USD or 2019 Iraqi Dinar and both costs and benefits were discounted at 3.5% annually. Results Strategies using a simplified approach were found to be cost saving in addition to improving patient outcomes when compared with a standard testing and diagnostic approach. When considering risk-based screening, a simplified approach was associated with a total cost saving of Iraqi Dinar 4375 billion (USD 3.7 billion) and per patient life-year and quality-adjusted life-year gains of 0.30 and 0.55, compared with a standard approach. Benefits and cost savings were driven by a 32.2% and 23.6% reduction in the incidence of cirrhosis and hepatocellular carcinoma, respectively. Estimated benefits and cost savings increased under total population screening. All screening and testing and diagnostic approaches were cost effective compared with a no screening scenario. Conclusions Improvements in the detection of HCV combined with a simplified one-stop testing and diagnostic approach represents an opportunity to reduce the burden of HCV in Iraq and may play a significant role in meeting World Health Organisation HCV elimination targets.

Background Conducting effective and translational research can be challenging and few trials undertake formal reflection exercises and disseminate learnings from them. Following completion of our multicentre randomised controlled trial, which was impacted by the COVID-19 pandemic, we sought to reflect on our experiences and share our thoughts on challenges, lessons learned, and recommendations for researchers undertaking or considering research in primary care. Methods Researchers involved in the Prediction of Undiagnosed atriaL fibrillation using a machinE learning AlgorIthm (PULsE-AI) trial, conducted in England from June 2019 to February 2021 were invited to participate in a qualitative reflection exercise. Members of the Trial Steering Committee (TSC) were invited to attend a semi-structured focus group session, Principal Investigators and their research teams at practices involved in the trial were invited to participate in a semi-structured interview. Following transcription, reflexive thematic analysis was undertaken based on pre-specified themes of recruitment, challenges, lessons learned, and recommendations that formed the structure of the focus group/interview sessions, whilst also allowing the exploration of new themes that emerged from the data. Results Eight of 14 members of the TSC, and one of six practices involved in the trial participated in the reflection exercise. Recruitment was highlighted as a major challenge encountered by trial researchers, even prior to disruption due to the COVID-19 pandemic. Researchers also commented on themes such as the need to consider incentivisation, and challenges associated with using technology in trials, especially in older age groups. Conclusions Undertaking a formal reflection exercise following the completion of the PULsE-AI trial enabled us to review experiences encountered whilst undertaking a prospective randomised trial in primary care. In sharing our learnings, we hope to support other clinicians undertaking research in primary care to ensure that future trials are of optimal value for furthering knowledge, streamlining pathways, and benefitting patients.

The prevalence of the hepatitis C virus (HCV) remains high amongst people who inject drugs (PWID) and accounts for the majority of newly acquired infections. This study aims to quantify the value of treatment amongst PWID with more efficacious treatments and at increased uptake rates, with respect to the avoidance of future infections and subsequent long-term complications of HCV. A dynamic HCV transmission and disease progression model was developed, incorporating acute and chronic infection and their long-term complications (decompensated cirrhosis, cancer, liver transplant and mortality), with the potential for HCV transmission to other PWID prior to successful treatment. The model was populated with prevalence and therapy data from a UK setting. Scenarios of current standard of care (SoC) treatment efficacy and uptake were compared to anticipated sustained virologic response (SVR) rates of 90-100% and increased uptake over varied horizons. SoC led to modest reductions in prevalence; >5% after 200 years. New treatments achieving 90% SVR could reduce prevalence below 5% within 60 years at current uptake rates or within 5 years if all patients are treated. Amongst 4,240 PWID, chronic HCV infections avoided as a result of increasing treatment uptake over the period 2015-2027 ranged from 20-580 and 34-912 with SoC and 90% SVR rates respectively. The reduction in downstream HCV infections due to increasing treatment uptake resulted in an approximate discounted gain of 300 life-years (from avoiding reduced life expectancy from HCV infection) and a gain of 1,700 QALYs (from avoiding the disutility of HCV infection and related complications), with a projected £5.4 million cost saving. While improved SVR profiles led to reductions in modelled prevalence, increased treatment uptake was the key driver of future infections avoided. Increased treatment among PWID with new more efficacious therapies could significantly change the future dynamics, cost and health burden of HCV-related disease.

Human cytomegalovirus (HCMV) US2, US3, US6 and US11 act in concert to prevent immune recognition of virally infected cells by CD8+ T-lymphocytes through downregulation of MHC class I molecules (MHC-I). Here we show that US2 function goes far beyond MHC-I degradation. A systematic proteomic study using Plasma Membrane Profiling revealed US2 was unique in downregulating additional cellular targets, including: five distinct integrin α-chains, CD112, the interleukin-12 receptor, PTPRJ and thrombomodulin. US2 recruited the cellular E3 ligase TRC8 to direct the proteasomal degradation of all its targets, reminiscent of its degradation of MHC-I. Whereas integrin α-chains were selectively degraded, their integrin β1 binding partner accumulated in the ER. Consequently integrin signaling, cell adhesion and migration were strongly suppressed. US2 was necessary and sufficient for degradation of the majority of its substrates, but remarkably, the HCMV NK cell evasion function UL141 requisitioned US2 to enhance downregulation of the NK cell ligand CD112. UL141 retained CD112 in the ER from where US2 promoted its TRC8-dependent retrotranslocation and degradation. These findings redefine US2 as a multifunctional degradation hub which, through recruitment of the cellular E3 ligase TRC8, modulates diverse immune pathways involved in antigen presentation, NK cell activation, migration and coagulation; and highlight US2's impact on HCMV pathogenesis.

Background Rheumatoid arthritis (RA) is an inflammatory autoimmune disease that causes chronic synovitis, resulting in progressive joint destruction and functional disability and affects approximately 400,000 people in the UK. This real-world study aimed to describe the characteristics, treatment patterns and clinical outcomes of patients who received abatacept in UK clinical practice. Methods This was a multi-centre, retrospective, observational study of patients with RA treated with abatacept at four UK centres between 01 January 2013 and 31 December 2017. Data were collected from medical records of each patient from the index date (date of first bDMARD initiation) until the most recent visit, death or end of study (31 December 2017). Results In total, 213 patients were included in the study. Patients received up to eight lines of therapy (LOTs). Treatment with abatacept, or any other bDMARD, was associated with reductions in DAS28-ESR and DAS28-CRP scores at 6 and 12 months. The distribution of EULAR responses (good/moderate/no response) tended to be more favourable for patients when receiving abatacept than when receiving other bDMARDs (22.8%/41.3%/35.9% versus 16.6%/41.4%/42.1% at 6 months, and 27.9%/36.1%/36.1% versus 21.2%/34.5%/44.2% at 12 months). Patients receiving abatacept at LOT1 ( n = 68) spent significantly longer on treatment compared with patients receiving other bDMARDs (53.4 vs. 17.4 months; p < 0.01); a similar trend was observed for LOT2. Among patients who discontinued after 6 months, a greater proportion experienced infection requiring antibiotics when receiving other bDMARDs compared to those receiving abatacept. Conclusions RA patients who received bDMARDs, including abatacept, experienced reduced disease activity. When receiving abatacept as first or second line of therapy, patients persisted with treatment significantly longer than those receiving other bDMARDs.