Systematic review with meta-analysis: the accuracy of serological tests to support the diagnosis of coeliac disease

BACKGROUND: There is growing support for a biopsy avoidant approach to diagnose coeliac disease in both children and adults, using a serological diagnosis instead. AIMS: To assess the diagnostic accuracy of serological tests for coeliac disease in adults and children. METHODS: Seven electronic databases were searched between January 1990 and August 2020. Eligible diagnostic studies evaluated the accuracy of serological tests for coeliac disease against duodenal biopsy. Risk of bias assessment was performed using QUADAS-2. Bivariate random-effects meta-analyses were used to estimate serology sensitivity and specificity at the most commonly reported thresholds. RESULTS: 113 studies (n = 28,338) were included, all in secondary care populations. A subset of studies were included in meta-analyses due to variations in diagnostic thresholds. Summary sensitivity and specificity of immunoglobulin A (IgA) anti-tissue transglutaminase were 90.7% (95% confidence interval: 87.3%, 93.2%) and 87.4% (84.4%, 90.0%) in adults (5 studies) and 97.7% (91.0%, 99.4%) and 70.2% (39.3%, 89.6%) in children (6 studies); and of IgA endomysial antibodies were 88.0% (75.2%, 94.7%) and 99.6% (92.3%, 100%) in adults (5 studies) and 94.5% (88.9%, 97.3%) and 93.8% (85.2%, 97.5%) in children (5 studies). CONCLUSIONS: Anti-tissue transglutaminase sensitivity appears to be sufficient to rule out coeliac disease in children. The high specificity of endomysial antibody in adults supports its use to rule in coeliac disease. This evidence underpins the current development of clinical guidelines for a serological diagnosis of coeliac disease. Studies in primary care are needed to evaluate serological testing strategies in this setting

The accuracy of diagnostic indicators for coeliac disease: A systematic review and meta-analysis

Background: The prevalence of coeliac disease (CD) is around 1%, but diagnosis is challenged by varied presentation and non-specific symptoms and signs. This study aimed to identify diagnostic indicators that may help identify patients at a higher risk of CD in whom further testing is warranted. // Methods: International guidance for systematic review methods were followed and the review was registered at PROSPERO (CRD42020170766). Six databases were searched until April 2021. Studies investigating diagnostic indicators, such as symptoms or risk conditions, in people with and without CD were eligible for inclusion. Risk of bias was assessed using the QUADAS-2 tool. Summary sensitivity, specificity, and positive predictive values were estimated for each diagnostic indicator by fitting bivariate random effects meta-analyses. // Findings: 191 studies reporting on 26 diagnostic indicators were included in the meta-analyses. We found large variation in diagnostic accuracy estimates between studies and most studies were at high risk of bias. We found strong evidence that people with dermatitis herpetiformis, migraine, family history of CD, HLA DQ2/8 risk genotype, anaemia, type 1 diabetes, osteoporosis, or chronic liver disease are more likely than the general population to have CD. Symptoms, psoriasis, epilepsy, inflammatory bowel disease, systemic lupus erythematosus, fractures, type 2 diabetes, and multiple sclerosis showed poor diagnostic ability. A sensitivity analysis revealed a 3-fold higher risk of CD in first-degree relatives of CD patients. // Conclusions: Targeted testing of individuals with dermatitis herpetiformis, migraine, family history of CD, HLA DQ2/8 risk genotype, anaemia, type 1 diabetes, osteoporosis, or chronic liver disease could improve case-finding for CD, therefore expediting appropriate treatment and reducing adverse consequences. Migraine and chronic liver disease are not yet included as a risk factor in all CD guidelines, but it may be appropriate for these to be added. Future research should establish the diagnostic value of combining indicators

SCOWLP classification: Structural comparison and analysis of protein binding regions

<p>Abstract</p> <p>Background</p> <p>Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design.</p> <p>Description</p> <p>Protein binding regions (PBRs) might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed.</p> <p>We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions.</p> <p>The hierarchical classification of PBRs is implemented into the SCOWLP database and extends the SCOP classification with three additional family sub-levels: Binding Region, Interface and Contacting Domains. SCOWLP contains 9,334 binding regions distributed within 2,561 families. In 65% of the cases we observe families containing more than one binding region. Besides, 22% of the regions are forming complex with more than one different protein family.</p> <p>Conclusion</p> <p>The current SCOWLP classification and its web application represent a framework for the study of protein interfaces and comparative analysis of protein family binding regions. This comparison can be performed at atomic level and allows the user to study interactome conservation and variability. The new SCOWLP classification may be of great utility for reconstruction of protein complexes, understanding protein networks and ligand design. SCOWLP will be updated with every SCOP release. The web application is available at <url>http://www.scowlp.org</url>.</p

Developing an Individual-level Geodemographic Classification

Geodemographics is a spatially explicit classification of socio-economic data, which can be used to describe and analyse individuals by where they live. Geodemographic information is used by the public sector for planning and resource allocation but it also has considerable use within commercial sector applications. Early geodemographic systems, such as the UK’s ACORN (A Classification of Residential Neighbourhoods), used only area-based census data, but more recent systems have added supplementary layers of information, e.g. credit details and survey data, to provide better discrimination between classes. Although much more data has now become available, geodemographic systems are still fundamentally built from area-based census information. This is partly because privacy laws require release of census data at an aggregate level but mostly because much of the research remains proprietary. Household level classifications do exist but they are often based on regressions between area and household data sets. This paper presents a different approach for creating a geodemographic classification at the individual level using only census data. A generic framework is presented, which classifies data from the UK Census Small Area Microdata and then allocates the resulting clusters to a synthetic population created via microsimulation. The framework is then applied to the creation of an individual-based system for the city of Leeds, demonstrated using data from the 2001 census, and is further validated using individual and household survey data from the British Household Panel Survey

Imbalanced decision hierarchy in addicts emerging from drug-hijacked dopamine spiraling circuit

Despite explicitly wanting to quit, long-term addicts find themselves powerless to resist drugs, despite knowing that drug-taking may be a harmful course of action. Such inconsistency between the explicit knowledge of negative consequences and the compulsive behavioral patterns represents a cognitive/behavioral conflict that is a central characteristic of addiction. Neurobiologically, differential cue-induced activity in distinct striatal subregions, as well as the dopamine connectivity spiraling from ventral striatal regions to the dorsal regions, play critical roles in compulsive drug seeking. However, the functional mechanism that integrates these neuropharmacological observations with the above-mentioned cognitive/behavioral conflict is unknown. Here we provide a formal computational explanation for the drug-induced cognitive inconsistency that is apparent in the addicts' “self-described mistake”. We show that addictive drugs gradually produce a motivational bias toward drug-seeking at low-level habitual decision processes, despite the low abstract cognitive valuation of this behavior. This pathology emerges within the hierarchical reinforcement learning framework when chronic exposure to the drug pharmacologically produces pathologicaly persistent phasic dopamine signals. Thereby the drug hijacks the dopaminergic spirals that cascade the reinforcement signals down the ventro-dorsal cortico-striatal hierarchy. Neurobiologically, our theory accounts for rapid development of drug cue-elicited dopamine efflux in the ventral striatum and a delayed response in the dorsal striatum. Our theory also shows how this response pattern depends critically on the dopamine spiraling circuitry. Behaviorally, our framework explains gradual insensitivity of drug-seeking to drug-associated punishments, the blocking phenomenon for drug outcomes, and the persistent preference for drugs over natural rewards by addicts. The model suggests testable predictions and beyond that, sets the stage for a view of addiction as a pathology of hierarchical decision-making processes. This view is complementary to the traditional interpretation of addiction as interaction between habitual and goal-directed decision systems

Small business owners' health and safety intentions: A cross-sectional survey

BACKGROUND: Little is known about the variables underlying small business owners' behavioural intentions toward workplace health and safety. This project explores the relationship between three mediating variables (Attitude Toward Safety, Subjective Norm and Perceived Behavioural Control) and owners' Intentions Toward Safety, following the Theory of Planned Behaviour. We also investigate the role of beliefs underlying each mediating variable. METHODS: Seven hundred businesses (5–50 employees) were randomly selected from 4084 eligible companies in a manufacturing business database (SIC codes 24 to 39). The 348 respondents are on average 51 yrs of age, 86% male, 96% white and have 2 to 4 years of post-secondary school. RESULTS: All three mediator variables are significantly correlated with Intentions Toward Safety; Attitude Toward Safety shows the strongest correlation, which is confirmed by path analysis. Owners with higher attitudes toward safety have a higher probability of believing that improving workplace health and safety will make employees' healthier and happier, show that they care, increase employee productivity, lower workers' compensation costs, increase product quality and lower costs. CONCLUSION: These results suggest that interventions aimed at increasing owners' health and safety intentions (and thus, behaviours) should focus on demonstrating positive employee health and product quality outcomes

Practices, patients and (im)perfect data - feasibility of a randomised controlled clinical drug trial in German general practices

<p>Abstract</p> <p>Background</p> <p>Randomised controlled clinical (drug) trials supply high quality evidence for therapeutic strategies in primary care. Until now, experience with drug trials in German general practice has been sparse. In 2007/2008, the authors conducted an investigator-initiated, non-commercial, double-blind, randomised controlled pilot trial (HWI-01) to assess the clinical equivalence of ibuprofen and ciprofloxacin in the treatment of uncomplicated urinary tract infection (UTI). Here, we report the feasibility of this trial in German general practices and the implementation of Good Clinical Practice (GCP) standards as defined by the International Conference on Harmonisation (ICH) in mainly inexperienced general practices.</p> <p>Methods</p> <p>This report is based on the experience of the HWI-01 study conducted in 29 German general practices. Feasibility was defined by 1) successful practice recruitment, 2) sufficient patient recruitment, 3) complete and accurate data collection and 4) appropriate protection of patient safety.</p> <p>Results</p> <p>The final practice recruitment rate was 18%. In these practices, 79 of 195 screened UTI patients were enrolled. Recruitment differed strongly between practices (range 0-12, mean 2.8 patients per practice) and was below the recruitment goal of approximately 100 patients. As anticipated, practice nurses became the key figures in the screening und recruitment of patients. Clinical trial demands, in particular for completing symptom questionnaires, documentation of source data and reporting of adverse events, did not agree well with GPs' documentation habits and required support from study nurses. In many cases, GPs and practice staff seemed to be overwhelmed by the amount of information and regulations. No sudden unexpected serious adverse reactions (SUSARs) were observed during the trial.</p> <p>Conclusions</p> <p>To enable drug trials in general practice, it is necessary to adapt the setup of clinical research infrastructure to the needs of GPs and their practice staff. Risk adaption of clinical trial regulations is necessary to facilitate non-commercial comparative effectiveness trials in primary health care.</p> <p>Trial Registration</p> <p>Trial registration number: <a href="http://www.controlled-trials.com/ISRCTN00470468">ISRCTN00470468</a></p

Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of Merit, Gap Statistics and Model Explorer

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