Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

BACKGROUND: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. OBJECTIVE: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). METHOD: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. RESULTS: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. CONCLUSION: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities

Lag times in the publication of network meta-analyses: A survey

Objective We assessed the extent of lag times in the publication and indexing of network meta-analyses (NMAs). Study design This was a survey of published NMAs on drug interventions. Setting NMAs indexed in PubMed (searches updated in May 2020). Primary and secondary outcome measures Lag times were measured as the time between the last systematic search and the article submission, acceptance, online publication, indexing and Medical Subject Headings (MeSH) allocation dates. Time-to-event analyses were performed considering independent variables (geographical origin, Journal Impact Factor, Scopus CiteScore, open access status) (SPSS V.24, R/RStudio). Results We included 1245 NMAs. The median time from last search to article submission was 6.8 months (204 days (IQR 95-381)), and to publication was 11.6 months. Only 5% of authors updated their search after first submission. There is a very slightly decreasing historical trend of acceptance (rho=-0.087; p=0.010), online publication (rho=-0.080; p=0.008) and indexing (rho=-0.080; p=0.007) lag times. Journal Impact Factor influenced the MeSH allocation process, but not the other lag times. The comparison between open access versus subscription journals confirmed meaningless differences in acceptance, online publication and indexing lag times. Conclusion Efforts by authors to update their search before submission are needed to reduce evidence production time. Peer reviewers and editors should ensure authors' compliance with NMA standards. The accuracy of these findings depends on the accuracy of the metadata used; as we evaluated only NMA on drug interventions, results may not be generalisable to all types of studies

Efficacy and safety of pharmacological interventions for managing sickle cell disease in children and adolescents: protocol for a systematic review with network meta-analysis

IntroductionSickle cell disease (SCD), an inherited haemoglobinopathy, has important impact on morbidity and mortality, especially in paediatrics. Previous systematic reviews are limited to adult patients or focused only on few therapies. We aim to synthesise the evidence on efficacy and safety of pharmacological interventions for managing SCD in children and adolescents.Methods and analysisThis systematic review protocol is available at Open Science Framework (doi:10.17605/OSF.IO/CWAE9). We will follow international recommendations on conduction and report of systematic reviews and meta-analyses. Searches will be conducted in PubMed, Scopus and Web of Science (no language nor time restrictions) (first pilot searches performed in May 2022). We will include randomised controlled trials comparing the effects of disease-modifying agents in patients with SCD under 18 years old. Outcomes of interest will include: vaso-occlusive crisis, haemoglobin levels, chest syndrome, stroke, overall survival and adverse events. We will provide a narrative synthesis of the findings, and whenever possible, results will be pooled by means of pairwise or Bayesian network meta-analyses with surface under the cumulative ranking curve analyses. Different statistical methods and models will be tested. Dichotomous outcomes will be reported as OR, risk ratio or HR, while continuous data will be reported as standard mean differences, both with 95% CI/credibility interval. The methodological quality of the trials will be evaluated using the Risk of Bias 2.0 tool, and the certainty of the evidence will be assessed with the Grading of Recommendations Assessment, Development and Evaluation approach.Ethics and disseminationThis study refers to a systematic review, so no ethics approval is necessary. We intent to publish our findings in international, peer-reviewed journal. Data will also be presented to peers in scientific events. Additionally, the results obtained in this study may contribute towards the update of therapeutic guidelines and for the development of health policies for SCD.PROSPERO registration numberCRD42022328471.</jats:sec

Anaphylaxis in an emergency department: a retrospective 10-year study in a tertiary hospital

Background. Anaphylaxis is a potentially fatal medical emergency. The frequency of hospital admissions for anaphylaxis seems to be increasing in the recent decades. Objective. Characterize the patients admitted for anaphylaxis to the adult emergency department (ED) of a tertiary care hospital over a 10-year period, discriminating aetiologies, clinical features and therapy administered. Methods. Retrospective, descriptive and inferential study, evaluating age, sex, Manchester triage system, suspected allergen, site of allergen exposure, comorbidities, cofactors, clinical findings and symptoms, treatment and management. Patients admitted between January 2007 and December 2016 were included. Results. Forty-three patients were enrolled: 23 males, mean age 54.3 ± 16.2 years, n = 22 had history of allergic disease. Two patients were triaged as non-urgent. The most frequently suspected causes of anaphylaxis were: drugs (33%, n = 14), Hymenoptera venoms (23%, n = 10), foods (21%, n = 9) and iodinated contrast products (12%, n = 5). Adrenaline was used in 88% of the episodes (n = 38), 55% of which (n = 21) intramuscularly. Mortality was registered in one case. At discharge, adrenaline auto-injector was prescribed in 7% (n = 3) of the patients, and Allergy and Clinical Immunology consultation (ACIC) was requested in 65% of the episodes (n = 28). Statistically significant associations (p minor 0.05) were established: a, anaphylaxis to drugs associated with a low intramuscular adrenaline use and with frequent oxygen therapy; b, anaphylaxis to food associated with intramuscular adrenaline administration; c, anaphylaxis to Hymenoptera venom associated with male sex; and d, anaphylaxis to iodinated contrasts associated with referral to ACIC and with shock. All obese patients developed shock. Conclusions. Anaphylaxis is a life-threatening condition that requires early recognition. Although most patients received adrenaline, administration was not always performed by the recommended route and only a few patients were prescribed adrenaline auto-injector.info:eu-repo/semantics/publishedVersio

Optimizing the use of systemic corticosteroids in severe asthma (ROSA II project): a national Delphi consensus study

Although the prevalence of severe asthma is not high (5–10% of patients), it is responsible for a large part of the overall disease burden and costs (50–60% of total costs), especially if the condition remains uncontrolled (which occurs in around 40% of cases). Currently, for patients without disease control or presenting frequent exacerbations despite optimal therapy, add-on treatments, traditionally long-acting anticholinergics, oral corticosteroids (OCS), or biologic agents (monoclonal antibodies) are recommended. Nonetheless, the long-term use of oral/systemic corticosteroids (CS) is significantly associated with adverse effects, acute and chronic complications that may decrease health-related quality of life and worsen prognosis, thus requiring additional monitoring and management. Conversely, target therapies (i.e., omalizumab, mepolizumab, reslizumab, benralizumab, and more recently, dupilumab) have been developed grounded on the different phenotypes and endotypes of severe asthma, and are gradually reducing the reliance on OCS (i.e., greater specificity for achieving disease control by reducing the risk of exacerbations and requirements for rescue medication and OCS, with limited adverse events).This work was supported by AstraZeneca.info:eu-repo/semantics/publishedVersio

ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology

We predicted fluid intelligence from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence

Sparse PLS hyper-parameters optimisation for investigating brain-behaviour relationships

Unsupervised learning approaches, such as Partial Least Squares, can be used to investigate relationships between multiple sources of data, such as neuroimaging and behavioural data. In cases of high-dimensional datasets with limited number of examples (e.g. neuroimaging data) there is a need for regularisation to enable the solution of the ill-posed problem and prevent overfitting. Different approaches have been proposed to optimise the regularisation parameters in unsupervised models, however, so far, there has been no comparison between the different approaches using the same data. In this work, two optimisation frameworks (i.e. a permutation and a train/test framework) were compared using sparse PLS to investigate associations between brain connectivity and behaviour data. Both frameworks were able to identify at least one brain-behaviour associative effect. A second brain-behaviour effect was only found using the train/test framework. More importantly, the results show that the multivariate associative effects found with the train/test framework generalise better to new data, suggesting that results based on the permutation framework should be carefully interpreted

Evaluation of allelic forms of the erythrocyte binding antigen 175 (EBA-175) in Plasmodium falciparum field isolates from Brazilian endemic area

<p>Abstract</p> <p>Background</p> <p>The <it>Plasmodium falciparum </it>Erythrocyte Binding Antigen-175 (EBA-175) is an antigen considered to be one of the leading malaria vaccine candidates. EBA-175 mediates sialic acid-dependent binding to glycophorin A on the erythrocytes playing a crucial role during invasion of the <it>P. falciparum </it>in the host cell. Dimorphic allele segments, termed C-fragment and F-fragment, have been found in high endemicity malaria areas and associations between the dimorphism and severe malaria have been described. In this study, the genetic dimorphism of EBA-175 was evaluated in <it>P. falciparum </it>field isolates from Brazilian malaria endemic area.</p> <p>Methods</p> <p>The study was carried out in rural villages situated near Porto Velho, Rondonia State in the Brazilian Amazon in three time points between 1993 and 2008. The allelic dimorphism of the EBA-175 was analysed by Nested PCR.</p> <p>Results</p> <p>The classical allelic dimorphism of the EBA-175 was identified in the studied area. Overall, C-fragment was amplified in a higher frequency than F-fragment. The same was observed in the three time points where C-fragment was observed in a higher frequency than F-fragment. Single infections (one fragment amplified) were more frequent than mixed infection (two fragments amplified).</p> <p>Conclusions</p> <p>These findings confirm the dimorphism of EBA175, since only the two types of fragments were amplified, C-fragment and F-fragment. Also, the results show the remarkable predominance of CAMP allele in the studied area. The comparative analysis in three time points indicates that the allelic dimorphism of the EBA-175 is stable over time.</p