86 research outputs found

    Contrasting Spatial Distribution and Risk Factors for Past Infection with Scrub Typhus and Murine Typhus in Vientiane City, Lao PDR

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    Scrub typhus and murine typhus are neglected but important treatable causes of fever, morbidity and mortality in South-East Asia. Epidemiological data suggests that scrub typhus would be more common in rural areas and murine typhus in urban areas but there are very few comparative data from places where both diseases occur, as is the case in Vientiane, the capital of the Lao PDR. We therefore determined the frequency of IgG antibody seropositivity against scrub typhus and murine typhus, as indices of prior exposure to these pathogens, in a randomly selected population of 2,002 adults living in different neighbourhoods in Vientiane. The overall prevalence of IgG against these two pathogens was ∼20%. However, within the city, the spatial distribution of IgG against these two diseases was radically different - past exposure to murine typhus being more frequent in urbanized areas while past exposure to scrub typhus more frequent in outlying areas. This study underscores the importance of ecological characteristics in improving the understanding of both scrub typhus and murine typhus transmission and epidemiology

    De novo TBR1 variants cause a neurocognitive phenotype with ID and autistic traits:report of 25 new individuals and review of the literature

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    TBR1, a T-box transcription factor expressed in the cerebral cortex, regulates the expression of several candidate genes for autism spectrum disorders (ASD). Although TBR1 has been reported as a high-confidence risk gene for ASD and intellectual disability (ID) in functional and clinical reports since 2011, TBR1 has only recently been recorded as a human disease gene in the OMIM database. Currently, the neurodevelopmental disorders and structural brain anomalies associated with TBR1 variants are not well characterized. Through international data sharing, we collected data from 25 unreported individuals and compared them with data from the literature. We evaluated structural brain anomalies in seven individuals by analysis of MRI images, and compared these with anomalies observed in TBR1 mutant mice. The phenotype included ID in all individuals, associated to autistic traits in 76% of them. No recognizable facial phenotype could be identified. MRI analysis revealed a reduction of the anterior commissure and suggested new features including dysplastic hippocampus and subtle neocortical dysgenesis. This report supports the role of TBR1 in ID associated with autistic traits and suggests new structural brain malformations in humans. We hope this work will help geneticists to interpret TBR1 variants and diagnose ASD probands

    Publisher Correction: Science diplomacy for plant health

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    Correction to: Nature Plants https://doi.org/10.1038/s41477-020-0744-x, published online 11 August 2020.1 Pág.An amendment to this paper has been published and can be accessed via a link at the top of the paper.In the version of this Comment originally published, in the penultimate paragraph of the section “Steps towards global phytosanitary research coordination” the second sentence incorrectly defined IPPC as ‘Intergovernmental Panel on Climate Change’, though it was cor rectly defined earlier as ‘International Plant Protection Convention’; the sentence has now been corrected to read “Ideally, they should benefit from the reputation of a United Nations mandate convention, such as the IPPC…”Peer reviewe

    Quality indicators for patients with traumatic brain injury in European intensive care units

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    Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

    Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

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    Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

    Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

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    INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

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    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

    Effects of eight neuropsychiatric copy number variants on human brain structure

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    peer reviewedMany copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions. © 2021, The Author(s)
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