137 research outputs found

    Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders

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    In the absence of intervention, early-onset congenital disorders lead to pregnancy loss, early death, or disability. Currently, lack of epidemiological data from many settings limits the understanding of the burden of these conditions, thus impeding health planning, policy-making, and commensurate resource allocation. The Modell Global Database of Congenital Disorders (MGDb) seeks to meet this need by combining general biological principles with observational and demographic data, to generate estimates of the burden of congenital disorders. A range of interventions along the life course can modify adverse outcomes associated with congenital disorders. Hence, access to and quality of services available for the prevention and care of congenital disorders affects both their birth prevalence and the outcomes for affected individuals. Information on this is therefore important to enable burden estimates for settings with limited observational data, but is lacking from many settings. This paper, the third in this special issue on methods used in the MGDb for estimating the global burden of congenital disorders, describes key interventions that impact on outcomes of congenital disorders and methods used to estimate their coverage where empirical data are not available

    Expert consensus on neurodevelopmental outcomes in pregnancy pharmacovigilance studies

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    Background: Exposure in utero to certain medications can disrupt processes of fetal development, including brain development, leading to a continuum of neurodevelopmental difficulties. Recognizing the deficiency of neurodevelopmental investigations within pregnancy pharmacovigilance, an international Neurodevelopmental Expert Working Group was convened to achieve consensus regarding the core neurodevelopmental outcomes, optimization of methodological approaches and barriers to conducting pregnancy pharmacovigilance studies with neurodevelopmental outcomes. Methods: A modified Delphi study was undertaken based on stakeholder and expert input. Stakeholders (patient, pharmaceutical, academic and regulatory) were invited to define topics, pertaining to neurodevelopmental investigations in medication-exposed pregnancies. Experts were identified for their experience regarding neurodevelopmental outcomes following medicinal, substances of misuse or environmental exposures in utero. Two questionnaire rounds and a virtual discussion meeting were used to explore expert opinion on the topics identified by the stakeholders. Results: Twenty-five experts, from 13 countries and professionally diverse backgrounds took part in the development of 11 recommendations. The recommendations focus on the importance of neurodevelopment as a core feature of pregnancy pharmacovigilance, the timing of study initiation and a core set of distinct but interrelated neurodevelopmental skills or diagnoses which require investigation. Studies should start in infancy with an extended period of investigation into adolescence, with more frequent sampling during rapid periods of development. Additionally, recommendations are made regarding optimal approach to neurodevelopmental outcome measurement, comparator groups, exposure factors, a core set of confounding and mediating variables, attrition, reporting of results and the required improvements in funding for potential later emerging effects. Different study designs will be required depending on the specific neurodevelopmental outcome type under investigation and whether the medicine in question is newly approved or already in widespread use. Conclusion: An improved focus on neurodevelopmental outcomes is required within pregnancy pharmacovigilance. These expert recommendations should be met across a complementary set of studies which converge to form a comprehensive set of evidence regarding neurodevelopmental outcomes in pregnancy pharmacovigilance

    Epidemiological Surveillance of Birth Defects Compatible with Thalidomide Embryopathy in Brazil

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    The thalidomide tragedy of the 1960s resulted in thousands of children being born with severe limb reduction defects (LRD), among other malformations. In Brazil, there are still babies born with thalidomide embryopathy (TE) because of leprosy prevalence, availability of thalidomide, and deficiencies in the control of drug dispensation. Our objective was to implement a system of proactive surveillance to identify birth defects compatible with TE. Along one year, newborns with LRD were assessed in the Brazilian hospitals participating in the Latin-American Collaborative Study of Congenital Malformations (ECLAMC). A phenotype of LRD called thalidomide embryopathy phenotype (TEP) was established for surveillance. Children with TEP born between the years 2000–2008 were monitored, and during the 2007–2008 period we clinically investigated in greater detail all cases with TEP (proactive period). The period from 1982 to 1999 was defined as the baseline period for the cumulative sum statistics. The frequency of TEP during the surveillance period, at 3.10/10,000 births (CI 95%: 2.50–3.70), was significantly higher than that observed in the baseline period (1.92/10,000 births; CI 95%: 1.60–2.20), and not uniformly distributed across different Brazilian regions. During the proactive surveillance (2007–2008), two cases of suspected TE were identified, although the two mothers had denied the use of the drug during pregnancy. Our results suggest that TEP has probably increased in recent years, which coincides with the period of greater thalidomide availability. Our proactive surveillance identified two newborns with suspected TE, proving to be a sensitive tool to detect TE. The high frequency of leprosy and the large use of thalidomide reinforce the need for a continuous monitoring of TEP across Brazil

    Estimating the birth prevalence and pregnancy outcomes of congenital malformations worldwide

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    Congenital anomaly registries have two main surveillance aims: firstly to define baseline epidemiology of important congenital anomalies to facilitate programme, policy and resource planning, and secondly to identify clusters of cases and any other epidemiological changes that could give early warning of environmental or infectious hazards. However, setting up a sustainable registry and surveillance system is resource-intensive requiring national infrastructure for recording all cases and diagnostic facilities to identify those malformations that that are not externally visible. Consequently, not all countries have yet established robust surveillance systems. For these countries, methods are needed to generate estimates of prevalence of these disorders which can act as a starting point for assessing disease burden and service implications. Here, we describe how registry data from high-income settings can be used for generating reference rates that can be used as provisional estimates for countries with little or no observational data on non-syndromic congenital malformations

    Classification algorithm for congenital Zika Syndrome: characterizations, diagnosis and validation.

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    Zika virus was responsible for the microcephaly epidemic in Brazil which began in October 2015 and brought great challenges to the scientific community and health professionals in terms of diagnosis and classification. Due to the difficulties in correctly identifying Zika cases, it is necessary to develop an automatic procedure to classify the probability of a CZS case from the clinical data. This work presents a machine learning algorithm capable of achieving this from structured and unstructured available data. The proposed algorithm reached 83% accuracy with textual information in medical records and image reports and 76% accuracy in classifying data without textual information. Therefore, the proposed algorithm has the potential to classify CZS cases in order to clarify the real effects of this epidemic, as well as to contribute to health surveillance in monitoring possible future epidemics

    Disentangling signatures of selection before and after European colonization in latin Americans

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    Throughout human evolutionary history, large-scale migrations have led to intermixing (i.e., admixture) between previously separated human groups. Although classical and recent work have shown that studying admixture can yield novel historical insights, the extent to which this process contributed to adaptation remains underexplored. Here, we introduce a novel statistical model, specific to admixed populations, that identifies loci under selection while determining whether the selection likely occurred post-admixture or prior to admixture in one of the ancestral source populations. Through extensive simulations, we show that this method is able to detect selection, even in recently formed admixed populations, and to accurately differentiate between selection occurring in the ancestral or admixed population. We apply this method to genome-wide SNP data of ∼4,000 individuals in five admixed Latin American cohorts from Brazil, Chile, Colombia, Mexico, and Peru. Our approach replicates previous reports of selection in the human leukocyte antigen region that are consistent with selection post-admixture. We also report novel signals of selection in genomic regions spanning 47 genes, reinforcing many of these signals with an alternative, commonly used local-ancestry-inference approach. These signals include several genes involved in immunity, which may reflect responses to endemic pathogens of the Americas and to the challenge of infectious disease brought by European contact. In addition, some of the strongest signals inferred to be under selection in the Native American ancestral groups of modern Latin Americans overlap with genes implicated in energy metabolism phenotypes, plausibly reflecting adaptations to novel dietary sources available in the Americas

    Human antibodies targeting Zika virus NS1 provide protection against disease in a mouse model.

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    Zika virus is a mosquito-borne flavivirus closely related to dengue virus that can cause severe disease in humans, including microcephaly in newborns and Guillain-Barré syndrome in adults. Specific treatments and vaccines for Zika virus are not currently available. Here, we isolate and characterize four monoclonal antibodies (mAbs) from an infected patient that target the non-structural protein NS1. We show that while these antibodies are non-neutralizing, NS1-specific mAbs can engage FcγR without inducing antibody dependent enhancement (ADE) of infection in vitro. Moreover, we demonstrate that mAb AA12 has protective efficacy against lethal challenges of African and Asian lineage strains of Zika virus in Stat2-/- mice. Protection is Fc-dependent, as a mutated antibody unable to activate known Fc effector functions or complement is not protective in vivo. This study highlights the importance of the ZIKV NS1 protein as a potential vaccine antigen
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