78 research outputs found

    What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask

    Get PDF
    Coincident with the tsunami of COVID-19-related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field

    International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries

    Get PDF
    Question What are international trends in hospitalizations for children and youth with SARS-CoV-2, and what are the epidemiological and clinical features of these patients? Findings This cohort study of 671 children and youth found discrete surges in hospitalizations with variable trends and timing across countries. Common complications included cardiac arrhythmias and viral pneumonia, and laboratory findings included elevations in markers of inflammation and abnormalities of coagulation; few children and youth were treated with medications directed specifically at SARS-CoV-2. Meaning These findings suggest large-scale informatics-based approaches used to incorporate electronic health record data across health care systems can provide an efficient source of information to monitor disease activity and define epidemiological and clinical features of pediatric patients hospitalized with SARS-CoV-2 infections

    A roadmap for the Human Developmental Cell Atlas

    Get PDF
    The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development

    Multiple interactions between the alpha2C- and beta1-adrenergic receptors influence heart failure survival

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Persistent stimulation of cardiac β<sub>1</sub>-adrenergic receptors by endogenous norepinephrine promotes heart failure progression. Polymorphisms of this gene are known to alter receptor function or expression, as are polymorphisms of the α<sub>2C</sub>-adrenergic receptor, which regulates norepinephrine release from cardiac presynaptic nerves. The purpose of this study was to investigate possible synergistic effects of polymorphisms of these two intronless genes (<it>ADRB1 </it>and <it>ADRA2C</it>, respectively) on the risk of death/transplant in heart failure patients.</p> <p>Methods</p> <p>Sixteen sequence variations in <it>ADRA2C </it>and 17 sequence variations in <it>ADRB1 </it>were genotyped in a longitudinal study of 655 white heart failure patients. Eleven sequence variations in each gene were polymorphic in the heart failure cohort. Cox proportional hazards modeling was used to identify polymorphisms and potential intra- or intergenic interactions that influenced risk of death or cardiac transplant. A leave-one-out cross-validation method was utilized for internal validation.</p> <p>Results</p> <p>Three polymorphisms in <it>ADRA2C </it>and five polymorphisms in <it>ADRB1 </it>were involved in eight cross-validated epistatic interactions identifying several two-locus genotype classes with significant relative risks ranging from 3.02 to 9.23. There was no evidence of intragenic epistasis. Combining high risk genotype classes across epistatic pairs to take into account linkage disequilibrium, the relative risk of death or transplant was 3.35 (1.82, 6.18) relative to all other genotype classes.</p> <p>Conclusion</p> <p>Multiple polymorphisms act synergistically between the <it>ADRA2C </it>and <it>ADRB1 </it>genes to increase risk of death or cardiac transplant in heart failure patients.</p

    Transcriptional recapitulation and subversion of embryonic colon development by mouse colon tumor models and human colon cancer

    Get PDF
    Colon tumors from four independent mouse models and 100 human colorectal cancers all exhibited striking recapitulation of embryonic colon gene expression from embryonic days 13.5-18.5

    Global gene expression profile progression in Gaucher disease mouse models

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Gaucher disease is caused by defective glucocerebrosidase activity and the consequent accumulation of glucosylceramide. The pathogenic pathways resulting from lipid laden macrophages (Gaucher cells) in visceral organs and their abnormal functions are obscure.</p> <p>Results</p> <p>To elucidate this pathogenic pathway, developmental global gene expression analyses were conducted in distinct <it>Gba1 </it>point-mutated mice (V394L/V394L and D409 V/null). About 0.9 to 3% of genes had altered expression patterns (≥ ± 1.8 fold change), representing several categories, but particularly macrophage activation and immune response genes. Time course analyses (12 to 28 wk) of INFγ-regulated pro-inflammatory (13) and IL-4-regulated anti-inflammatory (11) cytokine/mediator networks showed tissue differential profiles in the lung and liver of the <it>Gba1 </it>mutant mice, implying that the lipid-storage macrophages were not functionally inert. The time course alterations of the INFγ and IL-4 pathways were similar, but varied in degree in these tissues and with the <it>Gba1 </it>mutation.</p> <p>Conclusions</p> <p>Biochemical and pathological analyses demonstrated direct relationships between the degree of tissue glucosylceramides and the gene expression profile alterations. These analyses implicate IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory networks in differential disease progression with implications for understanding the Gaucher disease course and pathophysiology.</p

    International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

    Get PDF
    Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach

    Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study

    Get PDF
    Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1–365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53–3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03–4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55–5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14–1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37–0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17–1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20–1.58, p < 0.0001), male sex (HR 1.67, 95%CI 1.45–1.93, p < 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80–13.91, p < 0.0001), and hypertension (HR 1.22, 95%CI 1.10–1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32–1.67) and 365 days (RR 1.54, 95%CI 1.21–1.96) compared to COVID-19 patients with no AKI. Interpretation: COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery. Funding: Authors are supported by various funders, with full details stated in the acknowledgement section
    • …
    corecore