Natural Language Processing in Electronic Health Records in Relation to Healthcare Decision-making: A Systematic Review

Background: Natural Language Processing (NLP) is widely used to extract clinical insights from Electronic Health Records (EHRs). However, the lack of annotated data, automated tools, and other challenges hinder the full utilisation of NLP for EHRs. Various Machine Learning (ML), Deep Learning (DL) and NLP techniques are studied and compared to understand the limitations and opportunities in this space comprehensively. Methodology: After screening 261 articles from 11 databases, we included 127 papers for full-text review covering seven categories of articles: 1) medical note classification, 2) clinical entity recognition, 3) text summarisation, 4) deep learning (DL) and transfer learning architecture, 5) information extraction, 6) Medical language translation and 7) other NLP applications. This study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Result and Discussion: EHR was the most commonly used data type among the selected articles, and the datasets were primarily unstructured. Various ML and DL methods were used, with prediction or classification being the most common application of ML or DL. The most common use cases were: the International Classification of Diseases, Ninth Revision (ICD-9) classification, clinical note analysis, and named entity recognition (NER) for clinical descriptions and research on psychiatric disorders. Conclusion: We find that the adopted ML models were not adequately assessed. In addition, the data imbalance problem is quite important, yet we must find techniques to address this underlining problem. Future studies should address key limitations in studies, primarily identifying Lupus Nephritis, Suicide Attempts, perinatal self-harmed and ICD-9 classification

Screening, Brief Intervention, and Referral to Treatment for Pain Management for Veterans Seeking Service-Connection Payments for Musculoskeletal Disorders: SBIRT-PM Study Protocol

BACKGROUND: Veterans with significant chronic pain from musculoskeletal disorders are at risk of substance misuse. Veterans whose condition is the result of military service may be eligible for a disability pension. Department of Veterans Affairs compensation examinations, which determine the degree of disability and whether it was connected to military service, represent an opportunity to engage Veterans in pain management and substance use treatments. A multisite randomized clinical trial is testing the effectiveness and cost-effectiveness of Screening, Brief Intervention, and Referral to Treatment for Pain Management (SBIRT-PM) for Veterans seeking compensation for musculoskeletal disorders. This telephone-based intervention is delivered through a hub-and-spoke configuration. DESIGN: This study is a two-arm, parallel-group, 36-week, multisite randomized controlled single-blind trial. It will randomize 1,100 Veterans experiencing pain and seeking service-connection for musculoskeletal disorders to either SBIRT-PM or usual care across eight New England VA medical centers. The study balances pragmatic with explanatory methodological features. Primary outcomes are pain severity and number of substances misused. Nonpharmacological pain management and substance use services utilization are tracked in the trial. SUMMARY: Early trial enrollment targets were met across sites. SBIRT-PM could help Veterans, at the time of their compensation claims, use multimodal pain treatments and reduce existing substance misuse. Strategies to address COVID-19 pandemic impacts on the SBIRT-PM protocol have been developed to maintain its pragmatic and exploratory integrity

Roles of neutrophils in the regulation of the extent of human inflammation through delivery of IL-1 and clearance of chemokines

This study examined the establishment of neutrophilic inflammation in humans. We tested the hypotheses that neutrophil recruitment was associated with local CXCL8 production and that neutrophils themselves might contribute to the regulation of the size of the inflammatory response. Humans were challenged i.d. with endotoxin. Biopsies of these sites were examined for cytokine production and leukocyte recruitment by qPCR and IHC. Additional in vitro models of inflammation examined the ability of neutrophils to produce and sequester cytokines relevant to neutrophilic inflammation. i.d. challenge with 15 ng of a TLR4-selective endotoxin caused a local inflammatory response, in which 1% of the total biopsy area stained positive for neutrophils at 6 h, correlating with 100-fold up-regulation in local CXCL8 mRNA generation. Neutrophils themselves were the major source of the early cytokine IL-1β. In vitro, neutrophils mediated CXCL8 but not IL-1β clearance (>90% clearance of ≤2 nM CXCL8 over 24 h). CXCL8 clearance was at least partially receptor-dependent and modified by inflammatory context, preserved in models of viral infection but reduced in models of bacterial infection. In conclusion, in a human inflammatory model, neutrophils are rapidly recruited and may regulate the size and outcome of the inflammatory response through the uptake and release of cytokines and chemokines in patterns dependent on the underlying inflammatory stimulus

Genetic Determinants of Serum Testosterone Concentrations in Men

Testosterone concentrations in men are associated with cardiovascular morbidity, osteoporosis, and mortality and are affected by age, smoking, and obesity. Because of serum testosterone's high heritability, we performed a meta-analysis of genome-wide association data in 8,938 men from seven cohorts and followed up the genome-wide significant findings in one in silico (n = 871) and two de novo replication cohorts (n = 4,620) to identify genetic loci significantly associated with serum testosterone concentration in men. All these loci were also associated with low serum testosterone concentration defined as <300 ng/dl. Two single-nucleotide polymorphisms at the sex hormone-binding globulin (SHBG) locus (17p13-p12) were identified as independently associated with serum testosterone concentration (rs12150660, p = 1.2×10−41 and rs6258, p = 2.3×10−22). Subjects with ≥3 risk alleles of these variants had 6.5-fold higher risk of having low serum testosterone than subjects with no risk allele. The rs5934505 polymorphism near FAM9B on the X chromosome was also associated with testosterone concentrations (p = 5.6×10−16). The rs6258 polymorphism in exon 4 of SHBG affected SHBG's affinity for binding testosterone and the measured free testosterone fraction (p<0.01). Genetic variants in the SHBG locus and on the X chromosome are associated with a substantial variation in testosterone concentrations and increased risk of low testosterone. rs6258 is the first reported SHBG polymorphism, which affects testosterone binding to SHBG and the free testosterone fraction and could therefore influence the calculation of free testosterone using law-of-mass-action equation

Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al

The RAB39B p.G192R mutation causes X-linked dominant Parkinson’s disease

Objective: To identify the causal gene in a multi-incident U.S. kindred with Parkinson’s disease (PD). Methods: We characterized a family with a classical PD phenotype in which 7 individuals (5 males and 2 females) were affected with a mean age at onset of 46.1 years (range, 29-57 years). We performed whole exome sequencing on 4 affected and 1 unaffected family members. Sanger-sequencing was then used to verify and genotype all candidate variants in the remainder of the pedigree. Cultured cells transfected with wild-type or mutant constructs were used to characterize proteins of interest. Results: We identified a missense mutation (c.574G > A; p.G192R) in the RAB39B gene that closely segregated with disease and exhibited X-linked dominant inheritance with reduced penetrance in females. The mutation occurred in a highly conserved amino acid residue and was not observed among 87,725 X chromosomes in the Exome Aggregation Consortium dataset. Sequencing of the RAB39B coding region in 587 familial PD cases yielded two additional mutations (c.428C > G [p.A143G] and c.624_626delGAG [p.R209del]) that were predicted to be deleterious in silico but occurred in families that were not sufficiently informative to assess segregation with disease. Experiments in PC12 and SK-N-BE(2)C cells demonstrated that p.G192R resulted in mislocalization of the mutant protein, possibly by altering the structure of the hypervariable C-terminal domain which mediates intracellular targeting. Conclusions: Our findings implicate RAB39B, an essential regulator of vesicular-trafficking, in clinically typical PD. Further characterization of normal and aberrant RAB39B function might elucidate important mechanisms underlying neurodegeneration in PD and related disorders. Electronic supplementary material The online version of this article (doi:10.1186/s13024-015-0045-4) contains supplementary material, which is available to authorized users

A proposed framework for the systematic review and integrated assessment (SYRINA) of endocrine disrupting chemicals

Background - The issue of endocrine disrupting chemicals (EDCs) is receiving wide attention from both the scientific and regulatory communities. Recent analyses of the EDC literature have been criticized for failing to use transparent and objective approaches to draw conclusions about the strength of evidence linking EDC exposures to adverse health or environmental outcomes. Systematic review methodologies are ideal for addressing this issue as they provide transparent and consistent approaches to study selection and evaluation. Objective methods are needed for integrating the multiple streams of evidence (epidemiology, wildlife, laboratory animal, in vitro, and in silico data) that are relevant in assessing EDCs. Methods - We have developed a framework for the systematic review and integrated assessment (SYRINA) of EDC studies. The framework was designed for use with the International Program on Chemical Safety (IPCS) and World Health Organization (WHO) definition of an EDC, which requires appraisal of evidence regarding 1) association between exposure and an adverse effect, 2) association between exposure and endocrine disrupting activity, and 3) a plausible link between the adverse effect and the endocrine disrupting activity. Results - Building from existing methodologies for evaluating and synthesizing evidence, the SYRINA framework includes seven steps: 1) Formulate the problem; 2) Develop the review protocol; 3) Identify relevant evidence; 4) Evaluate evidence from individual studies; 5) Summarize and evaluate each stream of evidence; 6) Integrate evidence across all streams; 7) Draw conclusions, make recommendations, and evaluate uncertainties. The proposed method is tailored to the IPCS/WHO definition of an EDC but offers flexibility for use in the context of other definitions of EDCs. Conclusions - When using the SYRINA framework, the overall objective is to provide the evidence base needed to support decision making, including any action to avoid/minimise potential adverse effects of exposures. This framework allows for the evaluation and synthesis of evidence from multiple evidence streams. Finally, a decision regarding regulatory action is not only dependent on the strength of evidence, but also the consequences of action/inaction, e.g. limited or weak evidence may be sufficient to justify action if consequences are serious or irreversible.The workshops that supported the writing of this manuscript were funded by the Swedish Foundation for Strategic Environmental Research “Mistra”. LNV was funded by Award Number K22ES025811 from the National Institute of Environmental Health Sciences of the National Institutes of Health. TJW was funded by The Clarence Heller Foundation (A123547), the Passport Foundation, the Forsythia Foundation, the National Institute of Environmental Health Sciences (grants ES018135 and ESO22841), and U.S. EPA STAR grants (RD83467801 and RD83543301). JT was funded by the Academy of Finland and Sigrid Juselius. UH was funded by the Danish EPA. KAK was funded by the Canada Research Chairs program grant number 950–230607

Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

The combined application of next-generation sequencing platforms has provided an economical approach to unlocking the potential of the turkey genome