Medicine and Health Sciences Commons^™

Re: Incidence Of Sars-Cov-2 Breakthrough Infections After Vaccination In Adults: A Population-Based Survey Through 1 March 2023, Stacia M Desantis, Ashraf Yaseen, Tianyao Hao, Luis León-Novelo, Yashar Talebi, Melissa A Valerio-Shewmaker, Cesar L Pinzon Gomez, Sarah E Messiah, Harold W Kohl, Steven H Kelder, Jessica A Ross, Lindsay N Padilla, Mark Silberman, Samantha Wylie, David Lakey, Jennifer A Shuford, Stephen J Pont, Eric Boerwinkle, Michael D Swartz

Journal Articles

No abstract provided.

Rare Variant Enrichment Analysis Supports, Angad Jolly, Haowei Du, Christelle Borel, Na Chen, Sen Zhao, Christopher M Grochowski, Ruizhi Duan, Jawid M Fatih, Moez Dawood, Sejal Salvi, Shalini N Jhangiani, Donna M Muzny, André Koch, Konstantinos Rouskas, Stavros Glentis, Efthymios Deligeoroglou, Flora Bacopoulou, Carol A Wise, Jennifer E Dietrich, Ignatia B Van Den Veyver, Antigone S Dimas, Sara Brucker, V Reid Sutton, Richard A Gibbs, Stylianos E Antonarakis, Nan Wu, Zeynep H Coban-Akdemir, Lan Zhu, Jennifer E Posey, James R Lupski

Journal Articles

Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is characterized by aplasia of the female reproductive tract; the syndrome can include renal anomalies, absence or dysgenesis, and skeletal anomalies. While functional models have elucidated several candidate genes, only

Biallelic Variants In Adamts15 Cause A Novel Form Of Distal Arthrogryposis, Felix Boschann, Ozgur Cogulu, Davut Pehlivan, Saranya Balachandran, Pedro Vallecillo-Garcia, Christopher M Grochowski, Nils R Hansmeier, Zeynep H Coban Akdemir, Cesar A Prada-Medina, Ayca Aykut, Björn Fischer-Zirnsak, Simon Badura, Burak Durmaz, Ferda Ozkinay, René Hägerling, Jennifer E Posey, Sigmar Stricker, Gabriele Gillessen-Kaesbach, Malte Spielmann, Denise Horn, Knut Brockmann, James R Lupski, Uwe Kornak, Julia Schmidt

Journal Articles

No abstract provided.

Sars-Cov-2 Serostatus And Covid-19 Illness Characteristics By Variant Time Period In Non-Hospitalized Children And Adolescents, Sarah E Messiah, Michael D Swartz, Rhiana A Abbas, Yashar Talebi, Harold W Kohl, Melissa Valerio-Shewmaker, Stacia M Desantis, Ashraf Yaseen, Steven H Kelder, Jessica A Ross, Lindsay N Padilla, Michael O Gonzalez, Leqing Wu, David Lakey, Jennifer A Shuford, Stephen J Pont, Eric Boerwinkle

Journal Articles

OBJECTIVE: To describe COVID-19 illness characteristics, risk factors, and SARS-CoV-2 serostatus by variant time period in a large community-based pediatric sample.

DESIGN: Data were collected prospectively over four timepoints between October 2020 and November 2022 from a population-based cohort ages 5 to 19 years old.

SETTING: State of Texas, USA.

PARTICIPANTS: Participants ages 5 to 19 years were recruited from large pediatric healthcare systems, Federally Qualified Healthcare Centers, urban and rural clinical practices, health insurance providers, and a social media campaign.

EXPOSURE: SARS-CoV-2 infection.

MAIN OUTCOME(S) AND MEASURE(S): SARS-CoV-2 antibody status was assessed by the Roche Elecsys

RESULTS: Over half …

Antibody Duration After Infection From Sars-Cov-2 In The Texas Coronavirus Antibody Response Survey, Michael D Swartz, Stacia M Desantis, Ashraf Yaseen, Frances A Brito, Melissa A Valerio-Shewmaker, Sarah E Messiah, Luis G Leon-Novelo, Harold W Kohl, Cesar L Pinzon-Gomez, Tianyao Hao, Shiming Zhang, Yashar Talebi, Joy Yoo, Jessica R Ross, Michael O Gonzalez, Leqing Wu, Steven H Kelder, Mark Silberman, Samantha Tuzo, Stephen J Pont, Jennifer A Shuford, David Lakey, Eric Boerwinkle

Journal Articles

Understanding the duration of antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that causes COVID-19 is important to controlling the current pandemic. Participants from the Texas Coronavirus Antibody Response Survey (Texas CARES) with at least 1 nucleocapsid protein antibody test were selected for a longitudinal analysis of antibody duration. A linear mixed model was fit to data from participants (n = 4553) with 1 to 3 antibody tests over 11 months (1 October 2020 to 16 September 2021), and models fit showed that expected antibody response after COVID-19 infection robustly increases for 100 days postinfection, and predicts …

Measuring And Controlling Medical Record Abstraction (Mra) Error Rates In An Observational Study., Maryam Y Garza, Tremaine Williams, Sahiti Myneni, Susan H Fenton, Songthip Ounpraseuth, Zhuopei Hu, Jeannette Lee, Jessica Snowden, Meredith N Zozus, Anita C Walden, Alan E Simon, Barbara Mcclaskey, Sarah G Sanders, Sandra S Beauman, Sara R Ford, Lacy Malloch, Amy Wilson, Lori A Devlin, Leslie W Young

Journal Articles

BACKGROUND: Studies have shown that data collection by medical record abstraction (MRA) is a significant source of error in clinical research studies relying on secondary use data. Yet, the quality of data collected using MRA is seldom assessed. We employed a novel, theory-based framework for data quality assurance and quality control of MRA. The objective of this work is to determine the potential impact of formalized MRA training and continuous quality control (QC) processes on data quality over time.

METHODS: We conducted a retrospective analysis of QC data collected during a cross-sectional medical record review of mother-infant dyads with Neonatal …

Host And Gut Microbial Tryptophan Metabolism And Type 2 Diabetes: An Integrative Analysis Of Host Genetics, Diet, Gut Microbiome And Circulating Metabolites In Cohort Studies, Qibin Qi, Jun Li, Bing Yu, Jee-Young Moon, Jin C Chai, Jordi Merino, Jie Hu, Miguel Ruiz-Canela, Casey Rebholz, Zheng Wang, Mykhaylo Usyk, Guo-Chong Chen, Bianca C Porneala, Wenshuang Wang, Ngoc Quynh Nguyen, Elena V Feofanova, Megan L Grove, Thomas J Wang, Robert E Gerszten, Josée Dupuis, Jordi Salas-Salvadó, Wei Bao, David L Perkins, Martha L Daviglus, Bharat Thyagarajan, Jianwen Cai, Tao Wang, Joann E Manson, Miguel A Martínez-González, Elizabeth Selvin, Kathryn M Rexrode, Clary B Clish, Frank B Hu, James B Meigs, Rob Knight, Robert D Burk, Eric Boerwinkle, Robert C Kaplan

Journal Articles

OBJECTIVE: Tryptophan can be catabolised to various metabolites through host kynurenine and microbial indole pathways. We aimed to examine relationships of host and microbial tryptophan metabolites with incident type 2 diabetes (T2D), host genetics, diet and gut microbiota.

METHOD: We analysed associations between circulating levels of 11 tryptophan metabolites and incident T2D in 9180 participants of diverse racial/ethnic backgrounds from five cohorts. We examined host genome-wide variants, dietary intake and gut microbiome associated with these metabolites.

RESULTS: Tryptophan, four kynurenine-pathway metabolites (kynurenine, kynurenate, xanthurenate and quinolinate) and indolelactate were positively associated with T2D risk, while indolepropionate was inversely associated with …

Centers For Mendelian Genomics: A Decade Of Facilitating Gene Discovery, Samantha M Baxter, Jennifer E Posey, Nicole J Lake, Nara Sobreira, Jessica X Chong, Steven Buyske, Elizabeth E Blue, Lisa H Chadwick, Zeynep H Coban-Akdemir, Kimberly F Doheny, Colleen P Davis, Monkol Lek, Christopher Wellington, Shalini N Jhangiani, Mark Gerstein, Richard A Gibbs, Richard P Lifton, Daniel G Macarthur, Tara C Matise, James R Lupski, David Valle, Michael J Bamshad, Ada Hamosh, Shrikant Mane, Deborah A Nickerson, Heidi L Rehm, Anne O'Donnell-Luria

Journal Articles

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration.

METHODS: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution.

RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships …

Elucidating The Clinical Spectrum And Molecular Basis Of Hyal2 Deficiency, James Fasham, Siying Lin, Promita Ghosh, Francesca Clementina Radio, Emily G Farrow, Isabelle Thiffault, Jennifer Kussman, Dihong Zhou, Rick Hemming, Kenneth Zahka, Barry A Chioza, Lettie E Rawlins, Olivia K Wenger, Adam C Gunning, Simone Pizzi, Roberta Onesimo, Giuseppe Zampino, Emily Barker, Natasha Osawa, Megan Christine Rodriguez, Teresa M Neuhann, Elaine H Zackai, Beth Keena, Jenina Capasso, Alex V Levin, Elizabeth Bhoj, Dong Li, Hakon Hakonarson, Ingrid M Wentzensen, Adam Jackson, Kate E Chandler, Zeynep H Coban-Akdemir, Jennifer E Posey, Siddharth Banka, James R Lupski, Sarah E Sheppard, Marco Tartaglia, Barbara Triggs-Raine, Andrew H Crosby, Emma L Baple

Journal Articles

PURPOSE: We previously defined biallelic HYAL2 variants causing a novel disorder in 2 families, involving orofacial clefting, facial dysmorphism, congenital heart disease, and ocular abnormalities, with Hyal2 knockout mice displaying similar phenotypes. In this study, we better define the phenotype and pathologic disease mechanism.

METHODS: Clinical and genomic investigations were undertaken alongside molecular studies, including immunoblotting and immunofluorescence analyses of variant/wild-type human HYAL2 expressed in mouse fibroblasts, and in silico modeling of putative pathogenic variants.

RESULTS: Ten newly identified individuals with this condition were investigated, and they were associated with 9 novel pathogenic variants. Clinical studies defined genotype-phenotype correlations and …

Genetic Errors Of Immunity Distinguish Pediatric Nonmalignant Lymphoproliferative Disorders, Lisa R Forbes, Olive S Eckstein, Nitya Gulati, Erin C Peckham-Gregory, Nmazuo W Ozuah, Joseph Lubega, Nader K El-Mallawany, Jennifer E Agrusa, M Cecilia Poli, Tiphanie P Vogel, Natalia S Chaimowitz, Nicholas L Rider, Emily M Mace, Jordan S Orange, Jason W Caldwell, Juan C Aldave-Becerra, Stephen Jolles, Francesco Saettini, Hey J Chong, Asbjorg Stray-Pedersen, Helen E Heslop, Kala Y Kamdar, R Helen Rouce, Donna M Muzny, Shalini N Jhangiani, Richard A Gibbs, Zeynep H Coban-Akdemir, James R Lupski, Kenneth L Mcclain, Carl E Allen, Ivan K Chinn

Journal Articles

BACKGROUND: Pediatric nonmalignant lymphoproliferative disorders (PLPDs) are clinically and genetically heterogeneous. Long-standing immune dysregulation and lymphoproliferation in children may be life-threatening, and a paucity of data exists to guide evaluation and treatment of children with PLPD.

OBJECTIVE: The primary objective of this study was to ascertain the spectrum of genomic immunologic defects in PLPD. Secondary objectives included characterization of clinical outcomes and associations between genetic diagnoses and those outcomes.

METHODS: PLPD was defined by persistent lymphadenopathy, lymph organ involvement, or lymphocytic infiltration for more than 3 months, with or without chronic or significant Epstein-Barr virus (EBV) infection. Fifty-one subjects from …

Ethical, Legal, And Social Issues In The Earth Biogenome Project, Jacob S. Sherkow, Katharine B. Barker, Irus Braverman, Robert Cook-Deegan, Richard Durbin, Carla L. Easter, Melissa M. Goldstein, Maui Hudson, W. John Kress, Harris A. Lewin, Debra J. H. Mathews, Catherine Mccarthy, Ann M. Mccartney, Manuela Da Silva, Andrew W. Torrance, Henry T. Greely

Journal Articles

The Earth BioGenome Project (EBP) is an audacious endeavor to obtain whole-genome sequences of representatives from all eukaryotic species on Earth. In addition to the project’s technical and organizational challenges, it also faces complicated ethical, legal, and social issues. This paper, from members of the EBP’s Ethical, Legal, and Social Issues (ELSI) Committee, catalogs these ELSI concerns arising from EBP. These include legal issues, such as sample collection and permitting; the applicability of international treaties, such as the Convention on Biological Diversity and the Nagoya Protocol; intellectual property; sample accessioning; and biosecurity and ethical issues, such as sampling from the …

Evaluation Of The Kitchen Microbiome And Food Safety Behaviors Of Predominantly Low-Income Families, Christina K Carstens, Joelle K Salazar, Shreela V Sharma, Wenyaw Chan, Charles Darkoh

Journal Articles

Bacterial pathogens in the domestic environment present a risk to residents, particularly among susceptible populations. However, the impact of consumer demographic characteristics and food handling methods on kitchen microbiomes is not fully understood. The domestic kitchen bacterial communities of ten predominantly low-income families in Houston, TX, were assessed in conjunction with a cross-sectional food safety survey to evaluate differences in household and surface-specific microbiomes and bacterial foodborne pathogen presence. Three kitchen surfaces within each household, including the sink drain, the refrigerator handle, and the counter, were environmentally sampled and metataxonomically evaluated via targeted 16S rRNA sequencing. Disposable dish sponges were …

Methodology To Estimate Natural- And Vaccine-Induced Antibodies To Sars-Cov-2 In A Large Geographic Region, Stacia M Desantis, Luis G León-Novelo, Michael D Swartz, Ashraf S Yaseen, Melissa A Valerio-Shewmaker, Yashar Talebi, Frances A Brito, Jessica A Ross, Harold W Kohl, Sarah E Messiah, Steve H Kelder, Leqing Wu, Shiming Zhang, Kimberly A Aguillard, Michael O Gonzalez, Onyinye S Omega-Njemnob, David Lakey, Jennifer A Shuford, Stephen Pont, Eric Boerwinkle

Journal Articles

Accurate estimates of natural and/or vaccine-induced antibodies to SARS-CoV-2 are difficult to obtain. Although model-based estimates of seroprevalence have been proposed, they require inputting unknown parameters including viral reproduction number, longevity of immune response, and other dynamic factors. In contrast to a model-based approach, the current study presents a data-driven detailed statistical procedure for estimating total seroprevalence (defined as antibodies from natural infection or from full vaccination) in a region using prospectively collected serological data and state-level vaccination data. Specifically, we conducted a longitudinal statewide serological survey with 88,605 participants 5 years or older with 3 prospective blood draws beginning …

Comprehensive Characterization Of Covid-19 Patients With Repeatedly Positive Sars-Cov-2 Tests Using A Large U.S. Electronic Health Record Database., Xiao Dong, Yujia Zhou, Xiao-Ou Shu, Elmer V Bernstam, Rebecca Stern, David M Aronoff, Hua Xu, Loren Lipworth

Journal Articles

In the absence of genome sequencing, two positive molecular tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) separated by negative tests, prolonged time, and symptom resolution remain the best surrogate measure of possible reinfection. Using a large electronic health record database, we characterized clinical and testing data for 23 patients with repeatedly positive SARS-CoV-2 PCR test results ≥60 days apart, separated by ≥2 consecutive negative test results. The prevalence of chronic medical conditions, symptoms, and severe outcomes related to coronavirus disease 19 (COVID-19) illness were ascertained. The median age of patients was 64.5 years, 40% were Black, and 39% …

Exome Sequence Association Study Of Levels And Longitudinal Change Of Cardiovascular Risk Factor Phenotypes In European Americans And African Americans From The Atherosclerosis Risk In Communities Study, Elena V Feofanova, Elise Lim, Han Chen, Minjae Lee, Ching-Ti Liu, L Adrienne Cupples, Eric Boerwinkle

Journal Articles

Cardiovascular disease (CVD) is responsible for 31% of all deaths worldwide. Among CVD risk factors are age, race, increased systolic blood pressure (BP), and dyslipidemia. Both BP and blood lipids levels change with age, with a dose-dependent relationship between the cumulative exposure to hyperlipidemia and the risk of CVD. We performed an exome sequence association study using longitudinal data with up to 7805 European Americans (EAs) and 3171 African Americans (AAs) from the Atherosclerosis Risk in Communities (ARIC) study. We assessed associations of common (minor allele frequency > 5%) nonsynonymous and splice-site variants and gene-based sets of rare variants with levels …

Genome-Wide Association Study Of Serum Metabolites In The African American Study Of Kidney Disease And Hypertension, Shengyuan Luo, Elena V Feofanova, Adrienne Tin, Sarah Tung, Eugene P Rhee, Josef Coresh, Dan E Arking, Aditya Surapaneni, Pascal Schlosser, Yong Li, Anna Köttgen, Bing Yu, Morgan E Grams

Journal Articles

The genome-wide association study (GWAS) is a powerful means to study genetic determinants of disease traits and generate insights into disease pathophysiology. To date, few GWAS of circulating metabolite levels have been performed in African Americans with chronic kidney disease. Hypothesizing that novel genetic-metabolite associations may be identified in a unique population of African Americans with a lower glomerular filtration rate (GFR), we conducted a GWAS of 652 serum metabolites in 619 participants (mean measured glomerular filtration rate 45 mL/min/1.73m

Associations Between Physiological Biomarkers And Psychosocial Measures Of Pregnancy-Specific Anxiety And Depression With Support Intervention, Karen L Weis, Tony T Yuan, Katherine C Walker, Thomas F Gibbons, Wenyaw Chan

Journal Articles

Stress and anxiety significantly impact the hypothalamic-pituitary axis, and in pregnancy, the subsequent maternal-fetal response can lead to poor outcomes. The objective of this study was to assess the association between psychosocial measures of pregnancy-specific anxiety and physiologic inflammatory responses. Specifically, to determine the effectiveness of the Mentors Offering Maternal Support (M-O-M-S

Digital Technology Needs In Maternal Mental Health: A Qualitative Inquiry., Alexandra Zingg, Laura Carter, Deevakar Rogith, Amy Franklin, Sudhakar Selvaraj, Jerrie Refuerzo, Sahiti Myneni

Journal Articles

Digital technologies offer many opportunities to improve mental healthcare management for women seeking pre- and-postnatal care. They provide a discrete, practical medium that is well-suited for the sensitive nature of mental health. Women who are more prone to experiencing peripartum depression (PPD), such as those of low-socioeconomic background or in high-risk pregnancies, can benefit the most from such technologies. However, current digital interventions directed towards this population provide suboptimal support, and their responsiveness to end user needs is quite limited. Our objective is to understand the digital terrain of information needs for low-socioeconomic status women with high-risk pregnancies, specifically within …

Med-Bert: Pretrained Contextualized Embeddings On Large-Scale Structured Electronic Health Records For Disease Prediction., Laila Rasmy, Yang Xiang, Ziqian Xie, Cui Tao, Degui Zhi

Journal Articles

Deep learning (DL)-based predictive models from electronic health records (EHRs) deliver impressive performance in many clinical tasks. Large training cohorts, however, are often required by these models to achieve high accuracy, hindering the adoption of DL-based models in scenarios with limited training data. Recently, bidirectional encoder representations from transformers (BERT) and related models have achieved tremendous successes in the natural language processing domain. The pretraining of BERT on a very large training corpus generates contextualized embeddings that can boost the performance of models trained on smaller datasets. Inspired by BERT, we propose Med-BERT, which adapts the BERT framework originally developed …

Generalized And Transferable Patient Language Representation For Phenotyping With Limited Data., Yuqi Si, Elmer V Bernstam, Kirk Roberts

Journal Articles

The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing. In this work, we propose a multi-task pre-training and fine-tuning approach for learning generalized and transferable patient representations from medical language. The model is first pre-trained with different but related high-prevalence phenotypes and further fine-tuned on downstream target tasks. Our main contribution focuses on the impact this technique can have on low-prevalence phenotypes, a challenging task due to the dearth of data. We validate the representation from pre-training, and fine-tune the multi-task pre-trained models on low-prevalence phenotypes including 38 circulatory diseases, 23 …

Absent B Cells, Agammaglobulinemia, And Hypertrophic Cardiomyopathy In Folliculin-Interacting Protein 1 Deficiency, Francesco Saettini, Cecilia Poli, Jaime Vengoechea, Sonia Bonanomi, Julio C Orellana, Grazia Fazio, Fred H Rodriguez, Loreani P Noguera, Claire Booth, Valentina Jarur-Chamy, Marissa Shams, Maria Iascone, Maja Vukic, Serena Gasperini, Manuel Quadri, Amairelys Barroeta Seijas, Elizabeth Rivers, Mario Mauri, Raffaele Badolato, Gianni Cazzaniga, Cristina Bugarin, Giuseppe Gaipa, Wilma G M Kroes, Daniele Moratto, Monique M Van Oostaijen-Ten Dam, Frank Baas, Silvère Van Der Maarel, Rocco Piazza, Zeynep H Coban-Akdemir, James R Lupski, Bo Yuan, Ivan K Chinn, Lucia Daxinger, Andrea Biondi

Journal Articles

Agammaglobulinemia is the most profound primary antibody deficiency that can occur due to an early termination of B-cell development. We here investigated 3 novel patients, including the first known adult, from unrelated families with agammaglobulinemia, recurrent infections, and hypertrophic cardiomyopathy (HCM). Two of them also presented with intermittent or severe chronic neutropenia. We identified homozygous or compound-heterozygous variants in the gene for folliculin interacting protein 1 (FNIP1), leading to loss of the FNIP1 protein. B-cell metabolism, including mitochondrial numbers and activity and phosphatidylinositol 3-kinase/AKT pathway, was impaired. These defects recapitulated the Fnip1-/- animal model. Moreover, we identified either uniparental disomy …

Exchanges In A Virtual Environment For Diabetes Self-Management Education And Support: Social Network Analysis., Carlos A Pérez-Aldana, Allison A Lewinski, Constance M Johnson, Allison A Vorderstrasse, Sahiti Myneni

Journal Articles

BACKGROUND: Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities.

OBJECTIVE: The objective of this study was to …

Representation Of Ehr Data For Predictive Modeling: A Comparison Between Umls And Other Terminologies., Laila Rasmy, Firat Tiryaki, Yujia Zhou, Yang Xiang, Cui Tao, Hua Xu, Degui Zhi

Journal Articles

OBJECTIVE: Predictive disease modeling using electronic health record data is a growing field. Although clinical data in their raw form can be used directly for predictive modeling, it is a common practice to map data to standard terminologies to facilitate data aggregation and reuse. There is, however, a lack of systematic investigation of how different representations could affect the performance of predictive models, especially in the context of machine learning and deep learning.

MATERIALS AND METHODS: We projected the input diagnoses data in the Cerner HealthFacts database to Unified Medical Language System (UMLS) and 5 other terminologies, including CCS, CCSR, …

Understanding Spatial Language In Radiology: Representation Framework, Annotation, And Spatial Relation Extraction From Chest X-Ray Reports Using Deep Learning., Surabhi Datta, Yuqi Si, Laritza Rodriguez, Sonya E Shooshan, Dina Demner-Fushman, Kirk Roberts

Journal Articles

Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Such spatial relationships are also linked to various differential diagnoses and often described through uncertainty phrases. Structured representation of this clinically significant spatial information has the potential to be used in a variety of downstream clinical informatics applications. Our focus is to extract these spatial representations from the reports. For this, we first define a representation framework based on the Spatial Role Labeling (SpRL) scheme, which we refer to as …

Covid-19 Testnorm: A Tool To Normalize Covid-19 Testing Names To Loinc Codes., Xiao Dong, Jianfu Li, Ekin Soysal, Jiang Bian, Scott L Duvall, Elizabeth Hanchrow, Hongfang Liu, Kristine E Lynch, Michael Matheny, Karthik Natarajan, Lucila Ohno-Machado, Serguei Pakhomov, Ruth Madeleine Reeves, Amy M Sitapati, Swapna Abhyankar, Theresa Cullen, Jami Deckard, Xiaoqian Jiang, Robert Murphy, Hua Xu

Journal Articles

Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) …

Deep Learning In Clinical Natural Language Processing: A Methodical Review., Stephen Wu, Kirk Roberts, Surabhi Datta, Jingcheng Du, Zongcheng Ji, Yuqi Si, Sarvesh Soni, Qiong Wang, Qiang Wei, Yang Xiang, Bo Zhao, Hua Xu

Journal Articles

OBJECTIVE: This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the clinical domain, providing quantitative analysis to answer 3 research questions concerning methods, scope, and context of current research.

MATERIALS AND METHODS: We searched MEDLINE, EMBASE, Scopus, the Association for Computing Machinery Digital Library, and the Association for Computational Linguistics Anthology for articles using DL-based approaches to NLP problems in electronic health records. After screening 1,737 articles, we collected data on 25 variables across 212 papers.

RESULTS: DL in clinical NLP publications more than doubled each year, through 2018. Recurrent neural networks (60.8%) …

Digilego For Peripartum Depression: A Novel Patient-Facing Digital Health Instantiation, J Rodin, C Timko, S Harris

Journal Articles

Digital health technologies offer unique opportunities to improve health outcomes for mental health conditions such as peripartum depression (PPD), a disorder that affects approximately 10-15% of women in the U.S. every year. In this paper, we present the adaption of a digital technology development framework, Digilego, in the context of PPD. Methods include mapping of the Behavior Intervention Technology (BIT) model and the Patient Engagement Framework (PEF) to translate patient needs captured through focus groups. This informs formative development and implementation of digital health features for optimal patient engagement in PPD screening and management. Results show an array ofPPD-specific Digilego …

Enhancing Clinical Concept Extraction With Contextual Embeddings., Yuqi Si, Jingqi Wang, Hua Xu, Kirk Roberts

Journal Articles

OBJECTIVE: Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Recently, however, more advanced embedding methods and representations (eg, ELMo, BERT) have further pushed the state of the art in NLP, yet there are no common best practices for how to integrate these representations into clinical tasks. The purpose of this study, then, is to explore the space of possible options in utilizing these new models for clinical concept extraction, including comparing these to traditional word embedding methods (word2vec, GloVe, fastText).

MATERIALS AND METHODS: Both off-the-shelf, open-domain embeddings and …

Ankle And Midtarsal Joint Quasi-Stiffness During Walking With Added Mass, Andrew M. Kern, Nikolaos Papachatzis, Jeffrey M. Patterson, Dustin A. Bruening, Kota Z. Takahashi

Journal Articles

Examination of how the ankle and midtarsal joints modulate stiffness in response to increased force demand will aid understanding of overall limb function and inform the development of bio-inspired assistive and robotic devices. The purpose of this study is to identify how ankle and midtarsal joint quasi-stiffness are affected by added body mass during over-ground walking. Healthy participants walked barefoot over-ground at 1.25 m/s wearing a weighted vest with 0%, 15% and 30% additional body mass. The effect of added mass was investigated on ankle and midtarsal joint range of motion (ROM), peak moment and quasi-stiffness. Joint quasi-stiffness was broken …

Pm, Amal Rammah, Kristina W Whitworth, Inkyu Han, Wenyaw Chan, Elaine Symanski

Journal Articles

There is limited evidence on the role of exposure to chemical constituents of fine particulate matter (PM