Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department

BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. METHODS: In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. RESULTS: The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. CONCLUSIONS: Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance

Exploring Racial and Age Disproportionalities in COVID-19 Positive Pediatric Cohort

Background: Social and health inequities place marginalized populations at increased risk of contracting the novel coronavirus 2019 (COVID-19). While COVID-19 literature continues to accumulate, there remains a lack of comprehensive epidemiological data on COVID-19 in children. The study aims to identify demographic trends in disease severity amongst COVID-19 positive pediatric patients. Methods: We analyzed the medical records of 2217 laboratory-confirmed COVID-19 pediatric patients, ages 0-18, across Indiana. Working with Regenstrief Institute Center of Biomedical Informatics, data was extracted from the databases of Indiana Network for Patient Care, Indiana University Health, and Eskenazi Health from February 28th, 2020 to July 13th, 2020. Factors of interest were age, race, and ethnicity. The study assessed the clinical outcome of disease severity which was defined by one of the following clinical designations: outpatient management exclusively, emergency care without hospital admission, non-pediatric intensive care unit (PICU) hospitalization, PICU hospitalization, and death. Results: The laboratory confirmed COVID-19 pediatric cohort was composed of 12.2% (N= 270) Black or African American, 49.3% (N=1094) white, and 3.2% (N= 71) American Indian/Alaska Native, Asian/Pacific Islander, and Multiracial combined group. 34.4% of Black or African American patients required emergency (12.2%) or inpatient care (22.2%) while 24.4% white patients required emergency (7.0%) or inpatient care (17.3%). 17.6% of the cohort was 0-5 years old, 24.8% was 6-12 years old, and 57.6% was 13-18 years old. 30.9% of the 0-5 age group required emergency or inpatient care while the percentages of the 6-12 age group and 13-18 age group requiring emergency or inpatient care were 20.6% and 18.9%, respectively. Conclusion: While our data is preliminary and requires additional validation, our exploration of racial and age disproportionalities in pediatric coronavirus severity serves to expand on the current COVID-19 literature and understanding of this virus

The VHL/HIF Axis in the Development and Treatment of Pheochromocytoma/Paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from chromaffin cells in the adrenal medulla (PCCs) or extra-adrenal sympathetic or parasympathetic paraganglia (PGLs). About 40% of PPGLs result from germline mutations and therefore they are highly inheritable. Although dysfunction of any one of a panel of more than 20 genes can lead to PPGLs, mutations in genes involved in the VHL/HIF axis includin

An incoherent regulatory network architecture that orchestrates B cell diversification in response to antigen signaling

B cell receptor signaling controls the expression of IRF-4, a transcription factor required for B cell differentiation. This study shows that IRF-4 regulates divergent B cell fates via a ‘kinetic-control' mechanism that determines the duration of a transient developmental state

The Airlines’ Recent Experience Under the Railway Labor Act

Silky-feather has been selected and fixed in some breeds due to its unique appearance. This phenotype is caused by a single recessive gene (hookless, h). Here we map the silky-feather locus to chromosome 3 by linkage analysis and subsequently fine-map it to an 18.9 kb interval using the identical by descent (IBD) method. Further analysis reveals that a C to G transversion located upstream of the prenyl (decaprenyl) diphosphate synthase, subunit 2 (PDSS2) gene is causing silky-feather. All silky-feather birds are homozygous for the G allele. The silky-feather mutation significantly decreases the expression of PDSS2 during feather development in vivo. Consistent with the regulatory effect, the C to G transversion is shown to remarkably reduce PDSS2 promoter activity in vitro. We report a new example of feather structure variation associated with a spontaneous mutation and provide new insight into the PDSS2 function

Expression and Function of NUMB in Odontogenesis

NUMB is a multifunctional protein implicated to function in self-renewal and differentiation of progenitors in several tissues. To characterize the transcripts and to analyze the expression pattern of NUMB in odontogenesis, we isolated 2 full-length clones for NUMB from mouse dental pulp mRNA. One novel sequence contained 200 bp insertion in the phosphotyrosine binding domain (PTB). Confocal microscopy analysis showed strong NUMB expression in human dental pulp stem cells (hDPSC) and preameloblasts. Western blot analysis indicated that NUMB isoforms were differentially expressed in various dental tissues. Immunohistochemical analysis showed that in postnatal mouse tooth germs, NUMB was differentially expressed in the preameloblasts, odontoblasts, cervical loop region, and in the dental pulp stem cells during development. Interestingly, overexpression of NUMB in HAT-7, a preameloblast cell line, had dramatic antagonizing effects on the protein expression level of activated Notch 1. Further analysis of the Notch signaling pathway showed that NUMB significantly downregulates sonic hedgehog (Shh) expression in preameloblasts. Therefore, we propose that NUMB maintains ameloblast progenitor phenotype at the cervical loop by downregulating the activated Notch1 protein and thereby inhibiting the mRNA expression of Shh