About: Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis

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About: Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis
Creator	Temesgen, Zelalem Bauer, Philippe O'horo, John Anand, Akash Barve, Rakesh Puranik, Arjun Razonable, Raymund Solomon, Hugo Soundararajan, Venky Venkatakrishnan, A Wagner, Tyler Awasthi, Samir Badley, Andrew Halamka, John Anand, Praveen Bade, Sairam Challener, Douglas De Veerdonk, Doctor, Zainab Gores, Gregory Kang, Martin Liebers, Matt Mahmood, Maryam Morice Ii, William Murugadoss, Karthik Pickering, Brian Rizza, Stacey Shweta, Fnu Silvert, Eli Vergidis, Paschalis Williams, Amy Wilson, Walter
Source	Medline; PMC
abstract	Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVID(pos); n = 2,317) versus COVID-19-negative (COVID(neg); n = 74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVID(pos) over COVID(neg) patients. The combination of cough and fever/chills has 4.2-fold amplification in COVID(pos) patients during the week prior to PCR testing, in addition to anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.
has issue date	2020-07-07(xsd:dateTime)
bibo:doi	10.7554/elife.58227
bibo:pmid	32633720
has license	cc-by
sha1sum (hex)	2c389672ab46947d52b22c261beda997172d322a
schema:url	https://doi.org/10.7554/elife.58227
resource representing a document's title	Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis
has PubMed Central identifier	PMC7410498
has PubMed identifier	32633720
schema:publication	eLife
resource representing a document's body	covid:2c389672ab46947d52b22c261beda997172d322a#body_text
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