Author: Wagner, Tyler; Shweta, FNU; Murugadoss, Karthik; Awasthi, Samir; Venkatakrishnan, AJ; Bade, Sairam; Puranik, Arjun; Kang, Martin; Pickering, Brian W; O'Horo, John C; Bauer, Philippe R; Razonable, Raymund R; Vergidis, Paschalis; Temesgen, Zelalem; Rizza, Stacey; Mahmood, Maryam; Wilson, Walter R; Challener, Douglas; Anand, Praveen; Liebers, Matt; Doctor, Zainab; Silvert, Eli; Solomon, Hugo; Anand, Akash; Barve, Rakesh; Gores, Gregory; Williams, Amy W; Morice, William G; Halamka, John; Badley, Andrew; Soundararajan, Venky
Title: Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis Cord-id: plne3xlz Document date: 2020_7_7
ID: plne3xlz
Snippet: 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
Document: 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.
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