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 (COVIDpos; n = 2,317) versus COVID-19-negative (COVIDneg; 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 COVIDpos over COVIDneg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVIDpos 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.

中文翻译：

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来自大型 EHR 系统的临床记录的增强管理揭示了即将诊断出 COVID-19 的症状

了解 COVID-19 症状的时间动态可以提供细粒度的分辨率来指导临床决策。在这里，我们在机构范围的平台上使用深度神经网络来增强对 77,167 名接受 COVID-19 PCR 测试的患者的临床记录的管理。通过对比 PCR 测试日期前一周的 COVID-19 阳性（COVIDpos；n = 2,317）与 COVID-19 阴性（COVIDneg；n = 74,850）患者的电子健康记录 (EHR) 衍生症状，我们确定了嗅觉缺失/味觉障碍（27.1倍）、发烧/寒战（2.6倍）、呼吸困难（2.2倍）、咳嗽（2.2倍）、肌痛/关节痛（2倍）和腹泻（1.4倍）同样显着在 COVIDpos 中对 COVIDneg 患者进行了放大。咳嗽和发烧/发冷的组合有 4。除了嗅觉障碍/味觉障碍外，在 PCR 测试前一周内 COVIDpos 患者的 2 倍扩增构成了 COVID-19 最早的 EHR 衍生特征。本研究引入了一个增强智能平台，用于实时合成机构生物医学知识。该平台具有扩大治疗吞吐量的巨大潜力，从而实现 EHR 支持的早期疾病诊断。