ArticleJournal of biomedical informatics2021
ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes.
Article in Journal of biomedical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.The Cochrane database of systematic reviews · 2022Pooled it
- Exploring beyond diagnoses in electronic health records to improve discovery: a review of the phenome-wide association study.JAMIA open · 2025Review
- Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability in Medical Research: Comprehensive Review.Journal of medical Internet research · 2025Review
- A latent transfer learning method for estimating hospital-specific post-acute healthcare demands following SARS-CoV-2 infection.Patterns (New York, N.Y.) · 2024Article
- Improving reporting standards for phenotyping algorithm in biomedical research: 5 fundamental dimensions.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study.Journal of medical Internet research · 2023Article
- Medical Experts' Agreement on Risk Assessment Based on All Possible Combinations of the COVID-19 Predictors-A Novel Approach for Public Health Screening and Surveillance.International journal of environmental research and public health · 2022Article
- Novel informatics approaches to COVID-19 Research: From methods to applications.Journal of biomedical informatics · 2022Article
- Comparing automated vs. manual data collection for COVID-specific medications from electronic health records.International journal of medical informatics · 2022Article
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10 authors.
Funding
Abstract
objectiveIdentifying symptoms and characteristics highly specific to coronavirus disease 2019 (COVID-19) would improve the clinical and public health response to this pandemic challenge. Here, we describe a high-throughput approach - Concept-Wide Association Study (ConceptWAS) - that systematically scans a disease's clinical manifestations from clinical notes. We used this method to identify symptoms specific to COVID-19 early in the course of the pandemic.
methodsWe created a natural language processing pipeline to extract concepts from clinical notes in a local ER corresponding to the PCR testing date for patients who had a COVID-19 test and evaluated these concepts as predictors for developing COVID-19. We identified predictors from Firth's logistic regression adjusted by age, gender, and race. We also performed ConceptWAS using cumulative data every two weeks to identify the timeline for recognition of early COVID-19-specific symptoms.
resultsWe processed 87,753 notes from 19,692 patients subjected to COVID-19 PCR testing between March 8, 2020, and May 27, 2020 (1,483 COVID-19-positive). We found 68 concepts significantly associated with a positive COVID-19 test. We identified symptoms associated with increasing risk of COVID-19, including "anosmia" (odds ratio [OR] = 4.97, 95% confidence interval [CI] = 3.21-7.50), "fever" (OR = 1.43, 95% CI = 1.28-1.59), "cough with fever" (OR = 2.29, 95% CI = 1.75-2.96), and "ageusia" (OR = 5.18, 95% CI = 3.02-8.58). Using ConceptWAS, we were able to detect loss of smell and loss of taste three weeks prior to their inclusion as symptoms of the disease by the Centers for Disease Control and Prevention (CDC).
conclusionConceptWAS, a high-throughput approach for exploring specific symptoms and characteristics of a disease like COVID-19, offers a promise for enabling EHR-powered early disease manifestations identification.
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