Please use this identifier to cite or link to this item:
Title: A COVID-19 Test Triage Tool, Predicting Negative Results and Reducing the Testing Burden on Healthcare Systems During a Pandemic.
Austin Authors: Lundon, Dara J;Kelly, Brian D ;Nair, Sujit;Bolton, Damien M ;Patel, Gopi;Reich, David;Tewari, Ashutosh
Affiliation: Department of Infectious Diseases, Icahn School of Medicine, Mount Sinai Hospitals, New York, NY, United States
Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
Department of Urology, Icahn School of Medicine, Mount Sinai Hospitals, New York, NY, United States
Issue Date: Apr-2021
Date: 2021
Publication information: Frontiers in Medicine 2021; 8: 563465
Abstract: Background: Detecting and isolating cases of COVID-19 are amongst the key elements listed by the WHO to reduce transmission. This approach has been reported to reduce those symptomatic with COVID-19 in the population by over 90%. Testing is part of a strategy that will save lives. Testing everyone maybe ideal, but it is not practical. A risk tool based on patient demographics and clinical parameters has the potential to help identify patients most likely to test negative for SARS-CoV-2. If effective it could be used to aide clinical decision making and reduce the testing burden. Methods: At the time of this analysis, a total of 9,516 patients with symptoms suggestive of Covid-19, were assessed and tested at Mount Sinai Institutions in New York. Patient demographics, clinical parameters and test results were collected. A robust prediction pipeline was used to develop a risk tool to predict the likelihood of a positive test for Covid-19. The risk tool was analyzed in a holdout dataset from the cohort and its discriminative ability, calibration and net benefit assessed. Results: Over 48% of those tested in this cohort, had a positive result. The derived model had an AUC of 0.77, provided reliable risk prediction, and demonstrated a superior net benefit than a strategy of testing everybody. When a risk cut-off of 70% was applied, the model had a negative predictive value of 96%. Conclusion: Such a tool could be used to help aide but not replace clinical decision making and conserve vital resources needed to effectively tackle this pandemic.
DOI: 10.3389/fmed.2021.563465
Journal: Frontiers in Medicine
PubMed URL: 33996839
ISSN: 2296-858X
Type: Journal Article
Subjects: COVID-19
clinical decision aid
resource allocation
risk prediction
Appears in Collections:Journal articles

Files in This Item:
File Description SizeFormat 
26566.pdf842.92 kBAdobe PDFThumbnail
Show full item record

Page view(s)

checked on Nov 28, 2023


checked on Nov 28, 2023

Google ScholarTM


Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.