Document Type
Article
Publication Date
3-1-2021
Publication Title
PLoS ONE
Abstract
Objectives Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. Methods Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. Results Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age50 years, measured temperature37.5C, oxygen saturation 95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and-1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n = 9,975), the probability from logistic regression score produced an area under the receiver operating characteristic curve of 0.80 (95% CI: 0.79 0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified score, a score of zero produced a sensitivity of 95.6% (94.8 96.3%), specificity of 20.0% (19.0 21.0%), negative likelihood ratio of 0.22 (0.19 0.26). Increasing points on the simplified score predicted higher probability of infection (e.g., 75% probability with +5 or more points). Conclusion Criteria that are available at the point of care can accurately predict the probability of SARSCoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints.
First Page
1
Last Page
15
PubMed ID
33690722
Volume
16
Issue
3 March
Publisher
Public Library of Science
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Kline, Jeffrey A.; Camargo, Carlos A.; Courtney, D. Mark; Kabrhel, Christopher; Nordenholz, Kristen E.; Aufderheide, Thomas; Baugh, Joshua J.; Beiser, David G.; Bennett, Christopher L.; Bledsoe, Joseph; Castillo, Edward; Straker, Makini Chisolm; Goldberg, Elizabeth M.; House, Hans; House, Stacey; Jang, Timothy; Lim, Stephen C.; Madsen, Troy E.; McCarthy, Danielle M.; Meltzer, Andrew; Moore, Stephen; Newgard, Craig; Pagenhardt, Justine; Pettit, Katherine L.; Pulia, Michael S.; Puskarish, Michael A.; Southerland, Lauren T.; Sparks, Scott; Turner-Lawrence, Danielle; and Vrablik, Marie, "Clinical Prediction Rule for SARS-CoV-2 Infection From 116 U.S. Emergency Departments 2-22-2021" (2021). School of Medicine Faculty Publications. 120.
https://digitalscholar.lsuhsc.edu/som_facpubs/120
10.1371/journal.pone.0248438
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