PLoS ONE (Jan 2021)

Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021.

  • Jeffrey A Kline,
  • Carlos A Camargo,
  • D Mark Courtney,
  • Christopher Kabrhel,
  • Kristen E Nordenholz,
  • Thomas Aufderheide,
  • Joshua J Baugh,
  • David G Beiser,
  • Christopher L Bennett,
  • Joseph Bledsoe,
  • Edward Castillo,
  • Makini Chisolm-Straker,
  • Elizabeth M Goldberg,
  • Hans House,
  • Stacey House,
  • Timothy Jang,
  • Stephen C Lim,
  • Troy E Madsen,
  • Danielle M McCarthy,
  • Andrew Meltzer,
  • Stephen Moore,
  • Craig Newgard,
  • Justine Pagenhardt,
  • Katherine L Pettit,
  • Michael S Pulia,
  • Michael A Puskarich,
  • Lauren T Southerland,
  • Scott Sparks,
  • Danielle Turner-Lawrence,
  • Marie Vrablik,
  • Alfred Wang,
  • Anthony J Weekes,
  • Lauren Westafer,
  • John Wilburn

DOI
https://doi.org/10.1371/journal.pone.0248438
Journal volume & issue
Vol. 16, no. 3
p. e0248438

Abstract

Read online

ObjectivesAccurate 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.MethodsData 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.ResultsMultivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation75% probability with +5 or more points).ConclusionCriteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints.