PLoS ONE (Jan 2020)

COVID-MATCH65-A prospectively derived clinical decision rule for severe acute respiratory syndrome coronavirus 2.

  • Jason A Trubiano,
  • Sara Vogrin,
  • Olivia C Smibert,
  • Nada Marhoon,
  • Adrian A Alexander,
  • Kyra Y L Chua,
  • Fiona L James,
  • Nicholas R L Jones,
  • Sam E Grigg,
  • Cecilia L H Xu,
  • Nasreen Moini,
  • Sam R Stanley,
  • Michael T Birrell,
  • Morgan T Rose,
  • Claire L Gordon,
  • Jason C Kwong,
  • Natasha E Holmes

DOI
https://doi.org/10.1371/journal.pone.0243414
Journal volume & issue
Vol. 15, no. 12
p. e0243414

Abstract

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ObjectivesWe report on the key clinical predictors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and present a clinical decision rule that can risk stratify patients for COVID-19.Design, participants and settingA prospective cohort of patients assessed for COVID-19 at a screening clinic in Melbourne, Australia. The primary outcome was a positive COVID-19 test from nasopharyngeal swab. A backwards stepwise logistic regression was used to derive a model of clinical variables predictive of a positive COVID-19 test. Internal validation of the final model was performed using bootstrapped samples and the model scoring derived from the coefficients, with modelling performed for increasing prevalence.ResultsOf 4226 patients with suspected COVID-19 who were assessed, 2976 patients underwent SARS-CoV-2 testing (n = 108 SARS-CoV-2 positive) and were used to determine factors associated with a positive COVID-19 test. The 7 features associated with a positive COVID-19 test on multivariable analysis were: COVID-19 patient exposure or international travel, Myalgia/malaise, Anosmia or ageusia, Temperature, Coryza/sore throat, Hypoxia-oxygen saturation ConclusionsFrom the largest prospective outpatient cohort of suspected COVID-19 we define the clinical factors predictive of a positive SARS-CoV-2 test. The subsequent clinical decision rule, COVID-MATCH65, has a high sensitivity and NPV for SARS-CoV-2 and can be employed in the pandemic, adjusted for disease prevalence, to aid COVID-19 risk-assessment and vital testing resource allocation.