Rapid identification of SARS-CoV-2-infected patients at the emergency department using routine testing

Steef Kurstjens, Armando Van Der Horst, Robert Herpers, Mick W.L. Geerits, Yvette C.M. Kluiters-De Hingh, Eva Leonne Göttgens, Martinus J.T. Blaauw, Marc H.M. Thelen, Marc G.L.M. Elisen, Ron Kusters*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

23 Citations (Scopus)
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Abstract

Objectives: The novel coronavirus disease 19 (COVID-19), caused by SARS-CoV-2, spreads rapidly across the world. The exponential increase in the number of cases has resulted in overcrowding of emergency departments (ED). Detection of SARS-CoV-2 is based on an RT-PCR of nasopharyngeal swab material. However, RT-PCR testing is time-consuming and many hospitals deal with a shortage of testing materials. Therefore, we aimed to develop an algorithm to rapidly evaluate an individual's risk of SARSCoV-2 infection at the ED. Methods: In this multicenter retrospective study, routine laboratory parameters (C-reactive protein, lactate dehydrogenase, ferritin, absolute neutrophil and lymphocyte counts), demographic data and the chest X-ray/CT result from 967 patients entering the ED with respiratory symptoms were collected. Using these parameters, an easy-to-use point-based algorithm, called the corona-score, was developed to discriminate between patients that tested positive for SARS-CoV-2 by RT-PCR and those testing negative. Computational sampling was used to optimize the corona-score. Validation of the model was performed using data from 592 patients. Results: The corona-score model yielded an area under the receiver operating characteristic curve of 0.91 in the validation population. Patients testing negative for SARSCoV-2 showed a median corona-score of 3 vs. 11 (scale 0-14) in patients testing positive for SARS-CoV-2 (p<0.001). Using cut-off values of 4 and 11 the model has a sensitivity and specificity of 96 and 95%, respectively. Conclusions: The corona-score effectively predicts SARSCoV-2 RT-PCR outcome based on routine parameters. This algorithm provides the means for medical professionals to rapidly evaluate SARS-CoV-2 infection status of patients presenting at the ED with respiratory symptoms.

Original languageEnglish
Pages (from-to)1587-1593
Number of pages7
JournalClinical Chemistry and Laboratory Medicine
Volume58
Issue number9
DOIs
Publication statusPublished - 29 Jun 2020

Keywords

  • Algorithm
  • COVID-19
  • Coronavirus
  • Emergency department
  • Pandemic
  • Prediction-model
  • SARS-CoV-2

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