Article Text

other Versions

Download PDFPDF
Early warning scores to assess the probability of critical illness in patients with COVID-19
  1. Lars Veldhuis1,
  2. Milan L Ridderikhof1,
  3. Michiel Schinkel2,
  4. Joop van den Bergh3,
  5. Martijn Beudel4,
  6. Tom Dormans5,
  7. Renee Douma6,
  8. Niels Gritters van den Oever7,
  9. Lianne de Haan6,
  10. Karen Koopman8,
  11. Martijn D de Kruif5,
  12. Peter Noordzij9,
  13. Auke Reidinga8,
  14. Wouter de Ruijter10,
  15. Suat Simsek10,
  16. Caroline Wyers3,
  17. Prabath WB Nanayakkara11,
  18. Markus Hollmann12
  1. 1Emergency Medicine, Amsterdam UMC - Locatie AMC, Amsterdam, The Netherlands
  2. 2Internal Medicine, Amsterdam UMC Locatie VUmc, Amsterdam, Noord-Holland, The Netherlands
  3. 3Internal Medicine, VieCuri Medical Centre, Venlo, Limburg, The Netherlands
  4. 4Department of Neurology, Amsterdam UMC Locatie AMC, Amsterdam, North Holland, The Netherlands
  5. 5Intensive Care, Zuyderland Medical Centre Heerlen, Heerlen, Limburg, The Netherlands
  6. 6Internal Medicine, Flevoziekenhuis, Almere, Flevoland, The Netherlands
  7. 7Intensive Care, Treant Zorggroep, Hoogeveen, Drenthe, The Netherlands
  8. 8Intensive Care, Martini Ziekenhuis, Groningen, Groningen, The Netherlands
  9. 9Intensive Care, Saint Antonius, Nieuwegein, The Netherlands
  10. 10Internal Medicine, Noordwest Ziekenhuisgroep, Alkmaar, Noord-Holland, The Netherlands
  11. 11Section Acute Medicine, Department of Internal Medicine, Amsterdam Universitair Medische Centra, Amsterdam, Noord-Holland, The Netherlands
  12. 12Anaesthesiology, Amsterdam UMC - Locatie AMC, Amsterdam, The Netherlands
  1. Correspondence to Lars Veldhuis, Emergency Medicine, Amsterdam UMC - Locatie AMC, Amsterdam, Netherlands; l.i.veldhuis{at}amsterdamumc.nl

Abstract

Objective Validated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current study was to evaluate the performance of early warning scores (EWS) in the ED when identifying patients with COVID-19 who will require intensive care unit (ICU) admission for high-flow-oxygen usage or mechanical ventilation.

Methods Patients with a proven SARS-CoV-2 infection with complete resuscitate orders treated in nine hospitals between 27 February and 30 July 2020 needing hospital admission were included. Primary outcome was the performance of EWS in identifying patients needing ICU admission within 24 hours after ED presentation.

Results In total, 1501 patients were included. Median age was 71 (range 19–99) years and 60.3% were male. Of all patients, 86.9% were admitted to the general ward and 13.1% to the ICU within 24 hours after ED admission. ICU patients had lower peripheral oxygen saturation (86.7% vs 93.7, p≤0.001) and had a higher body mass index (29.2 vs 27.9 p=0.043) compared with non-ICU patients. National Early Warning Score 2 (NEWS2) ≥ 6 and q-COVID Score were superior to all other studied clinical risk scores in predicting ICU admission with a fair area under the receiver operating characteristics curve of 0.740 (95% CI 0.696 to 0.783) and 0.760 (95% CI 0.712 to 0.800), respectively. NEWS2 ≥6 and q-COVID Score ≥3 discriminated patients admitted to the ICU with a sensitivity of 78.1% and 75.9%, and specificity of 56.3% and 61.8%, respectively.

Conclusion In this multicentre study, the best performing models to predict ICU admittance were the NEWS2 and the Quick COVID-19 Severity Index Score, with fair diagnostic performance. However, due to the moderate performance, these models cannot be clinically used to adequately predict the need for ICU admission within 24 hours in patients with SARS-CoV-2 infection presenting at the ED.

  • emergency department
  • intensive care
  • COVID-19
  • risk management

Data availability statement

Data may be obtained from a third party and are not publicly available. We used data from the ongoing COVIDPredict Clinical Course Cohort. This is a nationwide database. Data may be used exclusively by scientists from the included hospitals.

This article is made freely available for use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non-commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.

https://bmj.com/coronavirus/usage

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Data availability statement

Data may be obtained from a third party and are not publicly available. We used data from the ongoing COVIDPredict Clinical Course Cohort. This is a nationwide database. Data may be used exclusively by scientists from the included hospitals.

View Full Text

Footnotes

  • Handling editor Katie Walker

  • Twitter @SchinkelMichiel

  • Contributors JB, MB, TD, RD, NG, LH, KK, MK, PN, AR, WR, SS, CW collected the data. LV designed, analysed, interpreted the data and draft the article. ML, MS, JB, MB, RD, SS, CW, PN, MH revised critically for important intellectual content and helped with the final version to be submitted. LV is the gauranter of this study.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.