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Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study
Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Amanda Loban; Simon Waterhouse; Richard Simmonds; Katie Biggs; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter.
Affiliation
  • Ben Thomas; University of Sheffield
  • Steve Goodacre; University of Sheffield
  • Ellen Lee; University of Sheffield
  • Laura Sutton; University of Sheffield
  • Amanda Loban; University of Sheffield
  • Simon Waterhouse; University of Sheffield
  • Richard Simmonds; University of Sheffield
  • Katie Biggs; University of Sheffield
  • Carl Marincowitz; University of Sheffield
  • Jose Schutter; University of Sheffield
  • Sarah Connelly; University of Sheffield
  • Elena Sheldon; University of Sheffield
  • Jamie Hall; University of Sheffield
  • Emma Young; University of Sheffield
  • Andrew Bentley; Manchester University NHS Foundation Trust
  • Kirsty Challen; Lancashire Teaching Hospitals NHS Foundation Trust
  • Chris Fitzsimmons; Sheffield Children's NHS Foundation Trust
  • Tim Harris; Barts Health NHS Trust
  • Fiona Lecky; University of Sheffield
  • Andrew Lee; University of Sheffield
  • Ian Maconochie; Imperial College Healthcare NHS Trust
  • Darren Walter; Manchester University NHS Foundation Trust
Preprint in En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20185892
ABSTRACT
ObjectivesThe World Health Organisation (WHO) and National Institute for Health and Care Excellence (NICE) recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in adults presenting to the emergency department (ED) with suspected COVID-19 infection. MethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the United Kingdom (UK). We collected data from people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment with the following triage tools the WHO algorithm, NEWS2, CURB-65, CRB-65, PMEWS and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome. ResultsWe analysed data from 20892 adults, of whom 4672 (22.4%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2614 (12.5%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point) 0.70; SFAHP (7-point) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support. At the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.96 and 0.95 respectively), at the expense of specificity (0.31 and 0.27 respectively). NEWS2 showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used. ConclusionCURB-65, PMEWS and NEWS2 provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity. RegistrationISRCTN registry, ISRCTN28342533, http//www.isrctn.com/ISRCTN28342533
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Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Cohort_studies / Observational_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Cohort_studies / Observational_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint