Evaluation of triage methods used to select patients with suspected pandemic influenza for hospital admission Kirsty Challen, 1,2 Steve W Goodacre, 1 Richard Wilson, 1 Andrew Bentley, 3 Mike Campbell, 4 Christopher Fitzsimmons, 5 Darren Walter 6 ABSTRACT Objectives Prepandemic projections anticipated huge excess attendances and mortality in an influenza pandemic. A number of tools had been suggested for triaging patients with influenza for inpatient and critical care admission, but none had been validated in these patients. The authors aimed to evaluate three potential triage toolsdCURB-65, PMEWS and the Department of Health community assessment tool (CAT)din patients in the first waves of the 2009 H1N1 pandemic. Setting Prospective cohort study in three urban emergency departments (one adult, one paediatric, one mixed) in two cities. Participants All patients presenting to the three emergency departments fulfilling the national definition of suspected pandemic influenza. Outcome measures 30-day follow-up identified patients who had died or had required advanced respiratory, cardiovascular or renal support. Results The pandemic was much less severe than expected. A total of 481 patients (347 children) were recruited, of which only five adults fulfilled the outcome criteria for severe illness. The c-statistics for CURB-65, PMEWS and CAT in adults in terms of discriminating between those admitted and discharged were 0.65 (95% CI 0.54 to 0.76), 0.76 (95% CI 0.66 to 0.86) and 0.62 (95% CI 0.51 to 0.72), respectively. In detecting adverse outcome, sensitivities were 20% (95% CI 4% to 62%), 80% (95% CI 38% to 96%) and 60% (95% CI 23% to 88%), and specificities were 94% (95% CI 88% to 97%), 40% (95% CI 32% to 49%) and 81% (95% CI 73% to 87%) for CURB-65, PMEWS and CAT, respectively. Conclusions Although limited by a paucity of cases, this research shows that current triage methods for suspected pandemic influenza did not reliably discriminate between patients with good and poor outcomes. INTRODUCTION An influenza pandemic could potentially place a huge strain on health and emergency care services, which may be exacerbated by staff sickness. The 2007 UK influenza pandemic contingency plan predicted 750 000 excess emergency department (ED) atten- dances and 82 500 excess hospitalisations. 1 Under these circumstances, it would be impractical for all patients to be fully assessed by a senior clinician. We therefore need methods of triage and resource allo- cation that are fair, robust and reproducible. 2 ED triage methods need to predict accurately the indi- vidual patient’s risk of death or severe illness; low-risk patients may be discharged home, high-risk patients admitted to hospital, and those at very high risk referred for high dependency or intensive care. In April 2009, a new strain of A/H1N1 influenza (swine flu) was detected in Mexico and started to spread globally, being declared a pandemic in June. Before this, Health Protection Agency guidance recommended the use of the CURB-65 pneumonia score 3 (appendix 1) for risk stratification of influenza-related pneumonia. Department of Health guidelines on surge capacity recommended use of CURB-65 ‘when assessing patients with influenza- like illness during a pandemic’, and also considered use of a physiological-social score (PMEWS) 4 (appendix 2), which includes physiological variables, age, social factors, chronic disease and performance status. National guidance produced in early 2009 included a new swine flu hospital pathway, based on a community assessment tool (CAT) with seven criteria, any one of which predicts increased risk and the need for hospital assessment 5 (appendices 3 and 4). This was flagged as being for use only where demand placed severe strain on surge capacity. CURB-65 performs reasonably as a mortality predictor in adults with community-acquired pneumonia (area under the receiver operating characteristic curve (AUROC) 0.76), 6 but less well in predicting the need for critical care (AUROC 0.69 7 and 0.64 8 ). PMEWS is not a particularly good predictor of death in community-acquired pneu- monia (AUROC 0.66), but performs better at predicting a requirement for critical care (AUROC 0.83) 8 and has shown promise in prehospital care in determining the need for ED attendance (AUROC 0.71 9 and 0.8 10 ). The CAT appears to have been developed by expert consensus without validation in the appropriate patient populations. To our knowledge there have been no studies evaluating any of these triage methods in patients with suspected pandemic influenza. We therefore aimed to use the initial waves of the H1N1 pandemic to evaluate ED triage methods for predicting severe illness or death in patients with suspected pandemic influenza. METHODS We undertook a prospective cohort study of patients presenting to the ED between September 2009 and February 2010 with suspected pandemic influenza. Patients were eligible for inclusion if they met the criteria of (1) fever (fever $388C) or a history of fever and (2) influenza-like illness (two or more of cough, sore throat, rhinorrhoea, limb or joint pain, headache, vomiting or diarrhoea) or severe and/or life- 1 School of Health and Related Research, University of Sheffield, Sheffield, UK 2 Emergency Medicine, North West Deanery, UK 3 Department of Respiratory and Intensive Care Medicine, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK 4 Department of Medical Statistics, School of Health and Related Research, University of Sheffield, Sheffield, UK 5 Department of Paediatric Emergency Medicine, Sheffield Children’s Hospital, Sheffield, UK 6 Department of Emergency Medicine, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK Correspondence to Kirsty Challen, School of Health and Related Research, University of Sheffield, Regent Court, Sheffield S1 4DA, UK; kirstychallen@hotmail.com Department of Health Disclaimer: the views and opinions expressed herein are those of the authors and do not necessarily reflect those of the Department of Health. Accepted 27 March 2011 Published Online First 17 May 2011 Emerg Med J 2012;29:383e388. doi:10.1136/emj.2010.104380 383 Original article group.bmj.com on April 27, 2012 - Published by emj.bmj.com Downloaded from