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Predicting influenza A and 2009 H1N1 influenza in patients admitted to hospital with acute respiratory illness
  1. Gerben B Keijzers1,2,
  2. Caleb Nathaniel Kai-Lik Vossen1,
  3. Ping Zhang2,
  4. Debourough MacBeth3,
  5. Petra Derrington4,
  6. John Gregory Gerrard5,
  7. Jenny Doust2
  1. 1Emergency Department, Gold Coast Health Service District, Gold Coast, Queensland, Australia
  2. 2Bond University, Gold Coast, Queensland, Australia
  3. 3Department of Infection Control, Gold Coast Health Service District, Gold Coast, Queensland, Australia
  4. 4Pathology Queensland, Gold Coast Microbiology, Gold Coast Health Service District, Gold Coast, Queensland, Australia
  5. 5Department of Medicine (Infectious Diseases), Gold Coast Health Service District, Queensland, Australia, Gold Coast, Queensland, Australia
  1. Correspondence to Dr Gerben Keijzers, Emergency Department, Gold Coast Hospital, 108 Nerang Street, Southpor, Gold Coast, Queensland 4215 QLD, Australia; Gerben_keijzers{at}health.qld.gov.au

Abstract

Objective To create a clinical decision tool for suspected influenza A (including 2009 H1N1) to facilitate treatment and isolation decisions for patients admitted to hospital with an acute respiratory illness from the emergency department (ED) during a 2009 H1N1 pandemic.

Methods Cross-sectional study conducted in two hospitals in Queensland, Australia. All patients admitted to hospital from the ED between 24 May and 16 August 2009 with an acute respiratory illness were included. All had nasal and throat swabs taken. Data were collected from clinical chart review regarding clinical symptoms, co-morbidities, examination findings, pathology and radiology results. Influenza A status was detected by reverse transcription–PCR assay. Univariate and multivariate regression analyses were performed to identify independent predictors of influenza A status.

Results 346 consecutive patients were identified, of which 106 were positive for 2009 H1N1 influenza; an additional 11 patients were positive for other influenza A viruses. Independent clinical predictors (with points allocated using weighted scoring) for all types of influenza A in patients admitted with acute respiratory illness were: age 18–64 years (2 points); history of fever (2); cough (1); normal level of consciousness (2); C-reactive protein >5 and ≤100 mg/l (2) and normal leucocyte count (1). A clinical score of 5 (presence of two or three predictors) gave a sensitivity of 93% (95% CI 87% to 96%), specificity of 36% (95% CI 30% to 42%), resulting in a negative-predictive value of 91% (95% CI 83% to 95%).

Conclusion A clinical prediction tool was developed that may be able to assist in making appropriate isolation decisions during future 2009 H1N1 outbreaks.

  • Clinical assessment
  • epidemiology
  • infection control
  • infectious diseases
  • influenza A virus (H1N1 subtype)
  • influenza human/diagnosis
  • research
  • respiratory
  • viral

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Footnotes

  • Competing interests None.

  • Ethics approval This study was conducted with the approval of the Gold Coast Health District Human Research and Ethics Committee.

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

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