Predicting influenza A and 2009 H1N1 influenza in patients admitted to hospital with acute respiratory illness

Gerben B. Keijzers, Caleb Nathaniel Kai Lik Vossen, Ping Zhang, Debourough MacBeth, Petra Derrington, John Gregory Gerrard, Jenny Doust

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4 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)500-506
Number of pages7
JournalEmergency Medicine Journal
Volume28
Issue number6
DOIs
Publication statusPublished - Jun 2011

Fingerprint

Human Influenza
Hospital Emergency Service
Patient Isolation
Queensland
Hospital Departments
Influenza A virus
Pandemics
Pharynx
Consciousness
Leukocyte Count
Nose
Cough
Radiology
C-Reactive Protein
Reverse Transcription
Disease Outbreaks
Fever
Multivariate Analysis
Cross-Sectional Studies
Regression Analysis

Cite this

Keijzers, Gerben B. ; Vossen, Caleb Nathaniel Kai Lik ; Zhang, Ping ; MacBeth, Debourough ; Derrington, Petra ; Gerrard, John Gregory ; Doust, Jenny. / Predicting influenza A and 2009 H1N1 influenza in patients admitted to hospital with acute respiratory illness. In: Emergency Medicine Journal. 2011 ; Vol. 28, No. 6. pp. 500-506.
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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.",
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Predicting influenza A and 2009 H1N1 influenza in patients admitted to hospital with acute respiratory illness. / Keijzers, Gerben B.; Vossen, Caleb Nathaniel Kai Lik; Zhang, Ping; MacBeth, Debourough; Derrington, Petra; Gerrard, John Gregory; Doust, Jenny.

In: Emergency Medicine Journal, Vol. 28, No. 6, 06.2011, p. 500-506.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Vossen, Caleb Nathaniel Kai Lik

AU - Zhang, Ping

AU - MacBeth, Debourough

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AU - Gerrard, John Gregory

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N2 - 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.

AB - 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.

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