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Predictive Symptoms and Signs of Laboratory-confirmed Influenza

  • Jeng How Yang
  • , Po Yen Huang
  • , Shian Sen Shie
  • , Shuan Yang
  • , Kuo Chien Tsao
  • , Tsu Lan Wu
  • , Hsieh Shong Leu
  • , Ching Tai Huang*
  • *Corresponding author for this work
  • Chang Gung Memorial Hospital
  • Chang Gung University

Research output: Contribution to journalJournal Article peer-review

32 Scopus citations

Abstract

Influenza infection poses annual threats and leads to significant morbidity and mortality. Early diagnosis is the key to successful treatment. Laboratory-based diagnosis has various limitations. Diagnosis based on symptoms or signs is still indispensable in clinical practice. We investigated the symptoms or signs associated with laboratory-confirmed influenza. A prospective study across 2 influenza seasons was performed from June 2010 to June 2012 at 2 branches (Taipei and Lin-Kou) of Chang Gung Memorial Hospital. Patients who visited outpatient clinics with suspected acute respiratory tract infection were sampled by throat swab or nasopharyngeal swab. RT-PCR and/or virus culture were used as a reference standard. We used logistic regression to identify the symptoms or signs associated with laboratory-confirmed influenza infection. We also evaluated the performance metrics of different influenza-like illness used in Taiwan, the USA, and WHO. A total of 158 patients were included in the study. The prevalence of influenza infection was 45% (71/158). Fever, cough, rhinorrhea, sneezing, and nasal congestion were significant predictors for influenza infection. Whereas fever + cough had a best sensitivity (86%; confidence interval [CI] 76%-93%), fever + cough and sneezing had a best specificity (77%; CI 62%-88%). Different case definitions of influenza-like illness had comparable accuracy in sensitivity and specificity. Clinical diagnosis based on symptoms and signs is useful for allocating resources, identifying those who may benefit from early antiviral therapy and providing valuable information for surveillance purpose.

Original languageEnglish
Pages (from-to)e1952
JournalMedicine (United States)
Volume94
Issue number44
DOIs
StatePublished - 01 11 2015

Bibliographical note

Publisher Copyright:
© 2015 Wolters Kluwer Health, Inc.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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