The need for strengthening the influenza virus detection ability of hospital clinical laboratories: an investigation of the 2009 pandemic

Sci Rep. 2017 Mar 10:7:43433. doi: 10.1038/srep43433.

Abstract

Most hospital clinical laboratories (HCLs) in China are unable to perform influenza virus detection. It remains unclear whether the influenza detection ability of HCLs influences the early identification and mortality rate of influenza. A total of 739 hospitalized patients with 2009 influenza A (H1N1) virus treated at 65 hospitals between May and December, 2009, in Zhejiang, China, were included based on identifications by HCLs and by public health laboratories (PHLs) of the Centers for Disease Control and Prevention. Of the patients, 407 (55.1%) were male, 17 died, resulting in an in-hospital mortality rate of 2.3%, and 297 patients were identified by HCLs and 442 by PHLs. The results indicated that a 24-hour delay in identification led to a 13% increase in the odds of death (OR = 1.13, P < 0.05). The time between onset and identification (3.9 days) of the HCL cohort was significantly shorter than that of the PHL cohort (4.8 days). The in-hospital mortality rate of the HCL group was significantly lower than that of the PHL group (1.0% vs. 3.2%, P < 0.05). HCL-based detection decreased the in-hospital mortality rate by 68.8%. HCL-based influenza virus detection facilitated early identification and reduced influenza mortality, and influenza detection ability of HCLs should be strengthened.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • China / epidemiology
  • Clinical Laboratory Services / organization & administration*
  • Delayed Diagnosis
  • Female
  • Hospital Mortality
  • Hospitalization / statistics & numerical data
  • Hospitals
  • Humans
  • Influenza A Virus, H1N1 Subtype / isolation & purification*
  • Influenza, Human / diagnosis*
  • Influenza, Human / epidemiology*
  • Influenza, Human / mortality
  • Influenza, Human / virology
  • Laboratories
  • Male
  • Middle Aged
  • Odds Ratio
  • Pandemics*
  • Public Health*