Persistent candidemia in very low birth weight neonates: risk factors and clinical significance

BMC Infect Dis. 2018 Nov 12;18(1):558. doi: 10.1186/s12879-018-3487-9.

Abstract

Background: The prevalence and risk factors for persistent candidemia among very low birth weight infants are poorly understood. This study aimed to investigate the epidemiology of persistent candidemia over a 4-year period in a neonatal intensive care unit (NICU) in Liuzhou, China.

Methods: We retrospectively extracted demographic data, risk factors, microbiological results and outcomes of very low birth weight infants with candidemia in our hospital between January 2012 and November 2015. Persistent candidemia was defined as a positive blood culture for > 5 days. Logistic regression was used to identify risk factors associated with persistent candidemia.

Results: Of 48 neonates with candidemia, 28 had persistent candidemia. Both mechanical ventilation and intubation were significantly associated with increased rates of persistent candidemia (P = 0.044 and 0.004, respectively). The case fatality rate for the persistent candidemia group was 14.3%.

Conclusion: The rate of persistent candidemia was high among very low birth weight neonates. Mechanical ventilation and intubation were the major factors associated with the development of persistent candidemia. This study highlights the importance of intensive prevention and effective treatment among neonates with persistent candidemia.

Keywords: Epidemiology; Neonates; Persistent candidemia; Very low birth weight.

MeSH terms

  • Candidemia / epidemiology*
  • China / epidemiology
  • Cross Infection / epidemiology
  • Female
  • Hospitals
  • Humans
  • Infant
  • Infant, Newborn
  • Infant, Newborn, Diseases / epidemiology*
  • Infant, Very Low Birth Weight*
  • Intensive Care Units, Neonatal / statistics & numerical data
  • Intubation / adverse effects
  • Intubation / statistics & numerical data
  • Male
  • Prevalence
  • Respiration, Artificial / adverse effects
  • Respiration, Artificial / standards
  • Respiration, Artificial / statistics & numerical data
  • Retrospective Studies
  • Risk Factors