Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research

Pediatr Res. 2022 Jan;91(2):368-379. doi: 10.1038/s41390-021-01721-1. Epub 2021 Sep 8.

Abstract

Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. IMPACT: This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.

Publication types

  • Review

MeSH terms

  • Anti-Bacterial Agents / therapeutic use
  • Humans
  • Infant, Newborn
  • Infant, Premature*
  • Intensive Care Units, Neonatal
  • Neonatal Sepsis / drug therapy
  • Neonatal Sepsis / physiopathology*

Substances

  • Anti-Bacterial Agents