Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Biomarkers for late-onset neonatal sepsis | Polin and Randis Genome Medicine 2010 2 58 http content 2 9 58 w Genome Medicine COMMENTARY L__ Biomarkers for late-onset neonatal sepsis Richard A Polin and Tara M Randis Abstract The diagnosis of healthcare-associated infections is problematic because of the overlap between clinical signs associated with normal physiological disturbances and those of bacteremia or fungemia. Earlier diagnosis of sepsis in critically ill infants would enable timely administration of antibiotics and discontinuation of treatment in infants with a low probability of sepsis. A recent study by Ng etal. identified two novel biomarkers for late-onset neonatal sepsis the des-arginine variant of serum amyloid A and apolipoprotein C-II. These markers may be of value in the identification of neonates with bacteremia or fungemia. Background Late-onset sepsis in newborn infants is defined as sepsis occurring after the first 72 hours of life and is a major cause of infant mortality 1 . Furthermore these infections increase the length of hospital stay add millions of dollars in excess healthcare costs annually and are associated with poorer neurodevelopmental outcomes. Infants of any gestational age are susceptible to late-onset sepsis. However very low birth weight infants those weighing less than 1 500 g are particularly vulnerable because of the need for invasive monitoring impaired host defense mechanisms limited amounts of normal endogenous flora reduced barrier function of neonatal skin and frequent exposure to broad-spectrum antibiotics. Most late-onset infections in newborn infants are classified as healthcare-associated infections because they occur while these infants are receiving neonatal intensive care. The two most common presentations are catheter-associated bloodstream infections and ventilator-associated pneumonia. The diagnosis of healthcare-associated infections is problematic because of the overlap between clinical signs associated with normal .
