Specific Aim 1: Develop a predictive model of neonatal infection based upon the expression profile of six salivary inflammatory biomarkers, CRP, procalcitonin, tumor necrosis factor-alpha (TNF-α), and interleukins (IL) 1β, 6, and 8, within the first 36 hours of treatment. Serial saliva samples collected at the initiation of antibiotic therapy and 18-36 hours into treatment from 2,250 neonatal 'rule out sepsis' evaluations will undergo multiplexed quantification of the six salivary inflammatory biomarkers. Diagnostic accuracy will be calculated and predictive models will be developed, incorporating clinical, demographic, and biomarker data.~Specific Aim 2: Validate the predictive model of neonatal infection developed in Aim 1 on an external cohort of newborns. Serial saliva samples from an additional, prospective cohort of 1,750 infants undergoing a 'rule out sepsis' evaluation will be collected to test the validity of the predictive model for neonatal infection.~Specific Aim 3: Establish normative salivary reference ranges of the inflammatory biomarkers across varying gestational ages and weights, and assess the potential of these biomarkers to predict other neonatal morbidities. Salivary samples from the subset of uninfected newborns from Aims 1 and 2 will be combined and used to establish the 95% reference intervals of the salivary inflammatory biomarkers at each time point. Salivary profiles will be correlated to discharge diagnoses (i.e. bronchopulmonary dysplasia, periventricular leukomalacia) to assess the ability of each biomarker, alone and in combination, to predict neonatal morbidities known or hypothesized to be associated with an inflammatory response.
The aim of this study is to develop a faster, safer, and more accurate method for determining if a newborn has an infection. This study involves analyzing saliva for markers of infection and inflammation known as cytokines. We will analyze infant's saliva repeatedly for inflammatory biomarkers (cytokines) within the first 36 hours of their standard of care treatment. We hypothesize that levels of these cytokines will more quickly predict which babies are truly infected and which babies are not compared to the blood tests currently being used.