ABSTRACT
INTRODUCTION: Diagnosing neonatal sepsis is heavily dependent on clinical phenotyping as culture-positive body fluid has poor sensitivity, and existing blood biomarkers have poor specificity.A combination of machine learning, statistical and deep pathway biology analyses led to the identification of a tripartite panel of biologically connected immune and metabolic markers that showed greater than 99% accuracy for detecting bacterial infection with 100% sensitivity. The cohort study described here is designed as a large-scale clinical validation of this previous work. METHODS AND ANALYSIS: This multicentre observational study will prospectively recruit a total of 1445 newborn infants (all gestations)-1084 with suspected early-or late-onset sepsis, and 361 controls-over 4 years. A small volume of whole blood will be collected from infants with suspected sepsis at the time of presentation. This sample will be used for integrated transcriptomic, lipidomic and targeted proteomics profiling. In addition, a subset of samples will be subjected to cellular phenotype and proteomic analyses. A second sample from the same patient will be collected at 24 hours, with an opportunistic sampling for stool culture. For control infants, only one set of blood and stool sample will be collected to coincide with clinical blood sampling. Along with detailed clinical information, blood and stool samples will be analysed and the information will be used to identify and validate the efficacy of immune-metabolic networks in the diagnosis of bacterial neonatal sepsis and to identify new host biomarkers for viral sepsis. ETHICS AND DISSEMINATION: The study has received research ethics committee approval from the Wales Research Ethics Committee 2 (reference 19/WA/0008) and operational approval from Health and Care Research Wales. Submission of study results for publication will involve making available all anonymised primary and processed data on public repository sites. TRIAL REGISTRATION NUMBER: NCT03777670.
Subject(s)
Neonatal Sepsis , Sepsis , Humans , Biomarkers , Cohort Studies , Multicenter Studies as Topic , Neonatal Sepsis/diagnosis , Neonatal Sepsis/microbiology , Observational Studies as Topic , Prospective Studies , ProteomicsABSTRACT
OBJECTIVE: To determine the usefulness of measures, available shortly after birth, as predictors of hypoxic-ischemic encephalopathy (HIE) following perinatal asphyxia. PATIENTS: All inborn patients at Southmead Hospital between January 2012 and March 2014 at ≥36 weeks gestation with a pH <7 or BE >16 on cord or baby's blood within one hour of birth or 10-minute Apgar score ≤5 or requiring intermittent positive pressure ventilation at 10 minutes were eligible for inclusion. METHODS: ROC curves were derived for the perinatal clinical and biochemical measures to establish their predictive values for the development of HIE and the area under the curve (AUC) used as the measure of prediction. RESULTS: We identified 79 eligible babies. Infants qualifying for therapeutic hypothermia (TH) based on aEEG abnormalities were considered to have HIE (n = 13; 16.5%), whereas babies with normal aEEG were classified as "non-HIE" (n = 66; 83.5%). The highest AUC measure was associated with the five-minute Apgar score (0.89 (0.79-0.99)). Troponin T (0.81 (0.64-0.98)) and ALT (0.78 (0.60-96)) also showed high values. CONCLUSIONS: In this work, the Apgar score, troponin T and ALT were found to be strong and useful predictors of HIE.
