Validation of a Risk Stratification Tool among Full-term Neonates with Suspicion of Invasive Bacterial Infections

Abstract

Context: The emergence of neonatal invasive bacterial infections (IBIs) poses a formidable challenge to health-care providers worldwide. The combination of nonspecific clinical symptoms, in addition to the absence of an acceptable sensitive test, resembles a dilemma for clinicians to diagnose or safely rule out the presence of infections. A newly developed tool by Chen et al. stratifies the risk of full-term neonates suspected of IBI. This model works by identifying neonates who need immediate antibiotic treatment from those who only need observational and continuous reassessment. Aims: The purpose of the study was to validate Chen et al.’s risk stratification tool. Settings and Design: This is a retrospective cohort study. Subjects and Methods: The following parameters are required to utilize this tool: ill appearance, abnormal neurological signs, age at admission, white blood cell, neutrophil percentage, C-reactive protein, and procalcitonin (PCT). Statistical Analysis Used: Data management and analysis were carried out using SPSS version 25. Results: Out of 768 neonates screened for IBIs, we identified 100 babies suspected of IBI regardless of PCT availability. Out of those, 30 neonates were eligible to be entered into the calculator and used for the validation process. The number of neonates who had IBIs was found to be 14 babies. Neonatal IBI incidence in full-term babies was estimated to be 0.79/1000 live births. Specificity, negative predictive value, and accuracy of the validated tool were reported as 82.14% (95% confidence interval [CI]: 63.11%–93.94%), 99.9% (95% CI: 99.88%–99.91%), and 82.07% (95% CI: 63.81%–93.59%), respectively. Conclusions: Overall, the tool demonstrated a poor outcome in terms of detecting those with IBI but excellent outcomes in identifying healthy babies.