Abstract
BackgroundNonspecific clinical signs and suboptimal diagnostic tests limit accurate identification of late onset sepsis (LOS) and necrotizing enterocolitis (NEC) in premature infants, resulting in significant morbidity and antibiotic overuse. An infant's systemic inflammatory response may be identified earlier than clinical suspicion through analysis of multiple vital signs by a computerized algorithm (RALIS). AimTo evaluate the revised RALIS algorithm for detection of LOS and NEC in preterm infants. MethodsIn this nested case–control study, VS data (heart rate, respiratory rate, temperature, desaturations, bradycardias) were extracted from medical records of infants 23–32 weeks gestation. RALIS generated an output, with score ≥ 5 triggering an alert. Patient episodes were classified based on culture, radiograph, and antibiotic data into categories: LOS, expanded LOS, NEC, and controls. Paired t-tests, linear regression and cross-validation analyses were used to evaluate the relationship between RALIS alert and LOS/NEC. ResultsAmong 155 infants with 161 episodes, there were 41 expanded LOS (+blood, CSF, urine, respiratory culture), 31 LOS (+blood, CSF, urine), 9 NEC, and 93 controls. RALIS alert was 43.1 ± 79 h before culture in LOS (p = .012). There was a significant association between RALIS alert and LOS/NEC (β = 0.72, p < .0001). Sensitivity and specificity for LOS/NEC were 84% and 80%, (PPV = 63%; NPV = 93%). The regression model demonstrated an AUC of 89.9%. ConclusionsFor infants ≤32 weeks, RALIS detects systemic inflammatory responses in LOS and NEC in the first month of life. The algorithm can identify infection earlier than clinical suspicion, even for NEC with negative cultures. RALIS has high NPV to rule-out LOS and NEC, and may, after prospective validation, aid in antibiotic treatment decisions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.