Predicting the course of early onset neonatal sepsis in pretern infants

Authors

Keywords:

early onset neonatal sepsis, predicting, sTREM-1, pretern infants

Abstract

Early onset neonatal sepsis (EONS) remains the main cause of morbidity and mortality, especially among prematern infants. Therefore, development and practical application of effective model of EONS adverse effects prediction is a priority area for improvement of medical aid quality for this category of infants.
The purpose. Improvement of care for prematurely born babies with EONS based on determination of predictive properties of sTREM-1 serum level and development of effective comprehensive algorithm for adverse effects prediction.
Materials and methods. Analysis of clinical laboratory observations for 42 newborns of gestational age 26–36 weeks (33 infants with EONS without shock and 9 infants with septic shock and/or death) with determination of serum content of sTREM-1 was carried out. Rank structures of indices were set and a prediction model was developed, when using Wald–Genkin heterogeneous sequential procedure.
Results. Newborns with shock and/or death had elevated sTREM-1 serum level >125.1 pg/ml. When developing a model of EONS adverse effects prediction, it was established that the highest predictive value is characteristic for sTREM-1 (I=3.03) and leukocytal intoxication index (I=2.97).
Conclusions. It was determined that the serum content of sTREM-1 in newborns with EONS >125.1 pg/ml in the 1st 24 hours of life is associated with further development of shock and/or death. High (>95.5%) reliability of the developed predictive multi-marker algorithm allows to recommend it for clinical use.
The research was carried out in accordance with the principles of the Helsinki Declaration. The study protocol was approved by the Local Ethics Committee of all participating institution. The informed consent of the patient was obtained for conducting the studies.

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