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Tackling Neonatal Sepsis—Can It Be Predicted?

Author

Listed:
  • Špela But

    (Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia)

  • Brigita Celar

    (Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia)

  • Petja Fister

    (Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
    Department of Paediatric Intensive Care, Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia)

Abstract

(1) Background: Early signs of sepsis in a neonate are often subtle and non-specific, the clinical course rapid and fulminant. The aim of our research was to analyse diagnostic markers for neonatal sepsis and build an application which could calculate its probability. (2) Methods: A retrospective clinical study was conducted on 497 neonates treated at the Clinical Department of Neonatology of the University Children’s Hospital in Ljubljana from 2007 to 2021. The neonates with a diagnosis of sepsis were separated based on their blood cultures, clinical and laboratory markers. The influence of perinatal factors was also observed. We trained several machine-learning models for prognosticating neonatal sepsis and used the best-performing model in our application. (3) Results: Thirteen features showed highest diagnostic importance: serum concentrations of C-reactive protein and procalcitonin, age of onset, immature neutrophil and lymphocyte percentages, leukocyte and thrombocyte counts, birth weight, gestational age, 5-min Apgar score, gender, toxic changes in neutrophils, and childbirth delivery. The created online application predicts the probability of sepsis by combining the data values of these features. (4) Conclusions: Our application combines thirteen most significant features for neonatal sepsis development and predicts the probability of sepsis in a neonate.

Suggested Citation

  • Špela But & Brigita Celar & Petja Fister, 2023. "Tackling Neonatal Sepsis—Can It Be Predicted?," IJERPH, MDPI, vol. 20(4), pages 1-13, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:3644-:d:1072896
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    References listed on IDEAS

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    1. Bogdan Mihai Neamțu & Gabriela Visa & Ionela Maniu & Maria Livia Ognean & Rubén Pérez-Elvira & Andrei Dragomir & Maria Agudo & Ciprian Radu Șofariu & Mihaela Gheonea & Antoniu Pitic & Remus Brad & Cla, 2021. "A Decision-Tree Approach to Assist in Forecasting the Outcomes of the Neonatal Brain Injury," IJERPH, MDPI, vol. 18(9), pages 1-19, April.
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