PREDICTION OF ADVERSE OUTCOMES IN HYPOXIC-ISCHEMIC ENCEPHALOPATHY IN TERM NEWBORNS

Authors:

Abstract:

The purpose of the study was to identify and predict adverse outcomes in term neonates diagnosed with hypoxic-ischemic encephalopathy a total of 120 children, aged from birth to one year. The study cohort was divided into two groups: the main group (90 patients with hypoxic-ischemic encephalopathy), and the control group (30 healthy children without a history of asphyxia). To develop a predictive model, logistic regression analysis was employed, a robust statistical method designed to explore and quantify the relationships between dependent and independent variables. A total of 67 independent variables (predictors) were identified, encompassing anamnestic, clinical, and laboratory-instrumental parameters. Using multiple variable selection methods (Enter, Forward, Backward, and Wald-based approaches), we identified key predictors that contribute significantly to the prognosis of these neonates. The high classification accuracy achieved across all methods (ranging from 93.3 % to 96.7 %) demonstrates its potential in clinical settings for predicting neonatal outcomes.

Keywords:

neonates hypoxic-ischemic encephalopathy predictive model logistic regression analysis outcomes

References:

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Publication:

«World of Medicine and Biology» Vol. 21 No. 91 (2025) , с. 90-96
УДК 616.831-002-005.4(075.8).

DOI:

https://doi.org/10.26724/2079-8334-2025-1-91-90-96