ArticleFrontiers in pediatrics2026
Construction and validation of a risk prediction model for early acute kidney injury in asphyxiated neonates.
Article in Frontiers in pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Optimized ensemble learning framework for neonatal asphyxia prediction using perinatal clinical features.Frontiers in public health · 2026Article
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Authors and funding
8 authors.
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Abstract
Objective: This study aims to construct a prediction model based on the Naive Bayes classifier to predict the risk of acute kidney injury (AKI) in asphyxiated neonates in the early stage. Methods: The subjects were 79 asphyxiated neonates born and treated at Hospital from September 2022 to December 2024. By collecting clinical data, measuring renal tissue oxygen saturation (RrSO Results: The model achieved an accuracy of 0.929, sensitivity of 0.889, and specificity of 1.000 on the training set; on the testing set, it achieved an accuracy of 0.826, sensitivity of 0.846, and specificity of 0.800. Conclusions: The study shows that this model can provide a reliable reference for the early assessment of AKI risk in clinical practice, thus helping improve the prognosis of asphyxiated neonates. Future research needs to expand the sample size and conduct multicenter validation to further optimize the model.
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