ArticleFrontiers in human neuroscience2020
Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage.
Article in Frontiers in human neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Two risk assessment models for predicting white matter injury in extremely preterm infants.Pediatric research · 2025Observational
- Dynamic Nomogram for Predicting the Fall Risk of Stroke Patients: An Observational Study.Clinical interventions in aging · 2025Observational
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9 authors.
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Abstract
purposeWhite matter damage (WMD) was defined as the appearance of rough and uneven echo enhancement in the white matter around the ventricle. The aim of this study was to develop and validate a risk prediction model for neonatal WMD. MATERIALS AND
methodsWe collected data for 1,733 infants hospitalized at the Department of Neonatology at The First Affiliated Hospital of Zhengzhou University from 2017 to 2020. Infants were randomly assigned to training (
resultsWe identified four variables as independent risk factors for brain WMD in neonates by multivariate logistic regression and LASSO analysis, including gestational age, fetal distress, prelabor rupture of membranes, and use of corticosteroids. These were used to establish a risk prediction nomogram and web-based calculator (https://caowenjun.shinyapps.io/dynnomapp/). The C-index of the training and validation sets was 0.898 (95% confidence interval: 0.8745-0.9215) and 0.887 (95% confidence interval: 0.8478-0.9262), respectively. Decision tree analysis showed that the model was highly effective in the threshold range of 1-61%. The sensitivity and specificity of the model were 82.5 and 81.7%, respectively, and the cutoff value was 0.099.
conclusionThis is the first study describing the use of a nomogram and web-based calculator to predict the risk of WMD in neonates. The web-based calculator increases the applicability of the predictive model and is a convenient tool for doctors at primary hospitals and outpatient clinics, family doctors, and even parents to identify high-risk births early on and implementing appropriate interventions while avoiding excessive treatment of low-risk patients.
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