Details

Autor(en) / Beteiligte

• Wei, Yihong
• Xu, Shuai
• Sun, Wenjuan
• Hong, Fanzhen

Titel

Development and validation of a prenatal predictive nomogram for the risk of NICU admission in infants born to Chinese mothers over 35 years of age: a retrospective cohort study

Ist Teil von

• BMC pregnancy and childbirth, 2024-05, Vol.24 (1), p.390-390, Article 390

Ort / Verlag

England: BioMed Central

Erscheinungsjahr

2024

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• The rising number of women giving birth at advanced maternal age has posed significant challenges in obstetric care in recent years, resulting in increased incidence of neonatal transfer to the Neonatal Intensive Care Unit (NICU). Therefore, identifying fetuses requiring NICU transfer before delivery is essential for guiding targeted preventive measures. This study aims to construct and validate a nomogram for predicting the prenatal risk of NICU admission in neonates born to mothers over 35 years of age. Clinical data of 4218 mothers aged ≥ 35 years who gave birth at the Department of Obstetrics of the Second Hospital of Shandong University between January 1, 2017 and December 31, 2021 were reviewed. Independent predictors were identified by multivariable logistic regression, and a predictive nomogram was subsequently constructed for the risk of neonatal NICU admission. Multivariate logistic regression demonstrated that the method of prenatal screening, number of implanted embryos, preterm premature rupture of the membranes, preeclampsia, HELLP syndrome, fetal distress, premature birth, and cause of preterm birth are independent predictors of neonatal NICU admission. Analysis of the nomogram decision curve based on these 8 independent predictors showed that the prediction model has good net benefit and clinical utility. The nomogram demonstrates favorable performance in predicting the risk of neonatal NICU transfer after delivery by mothers older than 35 years. The model serves as an accurate and effective tool for clinicians to predict NICU admission in a timely manner.