Objective To explore the influencing factors of brain injury in preterm infants with bronchopulmonary dysplasia(BPD)and to construct and validate a nomogram prediction model,in order to provide guidance for reducing brain injury and improving prognosis in preterm infants with BPD.Methods Ninety-eight premature infants with BPD who were delivered from July 2021 to July 2023 in Changzhou Maternal and Child Health Hospital were retrospectively analyzed.According to whether the children had brain injury,they were divided into brain injury group(30 cases)and non-brain injury group(68 cases).The factors affecting brain injury were analyzed,based on which a nomogram model was constructed to predict the risk of brain injury in the infants.The area under receiver operating characteristic(ROC)curve(AUC)was used to assess the predictive efficacy of the model.Results There was no difference in the sex composition,corrected gestational age,modes of delivery,number of fetuses,and proportions of pregnancy-induced hypertension,gestational diabetes mellitus,premature rupture of membranes,amniotic fluid contamination,septicemia,and hearing impairment between the two groups(P＞0.05).The gestational age and the birth weight in the brain injury group were lower than those in the non-brain injury group(P＜0.05).The proportions of 5-minute Apgar score＜7,duration of mechanical ventilation ≥ 7 d,metabolic acidosis and neonatal infections in the brain injury group were all higher than those in the non-brain injury group(P＜0.05).Multivariable Logistic regression analysis showed that high 5-minute Apgar score[OR=0.243,(95％CI:0.119,0.494)]was a protective factor for brain injury in neonates(P＜0.05).Long duration of mechanical ventilation[OR=3.567,(95％CI:1.622,7.843)]and neonatal infection[OR=5.339,(95％CI:2.662,10.706)]were risk factors for brain injury in neonates(P＜0.05).The verification of the nomogram prediction model constructed based on the above influencing factors by the Bootstrap method demonstrated that the C-index was 0.832(95％CI:0.787,0.925),suggestive of great discrimination of the model.The ROC curve analysis revealed that the sensitivity of the nomogram prediction model for SBI was 85.20％(95％CI:0.556,0.889),with a specificity of 88.70％(95％CI:0.620,0.915)and an AUC of 0.872(95％CI:0.77,0.957),indicating good predictive performance of the model.Conclusion High 5-minute Apgar score is an independent protective factor while long duration of mechanical ventilation and neonatal infection are independent risk factors for brain injury in preterm infants with BPD.The nomogram prediction model based on the above indicators can effectively assess the risk of brain injury in the neonates.
bronchopulmonary dysplasiabrain injurypreterm infantsinfluencing factorsnomogramprediction model
维普
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