[Influence of bronchopulmonary dysplasia on cerebral blood flow in preterm infants: a prospective study based on arterial spin labeling]. / åŸºäºŽåŠ¨è„‰è‡ªæ—‹æ ‡è®°æˆåƒæŠ€æœ¯æŽ¢è®¨æ”¯æ°”ç®¡è‚ºå‘è‚²ä¸è‰¯å¯¹æ—©äº§å„¿è„‘è¡€æµé‡å½±å“çš„å‰çž»æ€§ç ”ç©¶.

OBJECTIVES: To investigate local cerebral blood perfusion in preterm infants with bronchopulmonary dysplasia (BPD) based on cerebral blood flow (CBF) values of arterial spin labeling (ASL). METHODS: A prospective study was conducted on 90 preterm infants with a gestational age of <32 weeks and a birth weight of <1 500 g who were born in the Department of Obstetrics and admitted to the Department of Neonatology in the Third Affiliated Hospital of Zhengzhou University from August 2021 to June 2022. All of the infants underwent cranial MRI and ASL at the corrected gestational age of 35-40 weeks. According to the presence or absence of BPD, they were divided into a BPD group with 45 infants and a non-BPD group with 45 infants. The two groups were compared in terms of the CBF values of the same regions of interest (frontal lobe, temporal lobe, parietal lobe, occipital lobe, thalamus, and basal ganglia) on ASL image. RESULTS: Compared with the non-BPD group, the BPD group had a significantly lower 1-minute Apgar score, a significantly longer duration of assisted ventilation, and a significantly higher incidence rate of fetal distress (P<0.05). After control for the confounding factors such as corrected age and age at the time of cranial MRI by multiple linear regression analysis, compared with the non-BPD group, the BPD group still had higher CBF values of the frontal lobe, temporal lobe, parietal lobe, occipital lobe, basal ganglia, and thalamus at both sides (P<0.05). CONCLUSIONS: BPD can increase cerebral blood perfusion in preterm infants, which might be associated with hypoxia and a long duration of assisted ventilation in the early stage.

Construction of early risk prediction models for bronchopulmonary dysplasia in preterm infants. / 早产儿支气管肺发育不良早期风险预测模型的构建.

OBJECTIVES: To construct risk prediction models for bronchopulmonary dysplasia (BPD) in preterm infants on postnatal days 3, 7, and 14. METHODS: A retrospective analysis was performed on the medical data of 414 preterm infants, with a gestational age of <32 weeks and a birth weight (BW) of <1 500 g, who were admitted to the neonatal intensive care unit from July 2019 to April 2021. According to the diagnostic criteria for BPD revised in 2018, they were divided into a BPD group with 98 infants and a non-BPD group with 316 infants. The two groups were compared in terms of general status, laboratory examination results, treatment, and complications. The logistic regression model was used to identify the variables associated with BPD. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of models. RESULTS: The logistic regression analysis showed that BW, asphyxia, grade III-IV respiratory distress syndrome (RDS), acute chorioamnionitis, interstitial pneumonia, fraction of inspired oxygen (FiO2), and respiratory support mode were the main risk factors for BPD (P<0.05). The prediction models on postnatal days 7 and 14 were established as logit (P7) =-2.049-0.004×BW (g) +0.686×asphyxia (no=0, yes=1) +1.842×grade III-IV RDS (no=0, yes=1) +0.906×acute chorioamnionitis (no=0, yes=1) +0.506×interstitial pneumonia (no=0, yes=1) +0.116×FiO2 (%) +0.816×respiratory support mode (no=0, nasal tube=1, nasal continuous positive airway pressure=2, conventional mechanical ventilation=3, high-frequency mechanical ventilation=4) and logit (P14) =-1.200-0.004×BW (g) +0.723×asphyxia+2.081×grade III-IV RDS+0.799×acute chorioamnionitis+0.601×interstitial pneumonia+0.074×FiO2 (%) +0.800×respiratory support mode, with an area under the ROC curve (AUC) of 0.876 and 0.880, respectively, which was significantly larger than the AUC of the prediction model on postnatal day 3 (P<0.05). CONCLUSIONS: BW, asphyxia, grade III-IV RDS, acute chorioamnionitis, interstitial pneumonia, FiO2, and respiratory support mode are the main risk factors for BPD and can be used to construct risk prediction models. The prediction models on postnatal days 7 and 14 can effectively predict BPD.