振幅整合脑电图对早产儿脑损伤的诊断价值及其影响因素

Diagnostic value and influencing factors for amplitude-integrated EEG in brain injury in preterm infants

摘要:

目的 探讨振幅整合脑电图(aEEG)对早产儿脑损伤(BIPI)的诊断价值及其影响因素。方法 将116例胎龄27~36⁺⁶周早产儿纳入研究, 对所有早产儿生后 6 h 内aEEG进行评分; 依据BIPI诊断结果将116例早产儿分为BIPI组(n=63)和非BIPI组(n=53), 采用logistic回归分析对导致BIPI发生的危险因素进行评估; 依据aEEG检测结果再将116例早产儿分为aEEG正常组(n=58)和aEEG异常组(n=58), 对影响早产儿aEEG结果的因素行单因素分析。结果 BIPI组中aEEG异常52 例(83%); 非BIPI组中aEEG 异常6例(11%), 两组aEEG异常率比较差异有统计学意义(P<0.05)。将早产儿依据胎龄27~33⁺⁶周和34~36⁺⁶周进行划分, BIPI组aEEG评分明显低于同胎龄非BIPI组(P<0.01)。Logistic回归分析显示：小胎龄(<32周)、低出生体重(<1 500 g)、胎盘胎膜及脐带异常和母孕期高血压是导致BIPI发生的高危因素(P<0.05)。aEEG异常组与aEEG正常组在胎龄、出生体重、胎盘胎膜及脐带异常和母孕期高血压4方面比较差异有统计学意义(P<0.05)。结论 导致BIPI发生的危险因素与影响早产儿aEEG结果的因素相一致, 提示aEEG有助于BIPI的早期诊断。

Abstract:

Objective To study the diagnostic value and influencing factors for amplitude-integrated EEG (aEEG) in brain injury in preterm infants. Methods One hundred and sixteen preterm infants with a gestational age (GA) between 27 weeks and 36⁺⁶ weeks were enrolled as subjects. The aEEG scores of all preterm infants were obtained within 6 hours after birth. According to the diagnostic results, the 116 preterm infants were divided into two groups: brain injury (n=63) and non-brain injury (n=53). The risk factors for brain injury were evaluated using logistic regression analysis. According to the aEEG results, the 116 preterm infants were divided into two groups: normal aEEG (n=58) and abnormal aEEG (n=58). The influencing factors for aEEG results in preterm infants were determined using univariate analysis.Results The brain injury group had a significantly higher rate of abnormal aEEG than the non-brain injury group (83% vs 11%; P<0.05). The infants in the brain injury group from two different GA subgroups (27-33⁺⁶ weeks and 34-36⁺⁶ weeks) had significantly lower aEEG scores than the non-brain injury group from corresponding GA subgroups (P<0.01). Logistic regression analysis showed that low GA (<32 weeks), low birth weight (<1 500 g), abnormal placenta, fetal membranes, and umbilical cord, and hypertension during pregnancy were high-risk factors for brain injury (P<0.05). There were significant differences in GA, birth weight, abnormal placenta, fetal membranes, and umbilical cord, and hypertension during pregnancy between the normal and abnormal aEEG groups (P<0.05). Conclusions The risk factors for brain injury are consistent with the influencing factors for aEEG results in preterm infants, suggesting that aEEG contributes to the early diagnosis of brain injury.