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目的探讨振幅整合脑电图(a EEG)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6h内a EEG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a EEG检测结果再将116例早产儿分为a EEG正常组(n=58)和a EEG异常组(n=58),对影响早产儿a EEG结果的因素行单因素分析。结果 BIPI组中a EEG异常52例(83%);非BIPI组中a EEG异常6例(11%),两组a EEG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a EEG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(<1500g)、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)。a EEG异常组与a EEG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a EEG结果的因素相一致,提示a EEG有助于BIPI的早期诊断。
Objective To investigate the diagnostic value and influencing factors of amplitude integrated electroencephalogram (EEG) in premature infants with brain injury (BIPI). Methods A total of 116 preterm infants with gestational age of 27-36 + 6 weeks were enrolled in the study. All EEGs were measured within 6 hours after birth in preterm infants. One hundred and sixteen preterm infants were divided into BIPI group (n = 63) and non-infants BIPI group (n = 53). The risk factors leading to BIPI were evaluated by logistic regression analysis. Based on the results of a EEG test, 116 preterm infants were further divided into a normal EEG group (n = 58) and an abnormal EEG group n = 58). Univariate analysis was performed on the factors affecting the results of a EEG in preterm infants. Results There were 52 cases (83%) of abnormal EEG in BIPI group and 6 cases (11%) of abnormal EEG in non-BIPI group. There was significant difference in abnormal rate of EEG between the two groups (P <0.05). Preterm infants were divided according to gestational age from 27 to 33 + 6 weeks and 34 to 36 + 6 weeks. The EEG score of BIPI group was significantly lower than that of non - BIPI group (P <0.01). Logistic regression analysis showed that high risk factors for BIPI (P <0.05) were the small gestational age (<32 weeks), low birth weight (<1500g), abnormalities of placenta fetal membranes and umbilical cord blood and hypertension during pregnancy. There were significant differences in gestational age, birth weight, placental membranes, umbilical cord abnormalities and gestational hypertension between a group of EEG abnormalities and a group of normal EEG (P <0.05). Conclusions The risk factors leading to BIPI are consistent with the factors affecting the results of a EEG in preterm infants, suggesting that aEEG is helpful for the early diagnosis of BIPI.