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Chinese Journal of Contemporary Pediatrics ; (12): 435-439, 2015.
Artigo em Chinês | WPRIM | ID: wpr-346132

RESUMO

<p><b>OBJECTIVE</b>To study the diagnostic value and influencing factors for amplitude-integrated EEG (aEEG) in brain injury in preterm infants.</p><p><b>METHODS</b>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.</p><p><b>RESULTS</b>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).</p><p><b>CONCLUSIONS</b>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.</p>


Assuntos
Feminino , Humanos , Recém-Nascido , Gravidez , Peso ao Nascer , Lesões Encefálicas , Diagnóstico , Eletroencefalografia , Recém-Nascido Prematuro , Modelos Logísticos , Fatores de Risco
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