Fatores perinatais associados a anormalidades no traçado do eletroencefalograma de amplitude integrada em prematuros no primeiro dia de vida

• Autor(a) principal: Castro, Junia Sampel de [UNIFESP]
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UNIFESP
• Texto Completo: https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=4265795; http://repositorio.unifesp.br/handle/11600/46717
• topic: Electroencephalography; Preterm newborn; Neonatal intensive care unity; Eletroencefalografia; Recém-nascido prematuro; Terapia intensiva neonatal

Introduction: Given the growing concern about the neurological morbidities that premature infants are subject, to monitoring of brain electrical activity has gained ground in clinical practice; however, there are still gaps in knowledge about the factors that can influence brain function of preterm newborn infants on the first day of life. Objective: To evaluate the association between perinatal factors and abnormalities on electroencephalography amplitude-integrated (aEEG) in preterm newborn infants on the first day of life. Methods: Cross-sectional study with prospective data collection of 60 preterm infants with gestational age between 230/7-326/7 weeks, without malformations. The preterm infants were monitored by aEEG (Olympic CFM 6000, Natus®) for 3-24 hours on the first day of life with biparietal hydrogel electrodes applied in P3-P4 position. The tracings were recorded and analyzed in each record column for the presence of burst-suppression pattern, sleep-wake cycle and amplitude of the lower margin <3mV or <5mV. The association of perinatal factors (maternal complications, mode of delivery, neonatal demographic characteristics, resuscitation procedures, hypothermia on admission and SNAPPE II score) with modifications in aEEG was assessed by multiple logistic regression,using the independent variables which in the univariate analysis show p <0.20, excluded one by one if p> 0.05. At each stage, the model adjustment was assessed by the Hosmer-Lemeshow test. For the dependent variables "presence burst suppression pattern" and "presence of lower margin <3mV" noted the existence of collinearity between the variables "need for positive pressure ventilation in the delivery room" and "intubation in the delivery room" and it was decided to create two distinct models for each collinear independent variables. The results were described as odds ratio (OR) and its 95% confidence interval (95% CI). SPSS 19.0 software was used. Results: 60 preterm infants were studied with mean gestational age of 28.5±2.4 weeks, birth weight 1045 ± 369g, 55% male sex. The aEEG was installed on average 12 hours of life. Preterm infants were monitored for an average of 21 hours and 85% of this period there were appropriate tracing that allowed the analysis of the characteristics of brain neurological activity. The discontinuous pattern occurred in 65% of preterm infants and the continuous pattern in 23%. The burst-suppression pattern was associated with vaginal delivery (OR 7,6; 95%CI 1,1-53,1; p=0,041) and clinical severity of preterm infants detected by SNAPPE II ?40 (OR 13,1; 95%CI 1,8-95,1; p=0,011). The lower margin of the aEEG<3mV was also associated with the clinical severity of the newborn (OR 10,6; 95%CI 2,3-49,2; p=0,003), while its value <5mV was associated with lower gestational age (OR 0,51; 95%CI 0,34-0,761; p=0,001) and male sex (OR 4,03; 95%CI 0,96-16,04; p=0,057). There was no association between perinatal variables and absence of sleep-wake cycle in aEEG on the first day of life. Conclusion: Biological variables of preterm infants and their clinical severity are associated with electroencephalographic tracings characteristics on the first day of life and should be considered in clinical practice when aEEG is monitored.