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早期振幅整合脑电图与神经检查的预测价值。

Predictive value of an early amplitude integrated electroencephalogram and neurologic examination.

机构信息

Department of Pediatrics, Wayne State University, Detroit, Michigan, USA.

出版信息

Pediatrics. 2011 Jul;128(1):e112-20. doi: 10.1542/peds.2010-2036. Epub 2011 Jun 13.

Abstract

OBJECTIVE

To examine the predictive validity of the amplitude integrated electroencephalogram (aEEG) and stage of encephalopathy among infants with hypoxic-ischemic encephalopathy (HIE) eligible for therapeutic whole-body hypothermia.

DESIGN

Neonates were eligible for this prospective study if moderate or severe HIE occurred at <6 hours and an aEEG was obtained at <9 hours of age. The primary outcome was death or moderate/severe disability at 18 months.

RESULTS

There were 108 infants (71 with moderate HIE and 37 with severe HIE) enrolled in the study. aEEG findings were categorized as normal, with continuous normal voltage (n=12) or discontinuous normal voltage (n=12), or abnormal, with burst suppression (n=22), continuous low voltage (n=26), or flat tracing (n=36). At 18 months, 53 infants (49%) experienced death or disability. Severe HIE and an abnormal aEEG were related to the primary outcome with univariate analysis, whereas severe HIE alone was predictive of outcome with multivariate analysis. Addition of aEEG pattern to HIE stage did not add to the predictive value of the model; the area under the curve changed from 0.72 to 0.75 (P=.19).

CONCLUSIONS

The aEEG background pattern did not significantly enhance the value of the stage of encephalopathy at study entry in predicting death and disability among infants with HIE.

摘要

目的

探讨振幅整合脑电图(aEEG)与缺氧缺血性脑病(HIE)患儿脑病分期对接受全身亚低温治疗的 HIE 患儿的预测价值。

设计

本前瞻性研究纳入生后<6 小时且<9 小时进行 aEEG 检查的中重度 HIE 患儿。主要结局为 18 月龄时死亡或中重度残疾。

结果

共 108 例患儿(71 例中重度 HIE,37 例重度 HIE)入组,aEEG 表现为正常(连续正常电压 12 例,间断正常电压 12 例)、异常(爆发抑制 22 例,连续低电压 26 例,平坦波 36 例)。18 月龄时,53 例(49%)患儿死亡或残疾。单因素分析显示重度 HIE 和异常 aEEG 与主要结局相关,多因素分析显示仅重度 HIE 与结局相关。将 aEEG 模式加入 HIE 分期并未增加模型的预测价值,曲线下面积由 0.72 增加至 0.75(P=.19)。

结论

在预测 HIE 患儿死亡和残疾风险方面,aEEG 背景模式不能显著提高入组时脑病分期的预测价值。

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