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计算机解读的胎儿脑电图。II. 1岁时神经功能异常婴儿的脑电图模式。

Computer interpreted fetal electroencephalogram. II. Patterns in infants who were neurologically abnormal at 1 year of age.

作者信息

Chik L, Sokol R J, Rosen M G, Borgstedt A D

出版信息

Am J Obstet Gynecol. 1976 Jun 15;125(4):541-4.

PMID:984090
Abstract

A computer program for pattern recognition of fetal electroencephalogram has been used to analyze the records of nine fetuses, known to be neurologically abnormal at 1 year of age. In 4,913 10 second epochs of adequate FEEG, Low Voltage Irregular (LVI) accounted for 17.8 per cent, Mixed activity (MIX) for 30.5 per cent, High Voltage Slow (HVS) for 18.1 per cent, and Trace Alternant (T/A) for 33.2 per cent of the epochs. The numbers of observed FEEG patterns in these abnormal cases appear to be significantly different from those in 11 normal cases (p less than 0.001)3. Specifically, the relative frequency of LVI was found to be increased in the abnormal cases (p congruent to 0.05). Moreover, LVI was significantly associated with visually interpreted prolonged voltage suppression (p less than 0.025) and lowered one-minute Apgar score (p congruent to 0.025). Using discriminant function analysis for LVI, MIX, HVS, and T/A patterns from FEEG recorded during labor, 10 of 11 infants were correctly classified as being neurologically normal at one year of age and 6 of 9 infants were correctly classified as being neurologically abnormal at 1 year of age. These studies confirm previous associations based on visual analysis of FEEG and suggest that the relative frequencies of FEEG patterns may be useful in the prediction of neurologic outcome 1 year later.

摘要

一种用于胎儿脑电图模式识别的计算机程序已被用于分析9名已知在1岁时神经异常的胎儿的记录。在4913个时长为10秒的足够胎儿脑电图记录片段中,低电压不规则(LVI)占17.8%,混合活动(MIX)占30.5%,高电压慢波(HVS)占18.1%,交替型(T/A)占33.2%。这些异常病例中观察到的胎儿脑电图模式数量似乎与11例正常病例中的显著不同(p小于0.001)。具体而言,发现异常病例中LVI的相对频率增加(p约等于0.05)。此外,LVI与视觉解释的长时间电压抑制显著相关(p小于0.025)以及1分钟阿氏评分降低(p约等于0.025)。使用判别函数分析分娩期间记录的胎儿脑电图中的LVI、MIX、HVS和T/A模式,11名婴儿中有10名被正确分类为1岁时神经正常,9名婴儿中有6名被正确分类为1岁时神经异常。这些研究证实了基于胎儿脑电图视觉分析的先前关联,并表明胎儿脑电图模式的相对频率可能有助于预测1年后的神经学结果。

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