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自动肌电图分析在神经肌肉疾病中的诊断价值。

The diagnostic yield of automatic EMG analysis in neuromuscular diseases.

作者信息

Hausmanowa-Petrusewicz I, Rowińska-Marcińska K, Emeryk-Szajewska B, Ryniewicz B, Kopeć A, Kopeć J, Szmidt-Sałkowska E

机构信息

Department of Neurology, School of Medicine, Warsaw.

出版信息

Acta Physiol Pol. 1988 Jan-Feb;39(1):11-9.

PMID:3048045
Abstract

The aim of the study was to evaluate the diagnostic yield of automatic EMG analysis employed in differentiating normal from diseased muscle and myogenic, neural and spinal lesions. The material comprised 520 patients with neuromuscular diseases. Only diagnostically confirmed cases were included into the study. The control group comprised 51 healthy subjects. In all patients and healthy subjects routine EMG examination was performed by means of both the conventional technique and automatic method. On the basis of the statistical analysis of the material the authors concluded that the method of automated EMG using the Polish minicomputer Anops makes possible distinction of the main types of pathological processes affecting the muscles with higher than previously objectivity and reliability. They stress, however, the important role of the examiner and his experience.

摘要

本研究的目的是评估自动肌电图分析在区分正常肌肉与患病肌肉以及肌源性、神经源性和脊髓性病变方面的诊断效能。研究材料包括520例神经肌肉疾病患者。仅纳入经诊断证实的病例。对照组包括51名健康受试者。对所有患者和健康受试者均采用传统技术和自动方法进行常规肌电图检查。基于对材料的统计分析,作者得出结论,使用波兰小型计算机Anops的自动肌电图方法能够以高于以往的客观性和可靠性区分影响肌肉的主要病理过程类型。然而,他们强调了检查者及其经验的重要作用。

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