Literature DB >> 31274692

The Role of EEG in the Erroneous Diagnosis of Epilepsy.

Ushtar Amin1, Selim R Benbadis.   

Abstract

Errors in diagnosis are relatively common in medicine and occur in all specialties. The consequences can be serious for both patients and physicians. Errors in neurology are often because of the overemphasis on 'tests' over the clinical picture. The diagnosis of epilepsy in general is a clinical one and is typically based on history. Epilepsy is more commonly overdiagnosed than underdiagnosed. An erroneous diagnosis of epilepsy is often the result of weak history and an 'abnormal' EEG. Twenty-five to 30% of patients previously diagnosed with epilepsy who did not respond to initial antiepileptic drug treatment do not have epilepsy. Most patients misdiagnosed with epilepsy turn out to have either psychogenic nonepileptic attacks or syncope. Reasons for reading a normal EEG as an abnormal one include over-reading normal variants or simple fluctuations of background rhythms. Reversing the diagnosis of epilepsy is challenging and requires reviewing the 'abnormal' EEG, which can be difficult. The lack of mandatory training in neurology residency programs is one of the main reasons for normal EEGs being over-read as abnormal. Tests (including EEG) should not be overemphasized over clinical judgment. The diagnosis of epilepsy can be challenging, and some seizure types may be underdiagnosed. Frontal lobe hypermotor seizures may be misdiagnosed as psychogenic events. Focal unaware cognitive seizures in elderly maybe be blamed on dementia, and ictal or interictal psychosis in frontal and temporal lobe epilepsies may be mistaken for a primary psychiatric disorder.

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Year:  2019        PMID: 31274692     DOI: 10.1097/WNP.0000000000000572

Source DB:  PubMed          Journal:  J Clin Neurophysiol        ISSN: 0736-0258            Impact factor:   2.177


  9 in total

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Authors:  Fábio A Nascimento; Jin Jing; Sándor Beniczky; Selim R Benbadis; Jay R Gavvala; Elza M T Yacubian; Samuel Wiebe; Stefan Rampp; Michel J A M van Putten; Manjari Tripathi; Mark J Cook; Peter W Kaplan; William O Tatum; Eugen Trinka; Andrew J Cole; M Brandon Westover
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4.  Variability analysis of epileptic EEG using the maximal overlap discrete wavelet transform.

Authors:  Jack L Follis; Dejian Lai
Journal:  Health Inf Sci Syst       Date:  2020-09-15

5.  Insight into the Contact Impedance between the Electrode and the Skin Surface for Electrophysical Recordings.

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6.  Objective characterization of hip pain levels during walking by combining quantitative electroencephalography with machine learning.

Authors:  Atsushi Kimura; Yasue Mitsukura; Akihito Oya; Morio Matsumoto; Masaya Nakamura; Arihiko Kanaji; Takeshi Miyamoto
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7.  Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

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Journal:  Comput Intell Neurosci       Date:  2022-04-13

8.  EEG normal variants: A prospective study using the SCORE system.

Authors:  Stephan Wüstenhagen; Daniella Terney; Elena Gardella; Pirgit Meritam Larsen; Connie Rømer; Harald Aurlien; Sándor Beniczky
Journal:  Clin Neurophysiol Pract       Date:  2022-06-30

9.  Abnormal hubs in global network as neuroimaging biomarker in right temporal lobe epilepsy at rest.

Authors:  Ruimin Guo; Yunfei Zhao; Honghua Jin; Jihua Jian; Haibo Wang; Shengxi Jin; Hongwei Ren
Journal:  Front Psychiatry       Date:  2022-07-27       Impact factor: 5.435

  9 in total

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