Diagnosis of myalgic encephalomyelitis : where are we now?

Maes, Michael, Anderson, George, Morris, Gerwyn and Berk, Michael 2013, Diagnosis of myalgic encephalomyelitis : where are we now?, Expert opinion on medical diagnosis, vol. 7, no. 3, pp. 221-225.

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Title Diagnosis of myalgic encephalomyelitis : where are we now?
Author(s) Maes, Michael
Anderson, George
Morris, Gerwyn
Berk, Michael
Journal name Expert opinion on medical diagnosis
Volume number 7
Issue number 3
Start page 221
End page 225
Total pages 5
Publisher Informa Healthcare
Place of publication London, England
Publication date 2013-05
ISSN 1753-0059
Keyword(s) case definition
chronic fatigue
chronic fatigue syndrome
myalgic encepahlomyelitis
Summary Introduction: The World Health Organization has classified myalgic encephalomyelitis (ME) as a neurological disease since 1969 considering chronic fatigue syndrome (CFS) as a synonym used interchangeably for ME since 1969. ME and CFS are considered to be neuro-immune disorders, characterized by specific symptom profiles and a neuro-immune pathophysiology. However, there is controversy as to which criteria should be used to classify patients with “chronic fatigue syndrome.”

Areas covered: The Centers for Disease Control and Prevention (CDC) criteria consider chronic fatigue (CF) to be distinctive for CFS, whereas the International Consensus Criteria (ICC) stresses the presence of post-exertion malaise (PEM) as the hallmark feature of ME. These case definitions have not been subjected to rigorous external validation methods, for example, pattern recognition analyses, instead being based on clinical insights and consensus.

Expert opinion: Pattern recognition methods showed the existence of three qualitatively different categories: (a) CF, where CF evident, but not satisfying full CDC syndrome criteria. (b) CFS, satisfying CDC criteria but without PEM. (c) ME, where PEM is evident in CFS. Future research on this “chronic fatigue spectrum” should, therefore, use the abovementioned validated categories and novel tailored algorithms to classify patients into ME, CFS, or CF.
Language eng
Field of Research 119999 Medical and Health Sciences not elsewhere classified
Socio Economic Objective 970111 Expanding Knowledge in the Medical and Health Sciences
HERDC Research category C4 Letter or note
ERA Research output type X Not reportable
Persistent URL http://hdl.handle.net/10536/DRO/DU:30052554

Document type: Journal Article
Collection: School of Medicine
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