Myalgic Encephalomyelitis (ME), Chronic Fatigue Syndrome (CFS), and Chronic Fatigue (CF) are distinguished accurately: results of supervised learning techniques applied on clinical and inflammatory data.

There is much debate on the diagnostic classification of Myalgic Encephalomyelitis (ME), Chronic Fatigue Syndrome (CFS) and chronic fatigue (CF). Post-exertional malaise (PEM) is stressed as a key feature. This study examines whether CF and CFS, with and without PEM, are distinct diagnostic categories. Fukuda's criteria were used to diagnose 144 patients with chronic fatigue and identify patients with CFS and CF, i.e. those not fulfilling the Fukuda's criteria. PEM was rated by means of a scale with defined scale steps between 0 and 6. CFS patients were divided into those with PEM lasting more than 24h (labeled: ME) and without PEM (labeled: CFS). The 12-item Fibromyalgia and Chronic Fatigue Syndrome (FF) Rating Scale was used to measure severity of illness. Plasma interleukin-1 (IL-1), tumor necrosis factor (TNF)α, and lysozyme, and serum neopterin were employed as external validating criteria. Using fatigue, a subjective feeling of infection and PEM we found that ME, CFS, and CF were distinct categories. Patients with ME had significantly higher scores on concentration difficulties and a subjective experience of infection, and higher levels of IL-1, TNFα, and neopterin than patients with CFS. These biomarkers were significantly higher in ME and CFS than in CF patients. PEM loaded highly on the first two factors subtracted from the data set, i.e. "malaise-sickness" and "malaise-hyperalgesia". Fukuda's criteria are adequate to make a distinction between ME/CFS and CF, but ME/CFS patients should be subdivided into ME (with PEM) and CFS (without PEM). Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Citation

Michael Maes, Frank N M Twisk, Cort Johnson. Myalgic Encephalomyelitis (ME), Chronic Fatigue Syndrome (CFS), and Chronic Fatigue (CF) are distinguished accurately: results of supervised learning techniques applied on clinical and inflammatory data. Psychiatry research. 2012 Dec 30;200(2-3):754-60

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PMID: 22521895

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