Case-control studies are used to identify factors that may contribute
to a medical condition by comparing subjects who have that condition
(the 'cases') with patients who do not have the condition but are
otherwise similar (the 'controls'). Obviously how you define those
with and those without a disease or disorder substantially contributes
to the results and conclusions of any study. One of the major pluses
of this study, which has been in the works for several years, is the
size of the study.
EEG spectral coherence data distinguish chronic fatigue syndrome
patients from healthy controls and depressed patients – A case control
Previous studies suggest central nervous system involvement in chronic
fatigue syndrome (CFS), yet there are no established diagnostic
criteria. CFS may be difficult to differentiate from clinical
The study's objective was to determine if spectral coherence, a
computational derivative of spectral analysis of the
electroencephalogram (EEG), could distinguish patients with CFS from
healthy control subjects and not erroneously classify depressed
patients as having CFS.
Methods: This is a study, conducted in an academic medical center
electroencephalography laboratory, of 632 subjects: 390 healthy normal
controls, 70 patients with carefully defined CFS, 24 with major
depression, and 148 with general fatigue. Aside from fatigue, all
patients were medically healthy by history and examination.
EEGs were obtained and spectral coherences calculated after extensive
artifact removal. Principal Components Analysis identified coherence
factors and corresponding factor loading patterns.
Discriminant analysis determined whether spectral coherence factors
could reliably discriminate CFS patients from healthy control subjects
without misclassifying depression as CFS.
Results: Analysis of EEG coherence data from a large sample (n=632) of
patients and healthy controls identified 40 factors explaining 55.6%
total variance. Factors showed highly significant group
differentiation (p<.0004) identifying 89.5% of unmedicated female CFS
patients and 92.4% of healthy female controls.
Recursive jackknifing showed predictions were stable. A conservative
10-factor discriminant function model was subsequently applied, and
also showed highly significant group discrimination (p<.001),
accurately classifying 88.9% unmedicated males with CFS, and 82.4%
unmedicated male healthy controls.
No patient with depression was classified as having CFS. The model was
less accurate (73.9%) in identifying CFS patients taking psychoactive
Factors involving the temporal lobes were of primary importance.
Conclusions: EEG spectral coherence analysis identified unmedicated
patients with CFS and healthy control subjects without misclassifying
depressed patients as CFS, providing evidence that CFS patients demonstrate brain physiology that is not observed in healthy normals or patients with major depression. Studies of new CFS patients and
comparison groups are required to determine the possible clinical
utility of this test.
The results concur with other studies finding neurological abnormalities in CFS, and implicate temporal lobe involvement in CFS pathophysiology.
Author: Frank DuffyGloria McAnultyMichelle McCrearyGeorge
Credits/Source: BMC Neurology 2011, 11:82
Final version will be available at: