New Komaroff study: EEG spectral coherence in pwME/CFS - A potential diagnostic tool

[eric_s]

Here's a new study that seems interesting to me:

"EEG spectral coherence data distinguish chronic fatigue syndrome patients
from healthy controls and depressed patients - A case control study"

http://www.biomedcentral.com/content/pdf/1471-2377-11-82.pdf

Abstract: http://www.biomedcentral.com/1471-2377/11/82/abstract

Frank H Duffy, Gloria B McAnulty, Michelle C McCreary, George J Cuchural and Anthony L Komaroff

BMC Neurology 2011, 11:82doi:10.1186/1471-2377-11-82

Published: 1 July 2011
Abstract (provisional)

Background
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 depression. 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 medications. 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.

Feel free to post quotes etc., i'm a bit too wasted to do it myself right now and i usually don't read the entire papers.

 

[*GG*]

EEG spectral coherence data distinguish chronic fatigue syndrome patients
from healthy controls and depressed patients - A case control study

is the actual title of the paper. I was wondering if specral was a word I was not familiar with. Will read later.

GG

 

[kaffiend]

I've done a lot of spectral analysis of MEG/EEG data. They basically recorded brainwaves from controls, CFS and depressed patients and could identify (with certain accuracy) which group a patient belongs to (i.e., each group has different brainwave signatures). This looks like an early release of the article - it will be easier to interpret with figures.

 

[Enid]

Looking good to me eric - especially as those around me here forced into CBT were persuaded to acknowledge their "depression" (none of course were).

 

[eric_s]

EEG spectral coherence data distinguish chronic fatigue syndrome patients
from healthy controls and depressed patients - A case control study

is the actual title of the paper. I was wondering if specral was a word I was not familiar with. Will read later.

GG

Specral was a typo. I asked a moderator yesterday to correct it, but it looks as if he didn't do it yet.

 

[eric_s]

I've done a lot of spectral analysis of MEG/EEG data. They basically recorded brainwaves from controls, CFS and depressed patients and could identify (with certain accuracy) which group a patient belongs to (i.e., each group has different brainwave signatures). This looks like an early release of the article - it will be easier to interpret with figures.

Very interesting, kaffiend. I hope you will be able to comment further.

 

[Daffodil]

komaroff seems to intelligent yet spends so much time on junk. why cant he just focus on the infection. there are already a million biomarkers that distinguish us from depressed people. i havent heard anything useful from his camp for many years. he isnt even prescribing ARV's i dont think. he has been with CFS for decades now and seen so many die, i expected more.

 

[soxfan]

I am a patient of Dr. K and he doesn't prescribe much of anything. He only gave me some basic blood tests and that was it. I have been very disappointed with my visits. Plus you have to wait 4 months to see him inbetween.
He is a very kind and nice man but doesn't seem to do much in way of treatment for many of the symptoms...my last office visit was less than 10 minutes and it is 1 and1/2 hour drive to get there. Maybe my expectations were too high but it hasn't gone at all like I thought it would.

 

[eric_s]

Sorry to hear that. I always had a high opinion of him (and still do). Maybe he's not the man to go to for treatments. On the other hand i don't know if many people have success with treatments, i've never been into that much. Probably because i don't have pain or at least not much and not often.

I think this study is extremely interesting. If they were able to develop such a diagnostic tool that can be applied succesfully in doctor's offices, that would change things dramatically, i think, as far as acceptance as a serious physical illness goes. And it would hopefully lead to much "cleaner" cohorts and thus better studies. I'm not aware of any biomarker yet that is reliable and being used by doctors to diagnose people with ME/CFS. So far it's still Fukuda or the CCC that is being used for that (or one of the crap criteria).

And i think it helps us a lot to have a Harvard professor on our side.

 

[soxfan]

He is definately a brilliant doctor and seems to really care about CFS and trying to find answers. He is waiting for the Stanford study to come out before he will prescribe any anti virals. I think he is just very careful when it comes to treatments and doesn't use them if there isn't sufficient proof that they will benefit us. I just thought it was kind of strange that I wasn't tested for anything else. I know or have read that Dr. Klimas does all kinds of testing but all I had were a few blood tests. Maybe that is just how he practices...I will stick with him because I feel he is my best chance for some type of treatment in the future. Plus if he does any studies on his own with a/v then maybe I will have the chance to participate.

 

[eric_s]

Could you give some more info about what blood tests he did? Thanks.

 

[Advocate]

I think this could be a terribly important study. The full text is available here: http://www.biomedcentral.com/content/pdf/1471-2377-11-82.pdf

Here's the abstract:

http://www.biomedcentral.com/1471-2377/11/82/abstract

EEG spectral coherence data distinguish chronic fatigue syndrome patients from healthy controls and depressed patients - A case control study

Frank H Duffy , Gloria B McAnulty , Michelle C McCreary , George J Cuchural and Anthony L Komaroff

BMC Neurology 2011, 11:82doi:10.1186/1471-2377-11-82

Published: 1 July 2011
Abstract (provisional)

Background
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 depression. 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 medications. 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.

 

[soxfan]

He did the standard CBC and and metabolic panels...HHV6 IgG through Arup Lab, Lyme, Hepatitis B, EBV VCAIgG and VCA IgM, EBV EA, Vit B12, Quantitative Immunoglobulins IgG and IgM, ANA, SS-A (RO), SS-B(LA), RNP, HBV surface, HCB Ab

I think that is about it..

 

[taniaaust1]

He sounds like a cautious doctor... nothing really wrong with that as after all nothing is proven to work so I dont think doctors like that should be knocked due to just having a cautious nature.

I wouldnt at all call this at all "junk".
I think research looking into biomarkers or trying to make the evidence out there about certainly abnormalities we have stronger, is a very good thing, we need to encourage ME/CFS studies which arent psychological ones. We dont want the scienctific community to forget we have very real abnormalities...and there is so many psychological studies influence which need to be offset.

All my brain wave EEGs have always been labeled abnormal with unspecific findings. (eg they didnt know the abnormality is related to ME but I know it is from other ME patients results). We NEED this information to be more recognised.. we need ALL the abnormalities in ME to be more recognised. I applaud Dr komaroff for this study.

The more known ways to test to help distinguish between ME and depression and separate the different illnesses, the better. What is really more important then helping get the different patient groups clearer? Treatment studies are no good if the patient groups arent clear and have ones with completely different illnesses in them. Clarifying is very important.

Encourage all who back/support us rather then negatively knock them.