De "vermoeidheidsdeskundigen" van het CDC, zoals dr. Bill Reeves, zijn kennelijk niet voornemens onderzoek te doen naar organische afwijkingen/oorza(a)k(en) van ME/CVS...

Onlangs verscheen een studie van Reeves en kollega's waarin ze melding maken van

het feit dat ze "chronisch vermoeide mensen" onder kunnen verdelen in 5 groepen.

Eerst werden veegden "vermoeidheidsdeskundigen" Reeves en White

mensen met de niets zeggende vergaarbakdiagnose "CVS" (Reeves-kriteria: klik hier)

op een nog grotere hoop

met mensen andere "chronisch vermoeide mensen" die zich al dan niet "onwel" voelen...

Vervolgens, stellen de onderzoekers, kun je die mensen

op basis van slaapproblemen, depressiviteit, overgewicht en aantal symptomen

onderverdelen in de volgende vijf groepen:

En de "schokkende" konklusie van de "vermoeidheidsdeskundigen"?

De meeste CVS-patiënten vallen in kategorie 1 en 2.

Als klap op de vuurpijl stellen de auteurs dat

CVS heterogeen is (kort door de bocht: een grote vuilnisbak),

en dat het derhalve zinvol is de kriteria verder te verruimen.

Tja, dat klinkt heel logisch...

Buitenbeentjes (in meer dan één opzicht): zwaarlijvig, energiek én zorgeloos.

Citaten uit het uitgebreide studierapport:

Subjects with current non-melancholic major depressive episode or a past history of major depressive disorder were not excluded.

...

Thus, we evaluated functional impairment

by means of the Medical Outcomes Short-Form Health Survey (SF-36) [19].

We used the Multidimensional Fatigue Inventory (MFI-20)

to measure characteristics of fatigue, and

we utilized the CDC CFS Symptom Inventory

to document occurrence, frequency, and severity of the defining symptoms [21].

Subjects who had ≥ four case-defining symptoms,

who exceeded the Symptom Inventory cut-off score, and

who met CFS cut-off scores on the SF-36 and the MFI-20

were considered to have CFS (n=113 participants).

Class 1 (25%) captured ill subjects

with many symptoms, prominent fatigue, sleep problems, and depression,

but no aberrant biological markers (including body mass index) characterized this group.

Class 2 (24%) similarly captured ill subjects

who reported prominent, widespread symptoms, insomnia, and depression.

However, these subjects had an associated metabolic syndrome (elevated insulin and inflammatory markers) and were obese.

Class 3 (20%) included less ill subjects with fewer symptoms but similarly obese individuals with elevated serum insulin and inflammatory markers.

Class 4 (20%) and Class 5 (11%) primarily included well individuals of normal weight.

Class 5 included the youngest individuals and Class 4 the oldest.

...

Future etiological work needs to take into account the heterogeneity of CFS,

using the determining variables, such as obesity, multiple symptoms, and depression,

to stratify samples.

For instance, obesity leads to fatigue in multiple ways,

including sleep disturbance, metabolic strain,

increased inflammatory markers, and deconditioning [12,27,28]

...

The data do not support the current perception that

CFS represents a unique homogeneous disease and

suggests broader criteria may be more explanatory.

Replication of an empirical approach to delineate the heterogeneity of chronic unexplained fatigue

Popul Health Metr.2009 Oct 5;7(1):17.

Aslakson E, Vollmer-Conna U, Reeves WC, White PD.

BACKGROUND:

Chronic fatigue syndrome (CFS) is defined by self-reported symptoms.

There are

no diagnostic signs or laboratory markers,

and the pathophysiology remains inchoate.

In part, difficulties

identifying and replicating biomarkers and

elucidating the pathophysiology

reflect the heterogeneous nature of the syndromic illness CFS.

We conducted this analysis of

people from defined metropolitan, urban, and rural populations

to replicate our earlier empirical delineation

of medically unexplained chronic fatigue and CFS

into discrete endophenotypes.

Both the earlier and current analyses utilized quantitative measures

of functional impairment and symptoms as well as laboratory data.

This study and the earlier one

enrolled participants from defined populations and

measured the internal milieu,

which differentiates them from studies of clinic referrals

that examine only clinical phenotypes.

METHODS:

This analysis evaluated

386 women

identified in a population-based survey

of chronic fatigue and unwellness

in metropolitan, urban, and rural populations of the state of Georgia, USA.

We used

variables previously demonstrated to effectively delineate endophenotypes

in an attempt to replicate identification of these endophenotypes.

Latent class analyses were used to derive the classes, and

these were compared and contrasted

to those described in the previous study based in Wichita, Kansas.

RESULTS:

We identified five classes in the best fit analysis.

Participants in

Class 1 (25%)

were polysymptomatic, with sleep problems and depressed mood.

Class 2 (24%)

was also polysymptomatic, with insomnia and depression,

but participants were also obese with associated metabolic strain.

Class 3 (20%)

had more selective symptoms

but was equally obese with metabolic strain.

Class 4 (20%) and Class 5 (11%)

consisted of non-fatigued, less symptomatic individuals,

Class 4 being older and Class 5 younger.

The classes were generally validated by independent variables.

People with CFS fell equally into Classes 1 and 2.

Similarities to the Wichita findings

included the same four main defining variables of

obesity, sleep problems, depression, and the multiplicity of symptoms.

Four out of five classes were similar across both studies.

CONCLUSIONS:

These data support

the hypothesis that

chronic medically unexplained fatigue is heterogeneous and

can be delineated into discrete endophenotypes

that can be replicated.

The data do not support

the current perception that

CFS represents a unique homogeneous disease and

suggests broader criteria may be more explanatory.

This replication

suggests that

delineation of endophenotypes

of CFS and

associated ill health

may be necessary

in order

to better understand etiology and

provide more patient-focused treatments.

PMID: 19804639 [PubMed - as supplied by publisher]

Samenvatting:

http://www.ncbi.nlm.nih.gov/pubmed/19804639

Uitgebreid rapport:

http://www.pophealthmetrics.com/content/pdf/1478-7954-7-17.pdf