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Co-Cure Weekly Digest of research and medical posts only - 18 Jun 2007 to 25 Jun 2007

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Date:    Tue, 19 Jun 2007 13:36:27 -0400
From:    "Bernice A. Melsky" <bernicemelsky VERIZON.NET>
Subject: RES: Mindfulness training as an intervention for fibromyalgia: evidence of postintervention and 3-year follow-up benefits in well-being

Mindfulness training as an intervention for fibromyalgia: evidence of
postintervention and 3-year follow-up benefits in well-being.

Psychother Psychosom. 2007;76(4):226-33.

Grossman P, Tiefenthaler-Gilmer U, Raysz A, Kesper U.

Division of Psychosomatic Medicine, Department of Internal Medicine,
University of Basel Hospital, Basel, Switzerland.

PMID: 17570961

Background: Mindfulness-based stress reduction (MBSR) proposes a systematic
program for reduction of suffering associated with a wide range of medical
conditions. Studies suggest improvements in general aspects of well-being,
including quality of life (QoL), coping and positive affect, as well as
decreased anxiety and depression.

Methods: A quasi-experimental study examined effects of an 8-week MBSR
intervention among 58 female patients with fibromyalgia (mean, 52 ± 8
years) who underwent MBSR or an active social support procedure.
Participants were assigned to groups by date of entry, and 6 subjects
dropped out during the study. Self-report measures were validated German
inventories and included the following scales: visual analog pain, pain
perception, coping with pain, a symptom checklist and QoL. Pre- and
postintervention measurements were made. Additionally, a 3-year follow-up
was carried out on a subgroup of 26 participants.

Results: Pre- to postintervention analyses indicated MBSR to provide
significantly greater benefits than the control intervention on most
dimensions, including visual analog pain, QoL subscales, coping with pain,
anxiety, depression and somatic complaints (Cohen d effect size,
0.40-1.10). Three-year follow-up analyses of MBSR participants indicated
sustained benefits for these same measures (effect size, 0.50-0.65).

Conclusions: Based upon a quasi-randomized trial and long-term
observational follow-up, results indicate mindfulness intervention to be of
potential long-term benefit for female fibromyalgia patients.

Copyright (c) 2007 S. Karger AG, Basel.

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Date:    Wed, 20 Jun 2007 08:52:15 +0200
From:    "Dr. Marc-Alexander Fluks" <fluks COMBIDOM.COM>
Subject: RES: CFS/ME & FM papers, published since May 2007

Source: NCBI PubMed
Date:   June 20, 2007
URL:    http://www.ncbi.nlm.nih.gov/entrez/query.fcgi
        Topic=((chronic fatigue) OR (myalgic encephalomyelitis)) OR fibromyalgia
Ref:    In the update, you will only find journals that are indexed by
        Medline (PubMed).
        All scientific papers 1938-today,
        Search scientific papers,
        Figures computer analysis scientific papers,
        All popular papers 1900-today,

CFS/ME & FM papers, published since May 2007

___ Sundgren PC, Petrou M, Harris RE, Fan X, Foerster B, Mehrotra N, Sen A,
       Clauw DJ, Welsh RC.
       Diffusion-weighted and diffusion tensor imaging in fibromyalgia
       patients: a prospective study of whole brain diffusivity, apparent
       diffusion coefficient, and fraction anisotropy in different regions
       of the brain and correlation with symptom severity.
       Acad Radiol. 2007 Jul;14(7):839-46.
___ Grossman P, Tiefenthaler-Gilmer U, Raysz A, Kesper U.
       Mindfulness training as an intervention for fibromyalgia: evidence
       of postintervention and 3-year follow-up benefits in well-being.
       Psychother Psychosom. 2007;76(4):226-33.
___ Balon R.
       Reflections on relevance: the fields of psychosomatics and
       psychotherapy in 2006.
       Psychother Psychosom. 2007;76(4):203-12.
___ Martinez-Lavin M, Infante O, Lerma C.
       Hypothesis: The Chaos and Complexity Theory May Help our Understanding
       of Fibromyalgia and Similar Maladies.
       Semin Arthritis Rheum. 2007 Jun 13.
___ Wallace DJ, Gotto J.
       Hypothesis: Bipolar Illness with Complaints of Chronic Musculoskeletal
       Pain Is a Form of Pseudofibromyalgia.
       Semin Arthritis Rheum. 2007 Jun 13.
___ Masuko K, Nakamura H.
       Functional somatic syndrome: how it could be relevant to rheumatologists.
       Mod Rheumatol. 2007;17(3):179-84.
___ Wyller VB, Saul JP, Amlie JP, Thaulow E.
       Sympathetic predominance of cardiovascular regulation during mild
       orthostatic stress in adolescents with chronic fatigue.
       Clin Physiol Funct Imaging. 2007 Jul;27(4):231-8.
___ Tomoda A.
       School phobia and childhood chronic fatigue syndrome (CFS) [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1121-33.
___ Oki J, Okubo J.
       Usefulness of growth chart in children and adolescents with chronic
       fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1113-9.
___ Tanaka H.
       The autonomic function and child chronic fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1105-12.
___ Miike T.
       Childhood chronic fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1099-104.
___ Masuda A, Munemoto T, Tei C.
       A new treatment: thermal therapy [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1093-8.
___ Murakami M.
       Attentive consideration for the treatment of chronic fatigue syndrome
       Nippon Rinsho. 2007 Jun;65(6):1089-92.
___ Yamadera W, Itoh H.
       Overview of psychiatric therapy for chronic fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1082-6.
___ Yoshihara K, Kubo C.
       Overview of medical treatment and management of chronic fatigue
       syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1077-81.
___ Hakariya Y, Kuratsune H.
       Chronic fatigue syndrome: biochemical examination of blood [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1071-6.
___ Nishikai M.
       Antinuclear antibodies [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1067-70 [Japanese].
___ Tajima S, Kuratsune H, Yamaguti K, Takahashi A, Takashima S, Watanabe Y,
       Nishizawa Y.
       Estimation of fatigue state in patient with CFS using actigraph and
       R-R interval power spectrum analysis [Japanese]
       Nippon Rinsho. 2007 Jun;65(6):1057-64.
___ Sakudo A, Kuratsune H, Hakariya Y, Kobayashi T, Ikuta K.
       Spectroscopic diagnosis of chronic fatigue syndrome by multivariate
       analysis of visible and near-infrared spectra [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1051-6.
___ Kondo K.
       Chronic fatigue syndrome and herpesvirus reactivation [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1043-8.
___ Yamaguti K.
       The evaluation of fatigue by using acceleration plethysmography
       Nippon Rinsho. 2007 Jun;65(6):1034-42.
___ Kawai T, Rokutan K.
       Identification and application of marker genes for differential
       diagnosis of chronic fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1029-33.
___ Yoshiuchi K.
       Psychological symptoms in chronic fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1023-7.
___ Kumano-go T, Adachi H, Sugita Y.
       Sleep disturbance [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1017-22.
___ Ban N, Saiki T, Ko G, Kuwahata A.
       Clinical features of chronic fatigue syndrome-symptoms [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1011-5.
___ Miwa S, Takikawa O.
       Chronic fatigue syndrome and neurotransmitters [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):1005-10.
___ Narita M, Narita N.
       Genetic background of chronic fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):997-1002.
___ Sairenji T, Nagata K.
       Viral infections in chronic fatigue syndrome [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):991-6.
___ Kuratsune H.
       Overview of chronic fatigue syndrome focusing around prevalence and
       diagnostic criteria [Japanese].
       Nippon Rinsho. 2007 Jun;65(6):983-90.
___ Hashimoto N.
       History of chronic fatigue syndrome [Japanese]
       Nippon Rinsho. 2007 Jun;65(6):975-82.
___ White PD.
       How common is chronic fatigue syndrome; how long is a piece of string?
       Popul Health Metr. 2007 Jun 8;5(1):6.
___ Reeves WC, Jones JF, Maloney E, Heim C, Hoaglin DC, Boneva RS, Morrissey
       M, Devlin R.
       Prevalence of chronic fatigue syndrome in metropolitan, urban, and
       rural Georgia.
       Popul Health Metr. 2007 Jun 8;5(1):5.
___ Armitage R, Landis C, Hoffmann R, Lentz M, Watson NF, Goldberg J,
       Buchwald D.
       The impact of a 4-hour sleep delay on slow wave activity in twins
       discordant for chronic fatigue syndrome.
       Sleep. 2007 May 1;30(5):657-62.
___ Mease P, Arnold LM, Bennett R, Boonen A, Buskila D, Carville S, Chappell
       A, Choy E, Clauw D, Dadabhoy D, Gendreau M, Goldenberg D, Littlejohn G,
       Martin S, Perera P, Russell IJ, Simon L, Spaeth M, Williams D,
       Crofford L.
       Fibromyalgia syndrome.
       J Rheumatol. 2007 Jun;34(6):1415-25.
___ Hauser W.
       Self-assessed pain intensity and disability in subjects diagnosed with
       fibromyalgia claiming retirement pension [German].
       Schmerz. 2007 Jun 6.
___ Forbes D, Chalmers A.
       Fibromyalgia: revisiting the literature.
       JCCA J Can Chiropr Assoc. 2004 Jun;48(2):119-31.
___ Torpy DJ, Ho JT.
       Corticosteroid-binding globulin gene polymorphisms: clinical
       implications and links to idiopathic chronic fatigue disorders.
       Clin Endocrinol (Oxf). 2007 Jun 4.
___ Ter Wolbeek M, van Doornen LJ, Kavelaars A, van de Putte EM, Schedlowski
       M, Heijnen CJ.
       Longitudinal analysis of pro- and anti-inflammatory cytokine
       production in severely fatigued adolescents.
       Brain Behav Immun. 2007 May 31.
___ Bennett B, Goldstein D, Friedlander M, Hickie I, Lloyd A.
       The Experience of Cancer-Related Fatigue and Chronic Fatigue Syndrome:
       A Qualitative and Comparative Study.
       J Pain Symptom Manage. 2007 May 31.
___ Bazzichi L, Rossi A, Massimetti G, Giannaccini G, Giuliano T, De Feo F,
       Ciapparelli A, Dell'osso L, Bombardieri S.
       Cytokine patterns in fibromyalgia and their correlation with clinical
       Clin Exp Rheumatol. 2007 Mar-Apr;25(2):225-30.
___ Rossini M, Di Munno O, Valentini G, Bianchi G, Biasi G, Cacace E,
       Malesci D, La Montagna G, Viapiana O, Adami S.
       Double-blind, multicenter trial comparing acetyl l-carnitine with
       placebo in the treatment of fibromyalgia patients.
       Clin Exp Rheumatol. 2007 Mar-Apr;25(2):182-8.
___ Brown MM, Jason LA.
       Functioning in individuals with chronic fatigue syndrome: increased
       impairment with co-occurring multiple chemical sensitivity and
       Dyn Med. 2007 May 31;6:6.
___ White PD.
       What Causes Prolonged Fatigue after Infectious Mononucleosis - and
       Does It Tell Us Anything about Chronic Fatigue Syndrome?
       J Infect Dis. 2007 Jul 1;196(1):4-5.
___ Torres Mata X, Peri Nogues JM.
       Non pharmacologic and alternative treatments in fibromyalgia
       Med Clin (Barc). 2007 May 5;128(17):679.
___ Faulkner S, Smith A.
       A longitudinal study of the relationship between psychological
       distress and recurrence of upper respiratory tract infections in
       chronic fatigue syndrome.
       Br J Health Psychol. 2006 Dec 18.
___ Thieme K, Turk DC, Flor H.
       Responder criteria for operant and cognitive-behavioral treatment of
       fibromyalgia syndrome.
       Arthritis Rheum. 2007 Jun 15;57(5):830-6.
___ Scheeres K, Wensing M, Mes C, Bleijenberg G.
       The impact of informational interventions about cognitive behavioral
       therapy for chronic fatigue syndrome on GPs referral behavior.
       Patient Educ Couns. 2007 May 21.
___ Fioravanti A, Perpignano G, Tirri G, Cardinale G, Gianniti C, Lanza CE,
       Loi A, Tirri E, Sfriso P, Cozzi F.
       Effects of mud-bath treatment on fibromyalgia patients: a randomized
       clinical trial.
       Rheumatol Int. 2007 May 23.
___ Wyller VB, Thaulow E, Amlie JP.
       Treatment of chronic fatigue and orthostatic intolerance with
       J Pediatr. 2007 Jun;150(6):654-5.
___ Massey PB.
       Reduction of fibromyalgia symptoms through intravenous nutrient
       therapy: results of a pilot clinical trial.
       Altern Ther Health Med. 2007 May-Jun;13(3):32-4.

(c) 2007 NCBI PubMed

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Date:    Wed, 20 Jun 2007 13:14:10 -0700
From:    "TVA12082208 aol.com"
Subject: MED: Lyme and herpes in CFS

It has been puzzling to me that every cancer patient I test for a Lyme
infection turns out positive. My ongoing research on Lyme has focused in
weeks on a mycoplasma that lies at the root of the disease. It appears to be
fundamental factor that severely depresses the immune system allowing the
entire complex of pathogenic bacteria, fungi, parasites, and viruses to
proliferate. A recent study shows that "chronic infection or colonization by
mycoplasma(s) could gradually and significantly alter many biologic properties
mammalian host cells in culture, including induction of malignant

Therefore, in those individuals with cancer, it is important to eliminate the
Rife BX/BY "virus", the Gregory "cancer virus", the SV40 virus, and Lyme
disease. Failing to do this sets the individual up for progression and/or
recurrence of malignancy.
Mycoplasma fermentans infection promotes immortalization of human peripheral
blood mononuclear cells in culture.

Zhang S, Tsai S, Wu TT, Li B, Shih JW, Lo SC
Department of Infectious and Parasitic Diseases Pathology, American Registry
of Pathology, Washington DC, USA. Blood. 2004 Dec 15;104(13):4252-9. Epub 2004
Aug 26

Chronic infection or colonization by mycoplasma(s) could gradually and
significantly alter many biologic properties of mammalian host cells in
culture, including induction of malignant transformation. We examined effects of
Mycoplasma fermentans infection on the continuing survival and immortality of
human peripheral blood mononuclear cells (PBMCs) from healthy blood donors. Without
specific supplemental growth factors, human PBMCs normally die rapidly, with
few cells other than macrophages/monocytes surviving after 2 weeks in cultures.
Only occasional Epstein-Barr virus (EBV)-positive B lymphocytes would continue
to proliferate and undergo spontaneous immortalization. Our present study
revealed that infection of human PBMCs in culture with the incognitus and PG18
strains of M fermentans, but surprisingly not with some other strains tested
in parallel, markedly enhanced the rate of EBV-positive B lymphocytes to undergo
immortalization (74% vs 17%). Compared with spontaneously immortalized PBMCs,
the PBMCs immortalized in cultures infected with the mycoplasmas often had
prominent karyotype changes with chromosomal loss, gain, or translocations.
Furthermore, many of these immortalized B lymphocytes were found to be monoclonal
in nature. The in vitro findings would be of relevance to lymphoproliferative
disorders that occurred in patients with immune suppression. The
mycoplasma-mediated promotional effect in cell immortalization and its
potential clinical implications warrant further study.

Kind regards,
Katharina Gutsche

Katharina Gutsche, M.A. Psycholinguistics, Dipl.-Psych.Clinical Psychology,
State Licensured Naturopath (Psychotherapy)

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Date:    Thu, 21 Jun 2007 11:33:19 +0200
From:    "Dr. Marc-Alexander Fluks" <fluks COMBIDOM.COM>
Subject: RES,NOT: CDC on CFS prevalence

Source: Population Health Metrics
        Vol. 5, #1, p 5
Date:   June 8, 2007
URL:    http://www.pophealthmetrics.com/content/5/1/5


Prevalence of Chronic Fatigue Syndrome in Metropolitan, Urban, and Rural Georgia
William C. Reeves(1,*), James F. Jones(1), Elizabeth Maloney(1), Christine
Heim(2), David C. Hoaglin(3), Roumiana S. Boneva(1), Marjorie Morrissey(4),
Rebecca Devlin(4)

1 Chronic Viral Diseases Branch, Coordinating Center for Infectious Diseases,
  Centers for Disease Control and Prevention, Atlanta, GA, USA.
2 Department of Psychiatry & Behavioral Sciences, Emory University School of
  Medicine, Atlanta, GA, USA.
3 Abt Associates Inc, Cambridge, MA, USA, 4 Abt Associates Inc, Chicago, IL,
* Corresponding author
Email: William C Reeves* - wcr1@cdc.gov; James F Jones - jaj9@cdc.gov;
  Elizabeth Maloney - evm3@cdc.gov; Christine Heim - cmheim@emory.edu;
  David C Hoaglin - dave_hoaglin@abtassoc.com; Roumiana S Boneva -
rrb5@cdc.gov; Marjorie Morrissey - Marjorie_Morrissey@abtassoc.com;
  Rebecca Devlin - Rebecca_Devlin@abtassoc.com


Chronic fatigue syndrome (CFS) is a debilitating illness with no known cause
or effective therapy. Population-based epidemiologic data on CFS prevalence
are critical to put CFS in a realistic context for public health officials
and others responsible for allocating resources.

Based on a random-digit dialing survey we ascertained CFS cases and controls
to estimate the prevalence of CFS in metropolitan, urban, and rural
populations of Georgia. This report focuses on the 5,623 of 19,381
respondents ages 18 to 59 years old. Fatigued (2,438), randomly selected
unwell not fatigued (1,429) and randomly selected well (1,756) respondents
completed telephone questionnaires concerning fatigue, other symptoms, and
medical history. Subsets of those identified by interview as having
CFS-like illness (292), chronic unwellness which was not CFS-like
(268--randomly selected), and well subjects (223, matched to those with
CFS-like illness on sex, race, and age) completed a clinical evaluation.

We estimated that 2.54% of persons 18 to 59 years of age suffered from CFS.
There were no significant differences in prevalence of CFS between
metropolitan, urban or rural populations or between white and black
residents of the three regions. However, there were significant differences
in female-to-male ratios of prevalence across the strata (metropolitan
female: male 11.2 : 1, urban 1.7 : 1, rural 0.8 : 1).

We estimated that 2.54% of the Georgia population suffers from CFS, which is
6- to 10-fold higher than previous population-based estimates in other
geographic areas. These differences may reflect broader screening criteria
and differences in the application of the case definition. However, we
cannot exclude the possibility that CFS prevalence may be higher in Georgia
than other areas where it has been measured. Although the study did not
identify differences in overall prevalence between metropolitan, urban, and
rural Georgia populations, it did suggest the need for additional stratified
analyses by geographic strata.


Chronic fatigue syndrome (CFS) is a complex medical and public health
problem that is associated with severe personal suffering and loss. The
median duration of illness is 7 years, a quarter of those with the illness
are unemployed or receiving disability, and the average affected family
forgoes approximately $20,000 in annual earnings and wages [1]. Yet, fewer
than 20 percent have received medical care for CFS [2, 3]. Despite more than
3,000 articles in the peer- reviewed medical literature, the pathophysiology
of CFS is not well understood. There are no diagnostic laboratory
abnormalities or clinical tests. There is no public health control or
prevention strategy for CFS.

An understanding of the prevalence and distribution of CFS in the general
population is fundamental to focusing etiologic research, estimating the
effects of CFS on quality of life and productivity, and devising control and
prevention strategies. The few studies which have estimated the prevalence
of CFS in defined populations [4, 5, 3, 6] reported prevalence estimates for
CFS in adults to be between 0.24% [3] and 0.42% [5], and prevalence for
CFS-like illness between 0.25% [4] and 1.67% [6]. These studies used
different sampling, screening, and evaluation strategies; so, their results
are not strictly comparable. They also identified relatively small numbers
of persons with CFS, and thus they lack statistical power. However, all
four studies documented that CFS disproportionately affects women, is more
common in the economically disadvantaged, and affects racial/ethnic
minorities at rates equal to or greater than those of whites.

We conducted the survey herein reported to estimate the prevalence of CFS in
racial/ethnic groups representative of defined metropolitan, urban, and
rural populations. The primary objective was to obtain information that
could be used as a basis for the development and evaluation of a control
strategy for CFS. The study also rectified two major weaknesses of previous
studies. First, previous studies have screened the population for
individuals with fatigue and then evaluated them for CFS. Although fatigue
is central to CFS, focusing on fatigue ignores other important dimensions of
the illness such as impaired memory or concentration, unrefreshing sleep,
and bodily pain. For many persons who suffer from CFS, these symptoms,
rather than fatigue, constitute the primary complaint. In addition, a
household informant may not be familiar with specific symptoms but can
identify whether someone is generally unwell or not. Thus, rather than
limiting the initial screening stage to fatigued and non-fatigued persons,
this survey cast a broader screening net, utilizing household informants to
identify unwell (fatigue, problems with memory/concentration, unrefreshing
sleep, or pain) members of these populations. We then conducted detailed
evaluations of participants who were identified by a household informant as
unwell to further identify those with CFS. Second, previous studies have
not defined CFS in a rigorous reproducible manner (i.e., they did not use
validated and standardized instruments to measure fatigue, impairment, and
accompanying symptoms) [7]. To address this deficit, we used validated and
standardized instruments to define CFS according to criteria of the 1994
case definition [8].


The CDC Institutional Review Board, as required by Department of Health and
Human Services regulations, approved the study. All participants were
volunteers who gave informed consent. The study was conducted in English.
Non-English speaking respondents were not included.

Study Design

Metropolitan, urban, rural.
The definitions of metropolitan, urban and rural geographic strata are
complex. The U.S. Office of Management and Budget defines several
categories of metropolitan statistical areas according to specific
standards. In general, metropolitan areas contain at least a million
residents living in a core area (i.e., central city), together with adjacent
communities that have a high degree of economic and social integration with
that core. Atlanta, with approximately 4 million residents, is a
metropolitan city. The Census Bureau defines urban and rural areas
independently of OMB's classification. Urban and rural can occur inside of
and outside of metropolitan areas. Typically, settled areas of 2,500 or
more are considered to be urban and the remainder rural. Based on these
definitions, we determined that the cities of Macon and Warner Robins (with
populations of 300,000 and 48,000, respectively) were urban. For this
study, we considered the counties surrounding Macon and Warner Robins to be

Survey in general.
The survey was conducted between September 2004 and July 2005. It included
residents of three areas of Georgia: metropolitan (Atlanta -- Fulton and
DeKalb counties), urban (Macon -- Bibb County and Warner Robins in adjacent
Houston County), and rural (10 counties surrounding Bibb County -- Houston
-excluding Warner Robins, Baldwin, Bleckley, Crawford, Jones, Macon, Monroe,
Peach, Twiggs, and Wilkinson). The survey used the same strategy as
previously reported CDC population surveys of CFS [7, 6]. We used list-
assisted random-digit dialing [9] and an advance letter [10] to contact
households containing persons aged 18-59 years in the three population

Telephone screening interviews.
In contrast to our previous studies, which screened households for fatigue,
in this study we modified the initial screening interview to cover a broader
range of CFS defining symptoms. In brief, the screening interview asked a
household informant (=> 18 years) to report the age, sex, ethnicity and
health status of each household member aged 18 and older and to identify
unwell household members, who the informant noticed to have at least one of
the CFS defining symptoms (fatigue, cognitive impairment, unrefreshing
sleep, muscle pain, joint pain, sore throat, tender lymph nodes, or
headache) for 1 month, and well residents, who had none of these problems
for => 1 month.

Detailed telephone interviews.
Household residents between 18 and 59 years of age who were identified by
the informant as unwell with fatigue, randomly selected persons identified
as unwell without fatigue (i.e., identified with cognitive impairment,
unrefreshing sleep, muscle pain, joint pain, sore throat, tender lymph
nodes, or headache), and a random sample of people identified as well were
asked to complete a detailed telephone interview. The detailed interview
covered fatigue status and duration, other symptoms, race ("What race do you
consider yourself to be? Please note that you may choose more than one
option. White, black of African American, Asian, American Indian or Alaskan
Native, native Hawaiian or other Pacific islander"), self-identified
Hispanic/Latino or Spanish origin or descent, other demographic
characteristics, and medical history. Based on their responses to the
detailed interview, respondents were classified as: 1) having a medical or
psychiatric condition considered exclusionary for CFS [7]; 2) having CFS-
like illness if they reported severe fatigue lasting 6 months or longer that
was not alleviated by rest, that caused substantial reduction in
occupational, educational, social or personal activities, and that was
accompanied by at least 4 of the CFS case defining symptoms [11]; 3) being
chronically unwell (reporting any of the CFS defining symptoms) with or
without fatigue);, 4) or being well.

Clinical evaluation.
All respondents between 18 and 59 years who had no exclusionary conditions
per interview, and were classified as having a CFS-like illness were invited
for a one- day clinical examination to further investigate exclusionary
medical and psychiatric conditions. We also invited a similar number of
randomly selected participants identified with chronic unwellness (at least
six months of unwellness with or without fatigue but not CFS-like).
Finally, we invited well participants, matched to the CFS-like on geographic
stratum, sex, race/ethnicity and age (within 3 years), for a one-day
clinical examination. Those from the urban or rural areas attended a clinic
in Macon, and those from Atlanta attended a similar clinic in Atlanta. No
more than 4 participants attended a clinic on any day, and appointments were
staggered for optimal flow. Clinic staff with responsibilities for
examinations was not aware of participants' telephone interview responses or
classification. The authors and CDC CFS Research Program staff attended
clinics on a regular basis to assess operations.

Case definitions.
Telephone interview.
Study participants who underwent a detailed telephone interview and met
criteria of the 1994 CFS case definition [11] were classified as CFS-like.
In brief, criteria for classification as CFS-like on telephone included
persistent or relapsing fatigue of at least 6 months' duration; the fatigue
was not relieved by rest and caused substantial reduction in previous levels
of occupational, educational, social, or personal activities. Exclusionary
conditions included self-reported medical or psychiatric conditions that
could cause the fatigue. Finally, the medically/psychiatrically unexplained
fatigue must have been accompanied by at least 4 of the 8 CFS case defining
symptoms [11]: 1) unusual post-exertional malaise; 2) unrefreshing sleep;
3) impaired memory or concentration; 4) headaches; 5) muscle pain; 6) multi-
joint paint without swelling or redness; 7) sore throat; 8) tender
cervical/axillary lymph nodes. CFS-like subjects differ from CFS by not
having been evaluated clinically in the study.

The objective of the clinical evaluation was to classify participants'
clinical status and diagnose exclusionary medical and psychiatric
conditions. As recommended by the International CFS Study Group [7],
participants were classified as CFS, unexplained chronic illness not meeting
criteria for CFS (termed ISF), or well by using standardized reproducible
criteria for measuring specifics of the 1994 case definition [8]. We used
the Multidimensional Fatigue Inventory (MFI) [12] to assess fatigue status.
For classification as CFS, those with a score => well-population medians on
the general fatigue or reduced activity scales of the MFI were considered to
meet fatigue criteria of the 1994 case definition. Functional impairment
was assessed by the medical outcomes survey short form-36 (SF-36) [13].
For classification as CFS, those with a score =< 25th percentile of
population norms in the physical function or role physical, or social
function, or role emotional subscales of the SF-36 were considered to have
substantial reduction in activities as specified in the 1994 definition.
Finally we used the CDC Symptom Inventory (SI) [14] to evaluate occurrence,
frequency and severity of the 8 CFS- defining accompanying symptoms. The
SF-36, MFI and SI domain scores require complete data for the subscales.
We imputed a zero value in the case of one-item non-response for subscales
contributing to the relevant domains. For classification as CFS, those
reporting => 4 case defining symptoms and who scored > 25 on the SI
concerning frequency and severity of the 8 case defining symptoms [14] were
considered to meet accompanying symptom criteria of the 1994 case
definition. Participants who fulfilled some, but not all of these criteria
were classified as ISF. Those who met none of the criteria were considered
to be well. The MFI, SF-36 and SI are self-administered paper and pencil
forms. A trained clinic supervisor reviewed forms and helped subjects
complete missing or misunderstood portions.

To screen for medical conditions considered exclusionary for CFS [11, 7],
participants completed past medical history questionnaires and were
requested to bring all their medications and supplements to the clinic. A
licensed nurse practitioner or physician assistant reviewed subjects' past
medical histories and medications to clarify omissions or discrepancies and
also catalogued all medications. Relevant information was brought to the
attention of the study physicians. A specifically trained licensed physician
then performed a standardized physical examination [3]. The examination was
expanded if there were any concerns. The examiner recorded a differential
diagnosis. Blood and urine specimens were obtained for laboratory screening
tests to identify possible underlying or contributing medical conditions as
stipulated by the case definition [11, 7]. Laboratory tests included a
complete blood count with differential, c-reactive protein, alanine
aminotransferase (ALT), SGPT, albumin, alkaline phosphatase, asparatate
aminotransferase (AST), SGOT, total bilirubin, calcium, carbon dioxide,
chloride, creatinine, glucose, potassium, total protein, sodium, urea
nitrogen BUN, antinuclear antibodies, rheumatoid factor, TSH, free T4, and

To screen for psychiatric conditions considered exclusionary for CFS [11,
7], a trained and experienced licensed psychiatric social worker, clinical
psychologist, psychiatric nurse practitioner or certified psychiatric
research nurse administered the research version of the SCID [15]. They
underwent specific training for the SCID. Psychologists on the CDC CFS
Research Program monitored their technique on a regular basis. The SCID
included the screening module, mood episodes, psychotic symptoms, psychotic
disorders, mood disorders, substance use disorders, anxiety disorders,
somatoform disorders, eating disorders, and adjustment disorders.

A review committee of CDC and Emory University physicians and psychologists
reviewed medical and psychiatric evaluations to determine the presence of
medical and psychiatric conditions exclusionary for CFS. Members of the
review committee were not aware of subjects' classification either on phone
interview or in the clinic.


Prevalence estimates and statistical analyses utilized weighted data. The
survey weights maintained (through the stages of the survey) the relation
between the sample and the population in each geographic stratum, and they
included several adjustments that are customarily employed to reduce bias.
In the process of developing weights, one step adjusted for households that
did not have telephones. To estimate the proportion of households that did
not have a telephone in each of the three geographic strata, we analyzed
data from the 5% public-use microdata samples (PUMS) of the 2000 Census.
For the metropolitan stratum, the analysis used PUMS data from De Kalb and
Fulton Counties. The other two strata, however, do not correspond exactly
to geographic entities for which data are available in the PUMS. Thus, the
analysis for the urban stratum used data from Bibb County; the rural stratum
used data from a larger combination of counties that contained the counties
of that stratum. The resulting estimates of the proportion of households
that did not have a telephone were 1.68% in the metropolitan stratum, 3.66%
in the urban stratum, and 6.35% in the rural stratum.

Adjustments for nonresponse on the detailed telephone interview and
nonresponse on the clinical evaluation kept the categories of illness
separate; thus, to the extent possible, respondents accounted for
nonrespondents who belonged to the same illness category (and shared other
key characteristics). The adjustment factor, applied to the weight of each
respondent, equaled the ratio of the sum of the weights (at that stage) of
respondents and nonrespondents to the sum of the weights of respondents.
Another adjustment, at the household level, used data on interruptions in
telephone service to compensate for the inability of the telephone survey to
reach households that did not have telephone service.

Households completing the screening interview received a base sampling
weight (64.4 in the metropolitan stratum, 6.4 in the urban stratum, and 4.9
in the rural Stratum) equal to the reciprocal of the probability that the
household's telephone number was selected for the sample. Base weights were
reduced for multiple residential telephone numbers in the household (either
by a factor of 2 or a factor of 3) and adjusted for households that did not
complete screening interviews (by a factor of 1.03 in each stratum), for
numbers associated with undetermined residential status (by a factor of 2.4,
2.3, and 2.1, respectively), and for non-telephone households in the
population (by a factor of 1.7, 2.2, and 2.3 for households that reported
interruptions in telephone service and by a factor of 1.24, 1.38, and 1.04
for households that did not report interruptions) [16, 17]. (The household
weights ranged from 66 to 268 in the metropolitan stratum, from 7 to 34 in
the urban stratum, and from 4 to 24 in the rural stratum.)

Subjects selected for detailed interviews received an initial interview
weight equal to their household weight multiplied by the reciprocal of their
probability of selection (the probability of selecting a household as a
source of a subject ranged from 0.32 to 1.0 for unwell subjects and from
0.17 to 1.0 for well subjects; the probability of selecting an individual
subject within the household was the reciprocal of the number of unwell,
respectively well, persons in the household; subjects with prolonged fatigue
were selected with certainty). Within each combination of stratum
(metropolitan, urban, rural) and illness classification (fatigued, unwell,
well), initial weights were adjusted for nonresponse on the detailed
interview, within a total of 195 cells defined by sex, age, and race (the
adjustment factors ranged from 1.05 to 2.25 and exceeded 2.0 in only 22
cells). A further adjustment in each stratum used an iterative form of
post-stratification to bring the weighted totals into agreement with control
totals from the 2000 Census on race and on the combination of sex and age.
This process produced an interview weight for each subject who completed a
detailed interview. (The interview weights ranged from 84 to 16,723 in the
metropolitan stratum, from 5 to 822 in the urban stratum, and from 4 to 892
in the rural stratum.)

Each CFS-like subject who completed a clinical evaluation received a
clinical-evaluation weight, which incorporated an adjustment for nonresponse
on the clinical evaluation within stratum- specific cells defined by sex and
age (over the 19 cells the adjustment factor ranged from 1.11 to 2.71).
For chronically unwell subjects the clinical-evaluation weights incorporated
a parallel adjustment for nonresponse (over the 14 cells the adjustment
factor ranged from 1.52 to 2.61), preceded by an adjustment for selection of
the subsample (by a factor of 3.02, 3.88, and 2.89 in the respective
strata). (The clinical-evaluation weights ranged from 193 to 32,354 in the
metropolitan stratum, from 8 to 1,787 in the urban stratum, and from 10 to
1,358 in the rural stratum.) Because they were selected for clinical
evaluation only as a result of being matched to a CFS-like subject, well
subjects did not have their own clinical-evaluation weight.

Prevalence estimates

Within each stratum, prevalence was estimated using SUDAAN (SUDAAN: Research
Triangle Institute, Research Triangle Park, NC) [18] software to calculate
weighted percentages and obtain standard errors that reflected the sample
design and survey weights. Prevalence estimates based on illness
classifications derived from the detailed interviews used the data of all
subjects who completed detailed interviews, and their respective interview

In order to maintain the relation to the population, prevalence estimates
based on illness classifications derived from clinical data used a
combination of clinical data and interview data. For CFS-like and
chronically unwell subjects who completed clinical evaluations, the data
obtained from the clinical evaluations were used along with their
clinical-evaluation weights. For subjects classified as CFS-like and
chronically unwell who were not eligible for clinical evaluations, and also
for all well subjects, the data obtained from detailed interviews were used
along with their interview weights.

Because the matching process does not preserve a sampling-based connection
with the population, clinical data from well subjects were not used in
calculating prevalence estimates.

Statistical analyses

Weighted chi2 tests in SUDAAN were used to compare proportions of subjects
diagnosed with CFS by demographic categories. P-values were calculated to
evaluate the statistical significance of differences in CFS prevalence by
age, sex, race, ethnicity, education and household income.


Screening telephone interview

Overall, 105,000 telephone numbers were selected for a screening interview;
66,295 (63%) were ineligible because they belonged to businesses, were not
working, or were cellular phones. Residential status could not be
determined for 24,594 (23%) of the numbers -- 2,136 (2%) because all
attempts produced no contact, 4,258 (4%) because attempts reached only an
answering machine, and 18,200 (17%) because of another outcome (primarily
the person refused to participate before household status could be
determined). A total of 2,864 numbers (3%) belonged to households where
all residents were over the age of 59; these households were not eligible
for the study. The remaining 11,247 numbers (11%) were residential and
eligible for screening. We completed screening telephone interviews for
10,837 of the identified residential numbers (96% participation). Taking
into account estimated numbers of age-eligible households among the
telephone numbers for which residential status could not be determined and
among the households for which screening was not completed, the response
rate for the screening step was 79%. There were no important differences in
response across the strata (range 76.1% to 81.4%).

The screening interviews enumerated 19,381 residents. Of these, 10,834
(56%) were identified by the household informant as well, 5,122 (26%) as
unwell for at least a month but not fatigued, and 3,425 (18%) as unwell and
fatigued for at least a month. We attempted to conduct detailed telephone
interviews on all those who were unwell with fatigue, and 2,438 (71%)
completed the detailed interview. We randomly selected 2,134 of those who
were unwell not fatigued, and 1,429 (67%) completed detailed interviews;
similarly, 1,756 (56%) of 3,113 randomly selected household members
identified as well completed detailed telephone interviews. There were no
important differences in detailed interview completion across the strata
(range 66.8% to 72.6%)

Telephone interview sample

Individuals' responses during the detailed telephone interview roughly
mirrored the household informants' classification (Table 1). For example,
65% of those described as well by household informants during the screening
interview, described themselves as `well' during the detailed interview.
Similarly, 69% of those described as unwell not fatigued by household
informants, described themselves as unwell not fatigued. A smaller
proportion (49%) of those who were initially described as unwell fatigued by
household informants described themselves as unwell with fatigue during the
detailed interview. Following the detailed telephone interview 1,513
respondents were classified as well, 1,803 as unwell for at least a month
but not fatigued, 1,400 as unwell with fatigue, and 907 as CFS-like, meaning
that they fulfilled all criteria of the 1994 case definition [11] on
telephone interview.

Responses during the detailed telephone interview identified a self-reported
medical or psychiatric explanation for the illness in 438 (48%) of CFS-like
participants, 558 (40%) of those unwell with fatigue, and 429 (24%) of those
who were unwell but not fatigued. Interestingly, 184 (12%) of participants
classified as well reported medical and psychiatric conditions and these
were in general the same as those reported by participants with CFS-like
illness and those who were unwell.

Clinic sample

We invited all 469 individuals with CFS-like illness and no
medical/psychiatric exclusions for a clinical evaluation, and 292 (62%)
agreed to participate. Those who did not come for a clinical evaluation
were similar to those who did with regard to age, sex, income, and duration
of illness. We randomly selected 505 from the 1,763 identified as
chronically unwell (=> 6 months duration with or without fatigue) and
invited them to clinic; 268 (53%) participated. Finally, we selected 641
interview participants classified as well (n=481) or prolonged unwell, i.e.
unwell for 1 to 6 months duration (n=160). These were matched to the
CFS-like on sex, race, and age (within 3 years). A total of 163
participants classified as well and 60 who were classified as prolonged
unwell completed clinical evaluations. As with telephone interviews, there
were no important differences in clinical evaluation participation across
the three strata, either overall or by classification status.

Clinical evaluation identified a medical or psychiatric exclusion in 26
(16%) of those classified as well based on their detailed telephone
interview responses, 24 (40%) of those with prolonged unwellness, 44 (30%)
of the chronically unwell not fatigued, 45 (38%) of the chronically unwell
fatigued, and 141 (48%) of the CFS-like. The most frequent medical
exclusions included previously undiagnosed thyroid disease (24% of the
total), anemia (18%), uncontrolled diabetes (14%), autoimmune disease (11%),
inflammatory disease (8%), heart disease (7%), arthritis (3%) and pulmonary
disease (3%). Psychiatric exclusions encompassed alcohol or substance abuse
(43%), melancholic depression (26%), bipolar disorder (19%), psychosis (7%),
and anorexia/bulimia (5%). One subject enrolled with chronic unwellness and
one CFS-like subject had incomplete medical or psychiatric evaluations and
could not be classified.

Table 2 summarizes the relation between classification following detailed
telephone interview and clinic classification among the 501 study subjects
who did not have an exclusionary condition. One hundred-thirteen met
criteria for CFS, 264 had an unexplained illness (ISF), and 124 were well.
Interestingly, 53 (39%) of those who were classified as well based on their
telephone interview data were classified as ISF (insufficient symptoms or
fatigue for CFS) or CFS when evaluated in clinic, while 26 (15%) of those
enrolled as chronically unwell based on telephone interview had no evidence
of unwellness when evaluated in clinic.

Prevalence estimates

Table 3 summarizes prevalence of CFS in metropolitan, urban and rural
populations according to demographic characteristics. Overall, 2.54% of the
study populations had CFS; 83% reported gradual onset and 17% reported
sudden onset of their illness. There were no statistically significant
differences in prevalence of CFS among metropolitan, urban, and rural
populations among women (p=.37). However, among men, CFS prevalence varied
significantly among geographic strata, and was lowest in the metropolitan
stratum (p=.038). In the metropolitan area, the CFS prevalence in women
was 11.2 times that in men (p=.009), whereas in the urban and rural
populations the female-to-male ratios of CFS prevalence were 1.7 and 0.8,
respectively, and did not represent statistically significant differences.

Overall, white and black adults had roughly similar rates (2.3% and 2.9%,
respectively). Although Hispanic adults in metropolitan and rural
populations had considerably higher prevalence than non-Hispanic, the
numbers of Hispanics interviewed were low (23 in the metropolitan area, 38
urban, and 59 rural), and the differences were not statistically

Age-specific prevalence of CFS differed among age categories in urban and
rural populations (p=.041 and p=.0001, respectively), but not in
metropolitan (p=.224). The rate was lowest among urban and rural adults
aged 18-29 and highest among rural adults aged 50-59.

The prevalence of CFS was not significantly related to level of education in
metropolitan, urban or rural strata (p=.129, p=.486, and p=.695,
respectively). Similarly, CFS prevalence was not significantly related to
household income in these strata (p=.741, p=.900, and p=.373, respectively).


This is the first published study, of which we are aware, that screened
defined populations for unwellness and then used standardized, validated
instruments to define CFS, unwellness, and wellness based on functional
impairment, characteristics of fatigue, and frequency/severity of the 8 case
defining symptoms [7]. Using this approach, we found 2.54% of the Georgia
population to suffer from CFS, which was 10-fold higher than previous
estimates in the population of Wichita (0.24%) [3] and 6-fold higher than
estimated in the Chicago population (0.42%) [5]. We are aware of no other
published population-based surveys of CFS. However, several studies have
published estimates of CFS prevalence; although they cannot be directly
compared to the 2 U.S. studies, their prevalence estimates serve to put the
present study into a more complete perspective. A well-conducted survey of
the Group Health Cooperative of Puget Sound estimated that between 0.75 and
0.27% of that HMO population had CFS [19]. A survey of primary care
patients in England, published in 1997, estimated that 2.6% of that
population met criteria for CFS [20]. Finally, analysis of data from the
Australian National survey of Mental Health and Wellbeing estimated that
1.5% of the Australian adult population suffers from chronic neurasthenia
(defined similarly to CFS) [21].

In part, the increased prevalence we estimated in Georgia reflects a
difference in screening criteria. The Georgia survey screened for unwell
(the core symptoms of CFS), whereas previous studies have screened only for
fatigue. Our less restrictive approach allowed the inclusion of potential
cases whom, although noted as unwell-not fatigued by a household informant,
endorsed chronic fatigue upon detailed in-person interviewing. Sixty-nine
people whom the household informant identified during the screening
telephone interview as well or unwell without fatigue were classified as
CFS-like based on their responses during detailed telephone interview (7.6%
of all CFS-like). Further, 13 clinic participants classified as well or
unwell without fatigue, based on their detailed telephone interview were
diagnosed as CFS when evaluated clinically. In other words, 11.5% of
subjects with CFS would not have been detected in previous studies that
queried participants only for fatigue.

The 6- to 10-fold greater prevalence estimates also reflect application of
more sensitive and specific measures of the CFS diagnostic parameters
specified by the 1994 case definition. Previous prevalence estimates from
population surveys and those based on patients attending clinics did not use
validated standardized instruments to define CFS; rather they simply queried
as to the presence or absence of fatigue, accompanying symptoms, and
impairment. In 2003, the International Chronic Fatigue Syndrome Study Group
published recommendations concerning application of the case definition [7].
They recommended the use of validated instruments to obtain standardized
measures of the major symptom domains of the illness, and this study
implemented those recommendations. The Study Group specifically
recommended: 1) the SF-36, to measure functional impairment; 2) the
Checklist Individual Strength or MFI, to obtain reproducible quantifiable
measures of fatigue; 3) and the CDC Symptom Inventory to document toe
occurrence, duration and severity of the symptom complex. The manner in
which we applied the case definition in Georgia has been shown to detect
about 3 times the number of CFS cases as verbatim application of the 1994
definition [8]. Of course, we cannot exclude the possibility that CFS
prevalence may be higher in Georgia than Wichita and Chicago.

However, the manner in which we chose and applied subscales and their
cutoffs from the SF-36 and MFI can be debated. We used the SF-36 physical
function, role physical, social function and role emotional subscales to
define an illness severe enough to "result in substantial reduction in
previous levels of occupational, educational, social, or personal
activities." [11]. In particular, we included the role emotional subscale
to capture the relation between functional emotional impairment and reduced
social and personal activities. We ascertained the onset and duration of
fatigue during interview (the case definition requires => 6 months of
fatigue that is of new or definite onset) and utilized the MFI general
fatigue and reduced activity scales to define severe fatigue. We used
stringent (i.e., =< 25th percentile population norms on any of the 4 SF-36
scales) to define severe functional impairment. Numerous publications
tabulate slightly different population norms and we chose those published by
Quality Metric [22]. We are not aware of published population norms for the
MFI, so we used the cut-offs established in a previous CDC study (=> than
the median determined in Wichita) [8], which is more sensitive and less
specific than the 25th percentile SF-36 cutoff. There are no population
norms for the Symptom Inventory, so we also used cutoffs applied in the
previous study. Finally, population norms are not cast in iron and one
might consider defining cut-offs specific to each population studied. In
the end, we decided to use these cutoffs because we believe they make sense;
because we used them in the Wichita study and can compare findings in
similarly ill individuals; and, because others can replicate the findings if
they use the same cutoffs and stratify their populations based on variations
of the cutoffs..

The other important new finding is that, despite differences in demographic
factors, CFS prevalence was similar in the metropolitan, urban, and rural
populations we surveyed (about 2.5%). However, differences in sex-specific
prevalence among the strata must be evaluated in more detail. The striking
differences between female and male rates in the 3 strata may indicate risk
effects of gender (a social construct) in distinction to sex (a biologic
attribute). In addition, the high prevalence among those of Hispanic
ethnicity in the metropolitan area bears further investigation in a study
designed to include Spanish-speaking persons.

The final major finding concerns the high proportion of study participants
in whom the survey documented previously undiagnosed medical or psychiatric
conditions. Overall 48% of persons recruited for clinical evaluation
because CFS-like illness was identified on phone interview had exclusionary
medical or psychiatric conditions, which is similar to the occurrence of
such illness in other studies [2, 3]. Most of these exclusions are amenable
to treatment if appropriately recognized. It is also important to note the
relatively common occurrence of such conditions in people with other
categories of unwellness identified during the phone interview. Indeed, 16%
of respondents classified as well on the basis of interview had such
exclusions identified. Further analyses will address whether the onset of
psychiatric illness preceded or followed development of CFS-like illness.

Interpretation of the findings must consider obvious study weaknesses.
First, like other telephone surveys, we faced challenges of nonresponse.
Potential respondents can be lost in the processes of determining whether
telephone numbers belong to households, completing screening interviews with
household respondents, and maintaining contact with selected subjects to
complete detailed interviews. In addition, some people are reluctant to
schedule a full-day clinical examination. A random-digit-dialing survey
that subsamples some types of subjects does not have a standard,
single-number response rate. Taking into account the resolution of sampled
telephone numbers (as residential or not), completion of screening
interviews, and completion of detailed interviews, we calculated a response
rate of 47.8% through the detailed interview. A further calculation,
including the completion of clinical evaluations by subjects with CFS-like
illness and chronically unwell subjects, produced a response rate of 27.5%
through the clinic stage. Although nonresponse is always an appropriate
subject for concern, detailed adjustments in the sampling weights often are
able to mitigate its adverse effects. Thus, the adjustment for nonresponse
on the detailed interview used a total of 195 cells, taking into account
stratum, illness classification, sex, age, and race; post-stratification
aligned respondents' weights with population totals; and the adjustment for
nonresponse on the clinical evaluation used a total of 33 cells based on
stratum, illness classification, sex, and age.

The second weakness concerns obtaining clinical information by telephone
interview. Initial classification of subjects as well, unwell not fatigued,
and unwell fatigued based on telephone interviews with household informants
was confirmed by detailed interviews in 65%, 69% and 49% of subjects in
those respective categories. Except for the unwell fatigued group, these
levels of agreement between household informants and self-reports were
similar to the 66% agreement detected in a study designed to examine
concordance between self-reported health conditions and proxy information
among adults => 65 years of age in the United Kingdom [23]. This degree of
agreement was considered reasonable. The lower level of agreement detected
among the unwell fatigued may be due to the relative nonspecificity of
fatigue, compared to other symptoms of unwellness, including problems with
memory/concentration, unrefreshing sleep, or muscle/joint pain.

Third, the study was conducted in standard 8th grade-level English, which
may have led to an under-sampling of ethnic minority groups (e.g., Spanish
speaking). Prevalence of CFS was unusually high among the metropolitan and
rural Hispanic populations and unusually low among rural Hispanic residents.
This may reflect important ethnic differences in risk [2] and we weighted
the sample to allow for ethnic differences. Most likely it reflects
language-related misunderstanding of the questions and weighting cannot
address this. It will be important to further evaluate the occurrence of
and risk factors for CFS in English and non-English speaking metropolitan,
urban, and rural Hispanic populations [24].

Fourth, the study utilized Atlanta (Fulton and DeKalb counties) to represent
metropolitan Georgia, Macon and Warner Robins to represent urban Georgia,
and the counties surrounding the urban area to represent rural Georgia. We
did this for logistic reasons, and the results cannot a- priori be
generalized to other populations. Indeed, populations of the 10 rural
county seats varied from 587 to 19,000 (median 2,000), so several exceeded
the Census Bureau definition of rural.

Finally, in spite of a rigorous case definition, CFS has no diagnostic
markers or characteristic physical signs. Thus, CFS diagnosis is based on
self-reported symptoms, disability and exclusion of known diseases.
Therefore, potential misclassification of study subjects remains a concern,
as CFS is clinically heterogeneous and likely represents more than one
entity [25, 26].


In conclusion, this investigation suggests that 2.54% of the adult
population of Georgia suffers from CFS. This figure is 6- to 10-fold higher
than previous prevalence estimates and likely reflects improved screening
methods and more sensitive and specific diagnostic criteria. However, this
is the first study to measure CFS prevalence in Georgia, so we cannot rule
out the possibility that CFS prevalence is higher in Georgia than other
geographic areas where CFS prevalence has been reported. We did not find
evidence for metropolitan, urban, rural differences in the prevalence of
CFS, nor did we find differences in prevalence between white and black
populations. These findings are important for public health officials,
health care providers, and the public in general. The methodology and
findings from this study should be of interest to those studying CFS and
those with responsibilities for health care in other states in the US and in
other countries.

Competing interests

The authors declare that they have no competing interests.

Authors' Contributions

WCR was Principal Investigator of the study. WCR, EM, CH, RB, JFJ designed
the study and wrote the protocol. DCH was responsible for sampling strategy
and statistical analysis. WCR, CH, EM, RSB, JFJ supervised fieldwork. MM
and RD supervised technical aspects of the study and supervised daily phone
interviews and clinic operations. All authors contributed to preparation of
the manuscript.


This study was fully funded by the US Centers for Disease Control and
Prevention. We acknowledge Dr. Jin-Mann Lin for her statistical review of
this manuscript.

The findings and conclusions in this report are those of the authors and do
not necessarily represent the views of the funding agency.


Table 1. Screening Interview Classification
Detailed Interview               Well           Unwell not   Unwell Fatigued
Classification                   n=1,756        Fatigued     n=2,438
Well                (n=1,513)    1,141 (65%)    242 (17%)      130  (5%)
Unwell not Fatigued (n=1,803)      545 (31%)    982 (69%)      276 (11%)
Unwell Fatigued     (n=1,400)       57  (3%)    149 (10%)    1,194 (49%)
CFS-like            (n=907)         13  (1%)     56  (4%)      838 (34%)
(%) indicates column percent

Table 2. Clinic Classification of Participants with No Exclusionary Conditions
                                    Clinic Classification
Detailed Interview                  Well         ISF            CFS
Classification                      n=124        n=264          n=113

Well                (n=137)         83 (61%)     53 (39%)        1 (1%)
Prolonged Unwell    (n=36)          15 (42%)     19 (53%)        2 (6%)
Unwell not Fatigued (n=104)         20 (19%)     74 (71%)       10 (10%)
Unwell Fatigued     (n=74)           6  (8%)     52 (70%)       16 (22%)
CFS-like            (n=150)          0  (0%)     66 (44%)       84 (56%)
(%) indicates row percent

Table 3. Prevalence of CFS (in percent) by Demographic Characteristics in the
         Three Populations
                                 Metropolitan     Urban          Rural
                                    %      (SE)   %     (SE)     %     (SE)
Overall prevalence                   2.55  (0.85) 2.48  (0.67)   2.66  (0.58)
   Female                            4.70  (1.60) 3.10  (0.81)   2.40  (0.57)
   Male                              0.42  (0.37) 1.82  (1.08)   2.89  (0.97)
   White                             3.72  (1.71) 2.39  (0.70)   3.20  (0.72)
   Black                             1.78  (0.63) 2.71  (1.27)   1.71  (1.00)
   Hispanic                         21.21 (11.97) 7.02  (6.74)   0.70  (0.71)
   Non-Hispanic                      2.25  (0.82) 2.30  (0.64)   2.72  (0.59)
   18-29                             4.15  (2.28) 0.54  (0.29)   0.00
   30-39                             0.74  (0.43) 5.59  (2.40)   2.68  (1.06)
   40-49                             2.64  (1.34) 2.38  (0.83)   2.08  (0.77)
   50-59                             2.11  (1.13) 1.74  (1.09)   6.88  (2.17)
   =< High School Graduation         0.00         1.02  (0.73)   2.48  (1.10)
   High School Graduate              1.60  (1.24) 2.54  (1.02)   3.80  (1.34)
   Technical or Some College         2.02  (1.01) 3.05  (1.60)   2.33  (1.15)
   => College Graduate               3.44  (1.47) 2.60  (1.25)   1.97  (0.72)
Household Income
   =< $20,000                        4.85  (4.01) 1.87  (1.06)   1.87  (0.83)
   $20,001-$40,000                   3.43  (2.49) 2.89  (1.57)   4.72  (1.70)
   >$41,000                          1.60  (0.61) 2.79  (1.19)   2.25  (0.80)
Poverty Level
   =< $20,000                        4.85  (4.01) 1.87  (1.06)   1.87  (0.83)
   > $20,001                         2.09  (0.80) 2.82  (0.95)   3.09  (0.79)


 1. Reynolds KJ, Vernon SD, Bouchery E, Reeves WC: The economic impact of
    chronic fatigue syndrome. Cost Effectiveness Resource Allocation 2004,
 2. Jason LA, Taylor RR, Kennedy CL, Song S, Johnson D, Torres S: Chronic
    fatigue syndrome: occupation, medical utilization, and subtypes in a
    community-based sample. J Nerv Ment Dis 2000, 188:568-76.
 3. Reyes M, Nisenbaum R, Hoaglin DC, Unger ER, Emmons C, Randall B, Stewart
    JA, Abbey S, Jones JF, Gantz N, Minden S, Reeves WC: Prevalence and
    incidence of chronic fatigue syndrome in Wichita, Kansas. Arch Int Med
    2003, 163:1530-1536.
 4. Steele L, Dobbins JG, Fukuda K, Reyes M, Randall B, Koppelman M, Reeves
    WC: The epidemiology of chronic fatigue in San Francisco. Am J Med
    1998, 105(3A):83S-90S.
 5. Jason LA, Richman JA, Rademaker AW, Jordan KM, Plioplys AV, Taylor RR,
    McCready W, Huang CF, Plioplys S: A community-based study of chronic
    fatigue syndrome. Arch Int Med 1999, 159:2129-2137.
 6. Bierl C, Nisenbaum R, Hoaglin DC, Randall B, Jones AB, Unger ER, Reeves
    WC: Regional distribution of fatiguing illnesses in the United States: a
    pilot study. Population Health Metrics 2004, 2:1.
 7. Reeves WC, Lloyd A, Vernon SD, Klimas N, Jason LA, Bleijenberg G,
    Evengard B, White PD, Nisenbaum R, Unger ER: Identification of ambiguities
    in the 1994 chronic fatigue syndrome research case definition and
    recommendations for resolution. BMC Health Services Research 2003, 3:25.
 8. Reeves WC, Wagner D, Nisenbaum R, Jones JF, Gurbaxani B, Solomon L,
    Papanicolaou DA, Unger ER, Vernon SD, Heim C: Chronic fatigue syndrome
    - a clinically empirical approach to its definition and study. BMC Medicine
    2005, 3:16.
 9. Lepkowski JM: Telephone sampling methods in the United States. In
    Telephone Survey Methodology, (Eds. R. M. Groves et al.), New York: John
    Wiley & Sons, Inc., pp. 73-98. 1988.
10. Link MW, Mokdad A: Advance letters as a means of improving respondent
    cooperation in random digit dial studies. Public Opinion Quarterly
    2005, 69:572-587.
11. Fukuda K, Straus SE, Hickie I, Sharpe M, Dobbins JG, Komaroff A: The
    chronic fatigue syndrome: a comprehensive approach to its definition and
    study. Ann Int Med 1994, 121:953-959.
12. Smets EMA, Garssen B, Bonke B, De Haes JC: The Multidimensional Fatigue
    Inventory (MFI) psychometric qualities of an instrument to assess fatigue.
    J Psychosom Res 1995, 39:315-325.
13. Ware JE, Jr., Sherbourne CD: The MOS 36-item short-form health survey
    (SF-36). I. Conceptual framework and item selection. Med Care 1992,
14. Wagner D, Nisenbaum R, Heim C, Jones JF, Unger ER, Reeves WC:
    Psychometric properties of the CDC symptom inventory for the assessment
    of chronic fatigue syndrome. Population Health Metrics 2005, 3:8.
15. First MB, Spitzer RL, Gibbon M, Williams JBW: Structured Clinical
    Interview for DSM- IV-TR Axis I Disorders, Research Version. New York:
    Biometrics Research, New York State Psychiatric Institute. 2002.
16. Massey JT, Botman SL: Weighting adjustments for random digit dialed
    surveys. In Telephone Survey Methodology, (Eds. R. M. Groves et al.), New
    York: John Wiley & Sons, Inc., pp. 143-160. 1988.
17. Frankel MR, Srinath KP, Hoaglin DC, Battaglia MP, Smith PJ, Wright RA,
    Khare M: Adjustments for non-telephone bias in random-digit-dialling
    surveys. Statistics in Medicine 2003, 22:1611-1626.
18. Research Triangle Institute: SUDAAN Language Manual, Release 9.0.
    Research Triangle Park, NC: Research Triangle Institute. 2004
19. Buchwald D, Umali P, Umali J, Kith P, Pearlman T, Komaroff AL. Chronic
    fatigue and the chronic fatigue syndrome: prevalence in a Pacific
    northwest health care system. Ann Intern Med 1995, 123:81-88.
20. Wessely S, chalder T, Hirsch S, Wallace P, Wright D. The prevalence and
    morbidity of chronic fatigue and chronic fatigue syndrome: a prospective
    primary care study. Am J Pub Health 1997, 87:1449-1455.
21. Hickie I, Davenport T, Issakidis C, Andrews G. Neurasthenia:
    prevalence, disability and health care characteristics in the Australian
    community. Brit J Psychiatry 2002, 181:56-61.
22. Ware JE, Snow KK, Kosinski M, Gandex B. SF-36 Health Survey: Manual and
    Interpretation Guide. Lincoln, RI: Quality Metric, Inc, 1993, 2000.
23. Dewey ME, Parker CJ and the Analysis Group of the Medical Research
    Council: Cognitive Function and Ageing Study. Survey into health problems
    of elderly people: multivariate analysis of concordance between self-report
    and proxy information. Int J Epidemiol 2000, 29:698-703.
24. Skapinakis P, Lewis G, Mavreas V. Cross-cultural differences in the
    epidemiology of unexplained fatigue syndromes in primary care. Brit J
    Psychiatry 2003, 182:205-209.
25. Vollmer-Conna U, Aslakson E, White PD. An empirical delineation of the
    heterogeneity of chronic unexplained fatigue in women. Pharmacogenomics
    2006, 7:355-364.
26. Broderick G, Craddock RC, Whistler T, Taylor R, Klimas N, Unger ER:
    Identifying illness parameters in fatiguing syndrome using classical
    projection methods. Pharmacogenomics 2006, 7:407-419.

(c) 2007 BioMed Central Ltd

[Return to top]


Date:    Thu, 21 Jun 2007 12:11:59 +0100
From:    Tom Kindlon <tomkindlon OCEANFREE.NET>
Subject: RES: More symptoms could be added to a CFS Symptom Inventory

In response to:
Psychometric properties of the CDC Symptom Inventory for assessment of
Chronic Fatigue Syndrome
Dieter Wagner, Rosane Nisenbaum, Christine Heim, James F Jones, Elizabeth R
Unger and William C Reeves
Population Health Metrics 2005, 3:8     doi:10.1186/1478-7954-3-8

More symptoms could be added to a CFS Symptom Inventory

Tom Kindlon   (21 June 2007)

Many would feel that the 8 symptoms used in the CDC '94 definition [1] were
chosen in a somewhat arbitrary fashion; so it is to be welcomed that the CDC
itself has started to look beyond these symptoms with the CDC CFS Symptom
Inventory. The idea of a Short Form of the CDC Symptom Inventory is also

However, it is not clear to me where the extra symptoms that are on the CDC
CFS Symptom Inventory came from. For example, I didn't see some of the
symptoms listed in Reeves et al [2].

In 2001, De Becker et al [3] published data on the symptoms found in over
2500 patients. They tried to improve on the 1988 [4] and 1994 CDC criteria.
They suggested a list of symptoms that could be used to strengthen the
ability to select ME/CFS patients. Many of the symptoms they mentioned are
not in the CDC CFS Symptom Inventory. So to claim that the "CDC Symptom
Inventory assesses the full range of CFS associated symptoms" seems

It would be interesting if in future these symptoms (that De Becker et al
were suggesting) were added before statistical analyses are performed.

The fatigue criteria and functional impairment criteria have become much
less restrictive [5]. For example, to satisfy the fatigue criteria, the
fatigue is required to be greater than or equal to the medians of the MFI
general fatigue (? 13) or reduced activity (? 10) scales. So it now seems
particularly important that the symptom criteria have good sensitivity and
specificity or one is going to end up with a definition that leads to very
heterogeneous samples.

Tom Kindlon

[1] Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A: The
chronic fatigue syndrome; a comprehensive approach to its definition and
Ann Int Med 1994, 121:953-959.

[2] Reeves WC, Lloyd A, Vernon SD, Klimas N, Jason LA, Bleijenberg G,
Evengard B, White PD, Nisenbaum R, Unger ER, International Chronic Fatigue
Syndrome Study Group: Identification of ambiguities in the 1994 chronic
fatigue syndrome research case definition and recommendations for
BMC Health Services Research 2003, 3:25.

[3] A definition-based analysis of symptoms in a large cohort of patients
chronic fatigue syndrome, P. De Becker, N. McGregor, and K. De Meirleir.
Journal of Internal Medicine 2001;250:234-240

[4] Holmes GP, Kaplan JE, Gantz NM, Komaroff AL, Schonberger LB, Straus SE,
et al.: Chronic fatigue syndrome: a working case definition. Ann Intern Med
1988, 108:387-389.

[5] Reeves WC, Wagner D, Nisenbaum R, Jones JF, Gurbaxani B, Solomon L,
Papanicolaou DA,
Unger ER, Vernon SD, Heim C: Chronic fatigue syndrome - a clinically
empirical approach
to its definition and study. BMC Medicine 2005, 3:16.

The latest prevalence study only appears to use the 8 original CDC criteria.
However perhaps in the future the CDC will use the 19-symptom scale used in
this study or the Symptom Inventory Short Form (6 symptoms).

This study suggests that the 8 symptoms currently being used correlate with
the 19 symptoms score.  However if different or more symptoms had been used,
the correlation might have been weaker.  Also if different symptoms had been
used as part of the full inventory, the Short Form may have had different

My concern would be that any future CDC definition would not learn from the
Canadian definition or the research that informed it.

Here's an extract from the Canadian Guidelines with information on the De
Becker study:

"Since the development of our clinical criteria, we have had an opportunity
to review the analysis of symptoms in over 2,500 patients by De
Becker et al. (45). They found that the Holmes definition (42) of fatigue,
swollen/tender lymph nodes, sore throat, muscle weakness, recurrent
flu-like symptoms, post-exertional fatigue, myalgia, memory
disturbance, nonrestorative sleep and replacing low-grade fever with
hot flashes; and the addition of ten other symptoms (attention deficit,
paralysis, new sensitivities to food/drugs, cold extremities, difficulties
with words, urinary frequency, muscle fasciculations, lightheadedness,
exertional dyspnea and gastrointestinal disturbance) strengthen the ability
to select ME/CFS patients. Based on this study, we added exertional
dyspnea and muscle fasciculations to our clinical definition. All the
symptoms which the De Becker et al. study (45) recommended adding
to strengthen the ability to select ME/CFS patients are in our definition
except paralysis, which the panel did not consider prevalent enough for
inclusion in a clinical definition. The clinical definition has additional
symptoms, such as orthostatic intolerance, which we feel are important
in a clinical setting."

Tom Kindlon

[Return to top]


Date:    Fri, 22 Jun 2007 00:52:24 +0200
From:    Jan van Roijen <j.van.roijen CHELLO.NL>
Subject: med: Link Between Autism & Lyme Disease


Send an Email for free membership
       >>>> Help ME Circle  <<<<
 >>>>       22 June 2007        <<<<
Editorship : j.van.roijen chello.nl
Outgoing mail scanned by Norton AV

See also: *Lyme & herpes in ME/CFS*
Help ME Circle, 20 June 2007; at Co-Cure:




NEWSWIRE   2007-06-21

New Data Supporting the Link
Between Autism and Lyme Disease

The LIA foundation plans to release new data at the
Lyme-Autism Connection conference this weekend linking
Autism and Lyme disease.

"At this conference, we have presenters
who will show that this connection is real"

Corona, CA (PRWEB) June 20, 2007 -- News reports indicate a
staggering number of Lyme disease cases going unreported.
With autism rates rising each year, doctors are examining this
new connection.

With new CDC numbers showing one of the largest populations
of Lyme disease sufferers being boys from the age of 5-14, this
rings of déjB vu to parents of children with autism. Young boys
are the largest category of victims of autism as well as Lyme
disease, which is caused by a bacteria called Borrelia
Burgdorferi. Interestingly, the symptoms of chronic Lyme
disease when affecting the central nervous system are literally
the same symptoms as autism spectrum disorder.

The LIA Foundation will hold its first conference this week in
Irvine, CA, in which new data will be released supporting this
connection. "It's time that parents and doctors start looking
outside the box as to why these children are so sick," comments
co-founder of the LIA Foundation, Tami Duncan. "At this
conference, we have presenters who will show that this
connection is real."

"The increasing incidence of autism spectrum disorder (560,000
in the US) is a serious threat to our children and in most cases
the cause is still unknown. Some clinicians and parents have
noted chronic infections, including tick-borne infections;
including Lyme disease and the immune reactions to these
infections are sometimes associated with autistic symptoms
and autistic spectrum disorder. This meeting will review the data
regarding this observation and possible explanations of this
association with a goal to help reduce any preventable cases of
autism spectrum disorder," states Robert Bransfield, M.D. of
Red Bank, NJ.

Doctors are beginning to support this link. Joseph Burrascano,
M.D., the Vice President of ILADS (International Lyme and
Associated Disease Society) states his position on Lyme
disease and Autism. "It is my contention that Autism is an
inflammatory encephalitis cause by a pathogen such as
Bartonella or Mycoplasma. I share the view that Bartonella is a
major infection that may eclipse Borrelia Burgdorferi as the
ultimate cause of the morbidity in chronic Lyme disease.
Mycoplasma too is a major concern of mine- in reviewing my
7000+ cases, those patients who were relentlessly chronic, all at
one point or another in their illness, were positive for

In fact, one speaker at the conference, Professor Garth
Nicholson of the Institute for Molecular Medicine has found that
58% of children with Autism spectrum disorder are also
harboring multiple-infections, specifically Mycoplasma. "Since
these chronic infections like Borrelia, Mycoplasma and
Bartonella are known to suppress the immune system, it is not a
stretch to assume that when the child was injected with obscene
amounts of mercury, that his fate of having an autism diagnosis,
would become reality," Duncan states.

Proof is on the way, with data to be released at the Lyme-Autism
Connection Conference this weekend and studies in progress,
parents and doctors can be sure to hear more about this in the
coming months.

Conference information is available online at
www.liafoundation.org . It is going to be held at the Hyatt
Regency in Irvine, CA, June 22 - 24th. Registration is available
at the door.

About Autism

Autism is a disorder that currently affects 1 out of 150 children.
Boys are the majority of those affected. The numbers of autism
cases spiked in the mid-late 90's and continues to remain high.
The exact cause of autism is still unknown, however, many
theories exist. Most children do improve with some sort of
bio-medical intervention.

About Lyme disease

Lyme disease is generally caused by a tick bite in which the tick
transmits a bacteria called Borrelia Burgdorferi. Symptoms of
Lyme disease include, achy joints, confusion, slurring words or
word retrieval problems, brain fog, sensitivity to light and sound.
Lyme disease in its late stage can be fatal, causing MS like
symptoms and debilitating its victims. Treatment for Lyme
disease consists of antibiotic therapy.

About the LIA Foundation

The foundation was started in September 2006 by parents of
children with autism and Lyme disease. Kathy Blanco of
Beaverton, OR and Tami Duncan of Corona, CA are the
founders. The foundations' goals are to educate families and
physicians on the link between Lyme and autism, bring
physicians together to form a consensus for testing and
treatment options and to provide funding for research studies
related to autism and/or Lyme disease.

Contact information:
Tami Duncan
LIA Foundation
1771 Honors Lane
Corona, CA 92883
(951) 817-1173


Date:    Thu, 21 Jun 2007 22:24:14 -0400
From:    "connie <connie.nelson@NTLWORLD.COM> [via Co-Cure Moderators]"
Subject: ACT,NOT,MED:Cochrane on trial

Margaret Williams notes that the "bible" of "evidence-based" medicine -- the

Cochrane Collaboration -- has been exposed in this article as being
corrupted by money and vested interests. It will be recalled that Professor
Simon Wessely is responsible for Cochrane entries on ME/CFS.  It will also
be recalled that the York Systematic Review relied heavily on Cochrane data
in its work upon which the NICE draft Guideline on "CFS/ME" is founded.

Evidence-Based Medicine and the Cochrane Collaboration on Trial

David K. Cundiff, MD
Medscape General Medicine.  2007;9(2):56.  ©2007 Medscape
Posted 06/12/2007

The Cochrane Collaboration was founded in 1993 and was named for the British
epidemiologist Archie Cochrane, MD (1908-1988). At the initiation of the
National Health Service in the 1940s in the United Kingdom, Dr. Cochrane
suggested that the free care in the National Health Service should be
limited to interventions supported by evidence of their effectiveness. This
was a very innovative thought in the 1940s. Dr. Ian Chalmers, the driving
force behind the Cochrane Collaboration, was strongly influenced by the
writings of Archie Cochrane.

Most physicians perceive that "evidence-based medicine" means practicing
medicine by using tests and treatments that have been vetted by randomized
controlled clinical trials (RCTs) to prove that they work. Although the
Cochrane Collaboration focuses mainly on systematic reviews of RCTs, it also
addresses issues specific to reviewing other types of evidence when

Bernadine Healy, MD, former Director of the National Institutes of Health,
wrote an essay entitled "Who Says What's Best?"; the piece, critical of
evidence-based medicine, appeared on September 11, 2006 in US News and World
Report.[2] Kay Dickersin, PhD, the Director of Cochrane's US Center for
Clinical Trials, asked me and other Cochrane Collaboration evidence-based
medicine reviewers to respond by sending op-ed pieces to the media.

I agree with many of the points made by Dr. Healy. She writes that the rigid
adherence to RCTs as the only valid form of scientific evidence about
medical tests and treatments unfairly excludes other ways of determining
what medical interventions will best serve an individual patient with a
particular health problem. Dr. Healy put it succinctly: "The autonomy and
authority of the doctor, and the subsequent variability in care, are the
problems that evidence-based medicine wants to cure."

While I concur with Dr. Healy that relying solely on evidence-based medicine
to determine medical guidelines better suits the needs of governments and
insurance companies for cost control than the needs of patients for optimal
medical treatment, I agree for a different reason. While evidence-based
medicine is absolutely essential to comprehensive healthcare reform, it has
been profoundly corrupted by money.

In 2001, I volunteered to help conduct a review for the Cochrane
Collaboration of the evidence base for the use of anticoagulants (warfarin
[Coumadin] and heparins) for blood clots in the lungs (pulmonary emboli, or
PE) and legs (deep venous thromboses, or DVT), as recently affected Vice
President Dick Cheney. Dr. Juliet Manyemba, a physician from England, and
John Pezzullo, PhD, a retired biostatistician formally from Georgetown
University School of Medicine, were my coauthors. I disclosed to the
Cochrane editor that my research interest in anticoagulants for DVT and PE
originated because of a malpractice case against me concerning a DVT patient
that resulted in the loss of my medical license.

Warfarin, heparin, and other anticoagulant drugs have been used to treat
blood clots since the 1940s based on unscientific anecdotal evidence and
observational studies with historical controls. Subsequently, countless RCTs
involving blood thinners for venous thromboembolism (VTE) patients have
included no un-anticoagulated control subjects. According to anticoagulation
researchers contracted or employed by drug companies, the rationale is that
it would be "unethical" not to give anticoagulants to clinical research
subjects with blood clots in their legs or lungs. After reading over 1000
studies on the topic, I found 1 randomized and properly controlled trial of
DVT patients. Patients in the study received either standard treatment
(warfarin and heparin) or phenylbutazone (an anti-inflammatory drug like
aspirin). From this single well-designed study of anticoagulants came a
startling result: The anticoagulants did not prevent deaths.[3,4]

Cochrane archivists turned up 2 other RCTs of anticoagulation therapy in DVT
patients. Neither trial found any benefit due to anticoagulants. Summing the
results of the 3 trials, 66 DVT patients received anticoagulants and 6 of
them died; 60 DVT patients did not receive anticoagulants, and 1 of them
died. None of the 3 trials had been referenced in any journal articles or
reviews of anticoagulant therapy that I read.

Although these 3 trials show a trend suggesting that warfarin and heparin do
harm, there were too few patients to show with statistical significance that
anticoagulants increase deaths. But they contain enough subjects to show
that anticoagulants do not reduce mortality. Based on the complication rate
of anticoagulation for DVT or PE in much larger observational studies,
anticoagulants kill 1000-4000 Americans with VTE each year due to internal
bleeding, mostly in the brain.[5-7] According to a recent population-based
study of anticoagulation-related intracerebral bleeding (AAICB) rates in the
greater Cincinnati area, AAICB occurred in 2000-2500 VTE American patients
in 2004 (5.1-6.5 AAICB cases per 100,000 population; 12.9% of AAICB cases
were related to anticoagulation of VTE patients). About 60% of AAICB
patients die within 1 year.[8] Most of the surviving 40% remain permanently
disabled. Warfarin distribution in the United States quadrupled on a
per-capita basis between 1988 and 1999. In Cincinnati, cases of AAICB rose
5.5-fold from 1988 to 1999.[9]

The Cochrane peer reviewers (at least 4 out of 7 of which had undisclosed
financial ties to the drug companies that make anticoagulants) delayed four
years over releasing this review for publication. When the only 3 RCTs
discovered showed no benefit and possible harm from anticoagulants, the
editor and peer reviewers directed us to include 8 additional lines of
evidence supporting anticoagulation from about 50 other studies in the
medical literature. When my critique of those 8 lines of evidence showed
that they were all faulty, the peer reviewers did not rebut a single point.
Instead, the editor demanded that we delete the additional lines of evidence
from the review, because they were not from RCTs. The Cochrane editor also
would not allow publication of the estimate of major and fatal bleeding from
anticoagulants for VTE, because I derived those figures from large
retrospective observational studies and not RCTs.

When the author of one of the randomized trials discovered by the Cochrane
archivists refused to cooperate and clarify to us his method of randomizing
patients in his study, the Cochrane editor and/or peer reviewers invented a
reason to disqualify the trial from inclusion in our review. The editor told
us to accept the edits or the review wouldn't be published. The "authors'
conclusions," written into our article by the Cochrane editor and peer
reviewers, were these: "The limited evidence from randomized controlled
trials of anticoagulants versus nonsteroidal anti-inflammatory drugs or
placebo is inconclusive regarding the efficacy and safety of anticoagulants
in venous thromboembolism (DVT and PE) treatment. The use of anticoagulants
is widely accepted in clinical practice, so a further randomized trial
comparing anticoagulants to placebo could not ethically be carried out."

In our final draft of the review, we authors said that a placebo-controlled
trial would be impractical and suggested a "noninferiority trial" with
anticoagulants vs a nonsteroidal anti-inflammatory drug. One of the peer
reviewers, with no conflict of interest that I could find, commented, "Note
that it is ethically possible to conduct a study to determine if
anticoagulation therapy is harmful. If nothing else, dose reduction studies
could determine if lower doses or weaker therapies (aspirin or NSAIDS?) are
equally effective" (ie, a noninferiority trial).

Finally, in January 2006, The Cochrane Database of Systematic Reviews
published our review -- completely altered by the peer reviewers and
editor -- entitled, "Anticoagulants or Non-steroidal Anti-inflammatories or
Placebo for Treatment of Venous Thromboembolism."[10] At the suggestion of
Dr. Dickersin, I issued a complaint to the Cochrane Collaboration
publication arbitrator in September 2006. In the 7 months since I submitted
the complaint, 580-2300 American VTE patients have bled to death from
anticoagulants as estimated from observational studies.[5-7] This estimate
is consistent with 1160-1450 deaths based on the above mentioned Cincinnati
population-based AAICB study.[8] Worldwide, at least twice as many have

Dr. Dickersin recently told me that she cannot estimate when the Cochrane
investigation will be completed. A recent similar investigation took 2
years. The publication arbitrator has resigned, and she has no guarantee of
finding a replacement anytime soon. Options that they are considering
include withdrawing the review from the Cochrane Database of Systematic
Reviews and having new peer reviewers critique the review (except that she
doesn't know when she can find new peer reviewers with expertise in
anticoagulation). Options that are not under consideration include printing
the review as we authors wrote it, having the Cochrane peer reviewers reply
to my analysis of their 8 lines of evidence supposedly supporting
anticoagulation, and asking the FDA Office of Surveillance and Epidemiology
(formerly Office of Drug Safety) to examine the evidence and issue a report,
as I suggested 7 months ago.

Medscape General Medicine published my entire review, including the evidence
from the 8 lines other than the 3 RCTs included in our Cochrane VTE
review.[11-13] The Medscape VTE review concluded, "Anticoagulants have not
been shown to be efficacious in reducing morbidity or mortality or safe in
venous thromboembolism treatment." Medscape Chief Editor, George Lundberg,
MD (former Chief Editor of JAMA), wrote the accompanying editorial, entitled
"Is the Current Standard of Medical Practice for Treating Venous
Thromboembolism Simply Wrong?"[14] I sent the link to the review to several
anticoagulation experts at the Food and Drug Administration. Warren Rumble,
Ombudsman - FDA, Center for Drug Evaluation and Research, replied for them:
"Thank you for asking FDA to provide an official response to your published
article in Medscape General Medicine. I have consulted with officials in our
Center for Drug Evaluation and Research regarding your request, and we will
not have a response to your publication. We appreciate that you provided
access to your article, and the chance to comment on it."

Since anticoagulation researchers and FDA scientists chose not to rebut any
of the data or conclusions of either review, the media was not interested,
few physicians read the reviews, and no debate ensued. Researchers continue
receiving lucrative contracts from drug companies for more anticoagulant
trials. The medical establishment (drug companies, doctors, hospitals) keeps
making money from the diagnosis and treatment of DVT and PE with
anticoagulants (estimated total cost in 2007 will be $13 billion-$48 billion
in the United States[15]), and medical journals keep publishing more
anticoagulation trials without proper controls, which are dutifully covered
by a compliant media, while thousands of DVT and PE patients keep bleeding
to death.

To have a fair resolution concerning the interpretation of the scientific
evidence about the efficacy and safety of anticoagulants for the treatment
of VTE, I suggest that the reader call for the FDA Office of Surveillance
and Epidemiology to investigate the issue and decide which of the 2 reviews
of this topic published under my name[11,10] is valid (Office of
Surveillance and Epidemiology Director Gerald Dal Pan, MD,
gerald.dalpan@fda.hhs.gov ; Ph: 301-796-2380; or go to

Readers are encouraged to respond to the author at dkcundiff3@verizon.net
or to Paul Blumenthal, MD, Deputy Editor of MedGenMed, for the editor's eyes
only or for possible publication via email: pblumen@stanford.edu


Higgins JPT, Green S, eds. Cochrane Handbook for Systematic Reviews of
Interventions 4.2.6 [updated September 2006]. Available at:
Accessed January 16, 2007.

Healy B. Who says what's best? US News & World Report. September 3, 2006.
Available at:
Accessed May 31, 2007.

Nielsen HK, Husted SE, Krusell LR, Fasting H, Charles P, Hansen HH. Silent
pulmonary embolism in patients with deep venous thrombosis. Incidence and
fate in a randomized, controlled trial of anticoagulation versus no
anticoagulation. J Intern Med. 1994;235:457-461. Abstract

Nielsen HK, Husted SE, Krusell LR, et al. Anticoagulant therapy in deep
venous thrombosis. A randomized controlled study. Thromb Res.
1994;73:215-226. Abstract

van der Meer FJ, Rosendaal FR, Vandenbroucke JP, Briet E. Bleeding
complications in oral anticoagulant therapy. An analysis of risk factors.
Arch Intern Med. 1993;153:1557-1562. Abstract

Fihn SD, McDonell M, Martin D, et al. Risk factors for complications of
chronic anticoagulation. A multicenter study. Warfarin Optimized Outpatient
Follow-up Study Group. Ann Intern Med. 1993;118:511-520. Abstract

Landefeld CS, Beyth RJ. Anticoagulant-related bleeding: clinical
epidemiology, prediction, and prevention. Am J Med. 1993;95:315-328.

Flaherty ML, Haverbusch M, Sekar P, et al. Location and Outcome of
Anticoagulant-Associated Intracerebral Hemorrhage. Neurocrit Care.
2006;5:197-201. Abstract

Flaherty ML, Kissela B, Woo D, et al. The increasing incidence of
anticoagulant-associated intracerebral hemorrhage. Neurology.
2007;68:116-121. Abstract

Cundiff DK, Manyemba J, Pezzullo JC. Anticoagulants versus non-steroidal
anti-inflammatories or placebo for treatment of venous thromboembolism. The
Cochrane Database of Systematic Reviews. 2006; Issue 1. Art. No.: CD003746.
DOI: 10.1002/14651858.CD003746.pub2.

Cundiff DK. Anticoagulation therapy for venous thromboembolism. MedGenMed.
2004;6(3):5. Available at: http://www.medscape.com/viewarticle/487577
Accessed May 31, 2007.

Cundiff DK. Letters to editor re "Anticoagulation therapy for venous
thromboembolism." Medscape General Medicine. 2005;7(1):49. Available at:
Accessed May 31, 2007.

Cundiff DK. Author's response to letters to the editor regarding the article
entitled "Anticoagulation therapy for venous thromboembolism." Medscape
General Medicine. 2005;7(1):48. Available at:
Accessed May 31, 2007.

Lundberg GD. Is the current standard of medical practice for treating venous
thromboembolism simply wrong? MedGenMed. September 9, 2004;6(3):36.
Available at: http://www.medscape.com/viewarticle/488717
Accessed May 31, 2007.

Cundiff DK. Money Driven Medicine--Tests and Treatments That Don't Work.
2006;:170-172. Available at: http://doctormanagedcare.com
Accessed May 31, 2007.

David K. Cundiff, MD, Los Angeles County and USC Medical Center (Retired)

Author's email: dkcundiff3@verizon.net

Disclosure: David K. Cundiff, MD, has disclosed no relevant financial

[Return to top]


Date:    Fri, 22 Jun 2007 06:13:42 +0200
From:    Jan van Roijen <j.van.roijen CHELLO.NL>
Subject: not,med: First Fibromyalgia Treatment


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FDA OKs First Fibromyalgia Treatment

June 21,2007 | WASHINGTON -- A Pfizer Inc. drug won
expanded federal approval Thursday as the first treatment
for fibromyalgia, a mysterious syndrome marked by
muscle pain and fatigue.

The Food and Drug Administration action means Lyrica
becomes the first drug that can be marketed specifically as a
treatment for adults with fibromyalgia. Patients currently make
so-called "off label" use of pain medications, antidepressants,
muscle relaxants and sleep aids to treat the condition. Exercise
and applying heat also can help.

Fibromyalgia typically affects women, striking them with
long-lasting or chronic pain, as well as muscle stiffness and
tenderness, according to the FDA. An estimated 3 million to 6
million people in the United States are affected each year.

Lyrica, known generically as pregabalin, previously won FDA
approval to treat partial seizures, pain following the rash of
shingles and pain associated with diabetes nerve damage.

The FDA warned that common side effects of the drug included
mild-to-moderate dizziness and sleepiness. Also, the agency
said that Lyrica reduces pain and improves daily functions for
some patients with fibromyalgia, but that not everyone derived
benefit from the drug in studies.

The cause of fibromyalgia is a mystery, though it may be linked
to injury, emotional distress or viruses that change the way the
brain perceives pain, the FDA said.


On the Net:

FDA information on fibromyalgia:

Salon provides breaking news articles from the Associated
Press as a service to its readers, but does not edit the AP
articles it publishes.

© 2007 The Associated Press. All rights reserved. The
information contained in the AP News report may not be
published, broadcast, rewritten or redistributed without the prior
written authority of The Associated Press.



Lyrica Medication Approved for Fibromyalgia

Last Edited: Thursday, 21 Jun 2007, 8:22 PM EDT
Created: Thursday, 21 Jun 2007, 8:19 PM EDT

Pfizer announced Thursday that the Food and Drug
Administration approved Lyricacapsules CV for the
management of fibromyalgia, the most common chronic,
widespread pain condition in the U.S.

The approval of Lyrica, which received a priority review,
represents a breakthrough for the more than six million
Americans who suffer from this debilitating condition and who
previously had no FDA approved treatment options

Characterized by chronic widespread pain that can be
relentless, fibromyalgia is usually accompanied by poor sleep,
stiffness and fatigue; patients also report experiencing deep
tenderness, soreness and flu-like aching.

Fibromyalgia can have devastating effects on a sufferer and
engage in everyday activities, as well as their relationships with
family, friends and employers.

Fibromyalgia is thought to result from neurological changes in
how patients perceive pain, specifically a heightened sensitivity
to stimuli that are not normally painful.

Although its exact mechanism of action in fibromyalgia is not
known, Lyrica is thought to act in the central nervous system to
reduce the level of perceived pain.

In the clinical trials, Lyrica demonstrated rapid and sustained
improvements in pain compared with placebo. In addition,
patients taking Lyrica reported feeling better and improvements
in physical function.

Copyright 2007 Fox Washington, D.C. (WTTG). All rights
reserved. This material may not be published, broadcast,
rewritten, or redistributed. AP contributed to this report.

[Return to top]


Date:    Fri, 22 Jun 2007 00:08:38 -0700
From:    Jerry Campbell <jerrycamz YAHOO.COM>
Subject: RES: Dendritic cells are replenished from blood


  Dendritic cells are the type of cell that is the first line of immune defense. Until a foreign cell is identified by a dendritic cell,
it remains invisible to the immune system. Once a dendritic cell has tagged it as foreign, the dendritic cell then 'trains' T cells to attack it;
the T cells can then go on to cause B cells that make antibodies against this foreign cell to multiply and make more antibodies.

  The following article finds that dendritic cells within the spleen - and presumably the digestive tract and liver - are continuously
replenished from the bone marrow.

  Because the dendritic cells are continually dying off and being replenished, if one becomes infected it will not create a permanent
line of infected cells; instead it will dy off and be replenished by new uninfected cells from the bone marrow.


  Posted: June 12, 2007
Dendritic cells are replenished from blood

  Dendritic cells help direct the body’s immune response by presenting invading antigens to T cells so they know what to attack. But an
ongoing debate exists about where dendritic cells originate and how they multiply, especially in the spleen and lymph system. Now, in a paper
published in this month’s issue of Nature Immunology, Rockefeller University scientists have come a step closer to understanding the origins
of the spleen and lymph node dendritic cells, findings that are especially important for researchers developing immune-cell-targeted vaccines.

Prior studies suggested that dendritic cells in the spleen either must continually divide and renew their population, or must be constantly
replenished from precursor cells migrating from the bone marrow. Resolving the debate is important, says Kang Liu, postdoctoral associate
and the study’s first author, because if dendritic cells divide endlessly then they could be acting as a reservoir for pathogens. "On the
other hand, dividing could also allow them to present antigens to T cells for a longer period and prime the immune system to fight the pathogens
off," Liu says.

The study by Liu and Michel Nussenzweig, Sherman Fairchild Professor and head of the Laboratory of Molecular Immunology, appears to resolve the
debate. According to their research, spleen and lymphoid dendritic cells migrate to these organs through the blood as "dendritic cell
precursors," mature into dendritic cells, divide a few times and then die, leaving a void to be replenished by bone marrow precursors.

By joining two mice together so that they shared the same bloodstream, a technique called parabiosis, the scientists found that even though
the mice shared most of their immune cells equally, they only had about a 30 percent exchange rate in their spleen and lymph node dendritic
cells. These dendritic cells were continually being replaced by precursors from the blood, precursors that were never evenly distributed
between the two mice because they were removed from circulation too quickly to equilibrate.

Liu and Nussenzweig, who’s also an HHMI investigator, found three main factors for the maintenance of a mouse’s population of spleen and lymph node
dendritic cells: continuous replenishment of dendritic cell precursors from the blood at a rate of about 4,300 cells per hour, the limited
division of differentiated dendritic cells and the dendritic cell death rate. "These dendritic cells can’t last longer than 14 days without
being replenished, and the number of dendritic cells can be the rate-limiting factor of immune response," Liu says. "This is the first
time that their division and self-renewal capacity has been directly measured."

Nature Immunolgy 8(6): 578-583 (June 2007)

  Contact: Lauren Gravitz (212) 327-8977

[Return to top]


Date:    Fri, 22 Jun 2007 23:46:16 +0200
From:    "Dr. Marc-Alexander Fluks" <fluks COMBIDOM.COM>
Subject: RES,NOT: Members of European parliament support research into CFS

The European parliament made a statement on CFS this week.

Unfortunately, the text is not available in English,





but it is in the Dutch version of this page,





The last line of the text says that a dozen of MPs will work on research
into stam cells, CFS, astronomy and biotechnology.

[Return to top]


Date:    Sun, 24 Jun 2007 04:20:52 +0200
From:    Jan van Roijen <j.van.roijen CHELLO.NL>
Subject: res: ME/CFS -Metabolic & Neurocognitive Responses to Exercise Challenge


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From: Frank Twisk <frank.twisk hetnet.nl>


Metabolic And Neurocognitive Responses To An
Exercise Challenge In Chronic Fatigue Syndrome (CFS)

Medicine & Science in Sports & Exercise: Volume 39(5)
Supplement, May 2007, p S445

VanNess, J. Mark; Snell, Christopher R.; Stevens, Staci R.;
Stiles, Travis L.

University of the Pacific, Stockton, CA. Email:
mvanness@pacific.edu Supported by the CFIDS Association of

2401: Board #80 June 1 3:30 PM - 5:00 PM [F-25 Free
Communication/Poster - Clinical Exercise Physiology - Chronic
Diseases and Conditions: JUNE 1, 2007 1:00 PM - 6:00PM
ROOM: Hall E]

A comprehensive view of CFS patients during conditions
of post-exertional malaise can provide an integrated
perspective on the pathophysiology the illness.


To compare the metabolic responses and neurocognitive
consequences of a maximal exercise challenge between CFS
and control subjects.


Twenty (n=20) women with CFS and twenty (n=20) sedentary
control subjects performed a graded exercise test to maximal

Cardiopulmonary analysis was performed during the exercise

Blood samples for plasma lactate and glucose were collected
before and after the test.

Nasal acoustic rhinometry (NAR) was used to measure nasal
cross-sectional area and volume on both nostrils before and
after the exercise test.

Neurocognitive function was measured before and after the
exercise test using the CalCap computer program.


Multivariate analysis of cardiopulmonary variables found a
significant difference between groups; Wilks' ? = 0.053, F =
6.393 (7, 20), p>0.01.

Follow-up univariate tests with alpha levels adjusted to account
for inflation of the error term indicated that CFS patients scored
significantly lower on measures of peak workload (116±19 vs.
176±26 Watts), peak ventilation (70±22 vs. 102±16 L), peak
VO2 (23.4±6.4 vs. 32.0±4.5 ml/kg/min), and VO2 and workload
at anaerobic threshold (9.7±2.3 vs. 17.3±3.9ml/kg/min and
42±12 vs. 75±21 Watts respectively).

For the CalCap, a group by test (2X3) factorial MANOVA with
dependent variables; simple reaction time (SRT) and three
levels of choice reaction time (CRT), produced a significant
main effect for group; Wilks Lambda = 0.85, F=4.76 (4, 105),

Follow up discriminant function analysis indicated that the CRT
measures were more important in differentiating CFS than was
SRT. The CFS group was slower on all measures.

These results indicate that exercise performance and
neurocognitive abnorma¬lities exist in CFS.

The lack of any significant differences in lactate, glucose or
nasal rhinometry precludes clear explanation for these

© 2007 The American College of Sports Medicine

[Return to top]


Date:    Sun, 24 Jun 2007 04:45:28 +0200
From:    Jan van Roijen <j.van.roijen CHELLO.NL>
Subject: res: ME/CFS -post-exertional symptomology


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From: Frank Twisk <frank.twisk hetnet.nl>


Post-exertional Symptomology
In Chronic Fatigue Syndrome

(CFS Medicine & Science in Sports & Exercise: Volume 39(5)
Supplement, May 2007, p S445

Stiles, Travis L.; Snell, Christopher R.; Stevens, Staci R.; Moran,
Megan; VanNess, J. Mark

University of the Pacific, Stockton, CA.
Email: tstiles@pacific.edu

Supported by the CFIDS Association of America

Symptom exacerbation following physical stress has been
documented in illnesses such as multiple sclerosis (MS),
lupus and rheumatoid arthritis (RA). Similar
phenomenology has been reported in CFS but is not well


The purpose of this study was to explore symptom exacerbation
following an exercise challenge in CFS patients relative to a
sedentary control population.


Forty female subjects (n=40),
20 CFS and
20 matched sedentary controls served as subjects.

All participants underwent a graded maximal cardiopulmonary
exercise test (CPX).

Two questionnaires, Short Form-36 (SF-36) and a series of
open-ended questions, were completed 7 days after the
exercise challenge to assess post-exertional differences
between groups.

The open-ended questions pertained to symptoms
experienced following the test and time taken to recover from
any testing effects.

SF-36 data were analyzed using a multivariate analysis.

Written questionnaire responses were evaluated by determining
recovery time in days as well as number and type of symptoms


SF-36 analysis found statistical significance across all 8
health domains measured between groups (p <.01), but no
effects were found for the exercise test.

Analysis of the open-ended questionnaires revealed that
within 24 hours of the exercise challenge, 85% of controls
indicated full recovery in contrast to 0% of CFS patients.
The remaining 15% of controls recovered within 48 hours
of the test as opposed to only one CFS patient.

Clear differences in number and type of reported symptoms
were also found between groups.


The results of this study indicate that CFS patients suffer
symptom exacerbation following physical stress. As with MS,
lupus and RA, post-exertional symptom exacerbation appears to
be both a real and incapacitating feature of the syndrome.
The delayed recovery response evoked by a single bout
of exercise stress is distinctly different from that of
sedentary controls.

The debilitating effects experienced by these patients help
to explain activity avoidance, which should be considered
when prescribing exercise and activity management
programs for CFS patients.

© 2007 The American College of Sports Medicine

[Return to top]


Date:    Mon, 25 Jun 2007 19:53:10 -0400
From:    "Marly Silverman <beatcfsfms bellsouth.net> via Co-Cure Moderator"
Subject: NOT,RES: Miami researchers are looking for patients for innovative CFS research study

Miami researchers are looking for patients for innovative CFS research study

The University of Miami-Behavioral Medicine Research Center is conducting
research studies on chronic fatigue syndrome that allows patients to
participate in the comfort of their homes. It is called the TeleHealth Study.


What: The TeleHealth Study is a research project designed to help
individuals with CFS understand and manage their condition. Participants
will be provided with information about the nature and effects of stress
reactions; how to cope and manage stress; and how to take better care of
themselves via an innovative home-based program. The TeleHealth study is
funded by the National Institutes of Health (NIH) in collaboration with the
University of Miami Behavioral Medicine Research Center.

Who is eligible: People who
1. Have a diagnosis of CFS
2. Are between the ages of 21-65
3. Speak, read and write English fluently
4. Have a telephone line
5. Live in Dade or Broward counties for the next 9 months.

Payment: $50 for each completed assessment

Contact: To participate or for more information, call 305-243-1434 or

In Good Health and In Beauty,
Marly C. Silverman
P.A.N.D.O.R.A. - Patient Alliance for Neuroendocrineimmune Disorders
Organization for Research and Advocacy, Inc. -Volunteer Help Line :
954-783-6771 - Fax: 954-783-1098
www. pandoranet.info
Built on Hope - Strong on Advocacy - Finding a Cure through Research

Please support the I NEED A HERO! campaign for a Congressional Caucus for
CFS/ME-FM-GWI-MCS and related illnesses.

[Return to top]


End of Co-Cure Weekly Digest of research and medical posts only - 18 Jun 2007 to 25 Jun 2007

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