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Citation: Hieber, H.; Pricoco, R.;
Gerrer, K.; Heindrich, C.; Wiehler, K.;
Mihatsch, L.L.; Haegele, M.; Schindler,
D.; Donath, Q.; Christa, C.; et al. The
German Multicenter Registry for
ME/CFS (MECFS-R). J. Clin. Med.
2024,13, 3168. https://doi.org/
10.3390/jcm13113168
Academic Editor: Jacob Ablin
Received: 28 April 2024
Revised: 14 May 2024
Accepted: 17 May 2024
Published: 28 May 2024
Copyright: © 2024 by the authors.
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4.0/).
Journal of
Clinical Medicine
Article
The German Multicenter Registry for ME/CFS (MECFS-R)
Hannah Hieber 1, †, Rafael Pricoco 1 ,2 ,† , Katrin Gerrer 1, Cornelia Heindrich 2, Katharina Wiehler 1,
Lorenz L. Mihatsch 1, Matthias Haegele 1, Daniela Schindler 1, Quirin Donath 1, Catharina Christa 1,
Annika Grabbe 1, Alissa Kircher 1, Ariane Leone 1, Yvonne Mueller 1, Hannah Zietemann 1, Helma Freitag 2,
Franziska Sotzny 2, Cordula Warlitz 1, Silvia Stojanov 3, Daniel B. R. Hattesohl 4, Anna Hausruckinger 1,
Kirstin Mittelstrass 1, Carmen Scheibenbogen 2, 4, † and Uta Behrends 1,4,5,*,†
1MRI Chronic Fatigue Center for Young People (MCFC), Pediatrics, Children’s Hospital, TUM School of
Medicine and Health, Technical University of Munich, 80333 Munich, Germany;
hannah.hieber@tum.de (H.H.); rafael.pricoco@mri.tum.de (R.P.); lorenz.mihatsch@mri.tum.de (L.L.M.)
2
Institute of Medical Immunology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität
Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
3MRI Chronic Fatigue Center for Young People (MCFC), Child and Adolescent Psychosomatics, Children’s
Hospital, TUM School of Medicine and Health, Technical University of Munich, 80333 Munich, Germany
4German Association for ME/CFS, 20146 Hamburg, Germany
5German Center for Infection Research (DZIF), 81675 Munich, Germany
*Correspondence: uta.behrends@mri.tum.de
†These authors contributed equally to this work.
Abstract: Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debili-
tating multisystemic disease characterized by a complex, incompletely understood etiology. Methods:
To facilitate future clinical and translational research, a multicenter German ME/CFS registry (MECFS-
R) was established to collect comprehensive, longitudinal, clinical, epidemiological, and laboratory
data from adults, adolescents, and children in a web-based multilayer-secured database. Results:
Here, we present the research protocol and first results of a pilot cohort of 174 ME/CFS patients
diagnosed at two specialized tertiary fatigue centers, including 130 (74.7%) adults (mean age 38.4;
SD 12.6) and 43 (25.3%) pediatric patients (mean age 15.5; SD 4.2). A viral trigger was identified in
160/174 (92.0%) cases, with SARS-CoV-2 in almost half of them. Patients exhibited severe functional
and social impairment, as reflected by a median Bell Score of 30.0 (IQR 30.0 to 40.0) and a poor
health-related quality of life assessed with the Short Form-36 health survey, resulting in a mean
score of 40.4 (SD 20.6) for physical function and 59.1 (SD 18.8) for mental health. Conclusions: The
MECFS-R provides important clinical information on ME/CFS to research and healthcare institutions.
Paired with a multicenter biobank, it facilitates research on pathogenesis, diagnostic markers, and
treatment options. Trial registration: ClinicalTrials.gov NCT05778006.
Keywords: myalgic encephalomyelitis; chronic fatigue syndrome; ME/CFS; post-viral syndrome;
registry; post-COVID; PASC; children; adolescents
1. Introduction
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a frequent, com-
plex, severe, chronic disease classified by the World Health Organization as a neurological
disorder (ICD-10 GM G93.3, ICD-10 CM G93.32, ICD-11 8E49) [1].
The reported global prevalence of ME/CFS ranges from 0.2% (clinically diagnosed)
to 3.5% (self-reported), depending on the study design and diagnostic criteria applied [
2
].
In Germany, the pre-pandemic number of affected people is estimated as 140,000–310,000,
including up to 90,000 children and adolescents at the age of 6–17 years [
3
,
4
]. Patients with
ME/CFS endure persistent symptoms. According to a systematic review encompassing
14 studies with varying definitions of remission and length of follow-up, only 5% (range:
0–31%) of adult patients achieve complete remission of the disease, with 39.5% (range:
J. Clin. Med. 2024,13, 3168. https://doi.org/10.3390/jcm13113168 https://www.mdpi.com/journal/jcm
J. Clin. Med. 2024,13, 3168 2 of 16
8–63%) showing improvement during follow-up [
5
]. A Norwegian population-based study
found two age peaks at age 10–19 and 30–39 years [6].
The clinical picture is characterized by a substantial loss in pre-illness levels of activity
with pathological exhaustion (fatigue) and long-term worsening of symptoms after mild
to moderate activities (post-exertional malaise, PEM) (“crashes”). Fatigue and PEM are
typically accompanied by sleep disturbances, pain, and cognitive, autonomic, neuroen-
docrine, and flu-like symptoms [
7
]. Participation in social life is often severely impaired,
and significant absences from school or work are frequent [2,5].
A febrile episode with confirmed or probable viral origin is usually found before
symptom onset. Epstein–Barr virus (EBV)-associated infectious mononucleosis (IM) is a
prominent trigger [
8
] and accounted for about half of the pre-pandemic post-infectious
ME/CFS cases in childhood and adolescence [
9
–
13
]. In a study in Chicago, 13%, 7%, and
4% adolescents were diagnosed with ME/CFS at 6, 12, and 24 months after EBV-IM [
14
].
During the coronavirus disease 2019 (COVID-19) pandemic, infection with severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2) became another frequent trigger. Prior
research indicates that 19–58% of adult outpatients with post-acute sequelae of COVID-19
(PASC) may meet ME/CFS criteria [
15
–
18
], and the first cases of ME/CFS in children
and adolescents with PASC were described [
19
], though comprehensive population-based
studies are currently lacking. The number of ME/CFS cases was expected to at least double
during the pandemic due to long-term COVID-19 sequelae [20,21].
The pathophysiology of ME/CFS is still largely unknown, and reliable biomarkers and
specific treatment options are not available yet [
22
]. Various immunological changes [
23
–
25
],
including autoantibodies [
26
,
27
], as well as metabolic, vascular dysfunction, and various
genetic signatures, have been described [
28
–
30
]. Furthermore, persistent or reactivated
viruses might contribute to pathogenic mechanisms [
31
]. ME/CFS is diagnosed by differ-
ent clinical criteria, of which all more recent criteria require PEM as a cardinal symptom.
Recommended case definitions by the European Network on Myalgic Encephalomyeli-
tis/Chronic Fatigue Syndrome (EUROMENE) include the Canadian Consensus Criteria
(CCC) [
32
] and the broader Institute of Medicine (IOM) criteria [
33
]. The clinical diagnostic
worksheet by Rowe and colleagues (CDW-R) and the pediatric case definition by Jason
and colleagues (PCD-J) are being used as age-adapted alternatives for children and ado-
lescents [
2
,
19
,
34
]. All case definitions are based on significant severity and frequency of
typical ME/CFS symptoms and no evidence of other medical conditions, necessitating a
thorough diagnostic workup.
Routine treatment of ME/CFS is symptom-oriented [
7
]. It aims at reducing the
symptom load with pain, orthostatic intolerance, and sleep-related problems, and also
the impact of aggravating conditions such as infections, allergies, and/or nutritional
deficiencies [
4
,
35
,
36
]. A key part of managing ME/CFS is the implementation of adequate
stress and energy self-management (pacing) to avoid PEM and a subsequent worsening of
symptoms. Psychosocial support can help with the development of coping strategies [32].
Providing a timely diagnosis can reduce the complex burden on patients and their social
networks and thereby support recovery. Many patients are under- or misdiagnosed and
exposed to stigmatization and/or mistreatment [37,38].
To facilitate future ME/CFS research and to pave the way to improved clinical care, we
aimed at a standardized multicenter evaluation of ME/CFS-specific clinical phenotypes and
healthcare features in our novel German ME/CFS registry (MECFS-R). Here, we present
the structure of this registry and provide medical data on a cohort of adults, adolescents,
and children recruited from two specialized tertiary care centers in Berlin and Munich.
The MECFS-R provides comprehensive information on clinical phenotypes, features of
medical care, and disease trajectories over time. Together with our ME/CFS biobank, the
MECFS-R is expected to aid scientists in discovering risk factors, predictive and diagnostic
biomarkers, as well as therapeutic targets for this debilitating disease. It aims to classify
distinct patient groups and provide decision-makers with information on the disease’s
burden and its social and economic impacts. We will invite additional healthcare providers
J. Clin. Med. 2024,13, 3168 3 of 16
caring for ME/CFS patients to share our standard diagnostic procedures and contribute
data to this registry study.
2. Materials and Methods
2.1. Participating Institutions and Target Population
The multicentric MECFS-R, a patient registry with an attached biobank, was developed
by a multidisciplinary team of clinicians, researchers, patients, and members of ME/CFS
foundations and support groups. It was established at the Munich Chronic Fatigue Center
for Young People (MCFC) in Munich [
39
] and the CharitéFatigue Center (CFC) in Berlin,
Germany [
39
,
40
]. At the CFC most patients are seen in the Department of Immunology
with currently approximately 500–600 adult patients seen per year with suspected infection-
triggered ME/CFS. In approximately 60% of cases the diagnosis ME/CFS is confirmed
following the exclusion of other fatiguing illness. In roughly 40% of cases, either an alterna-
tive diagnosis is identified during the diagnostic workup or the clinical presentation does
not entirely align with the clinical criteria for ME/CFS. The MCFC sees about 100 young
people aged up to 20 years annually. Additional centers are currently being integrated
to create a comprehensive national registry. Standard operation procedures (SOPs) for
differential diagnostic workups have been implemented at both centers and are being dis-
tributed nation-wide. Inclusion criteria of the MECFS-R require the diagnosis of ME/CFS
by PEM-based clinical criteria (CCC, IOM, CDW-R, PCD-J) and written informed consent
provided by the patients or their legal guardians. Exclusion criteria are no ME/CFS diag-
nosis, for example, due to an alternate diagnosis or not meeting any established clinical
criteria, and missing informed written consent. Participating institutions are collecting
detailed clinical routine data for each patient at a baseline and any clinically indicated
follow-up visit. There is no specific interval between examinations, as these are provided
according to the patient’s needs.
Furthermore, biosamples, including serum, plasma, and peripheral blood mononu-
clear cells (PBMCs), are collected. The MECFS-R study is registered via ClinicalTrials.gov
(NCT05778006).
2.2. Ethical Considerations
Before inclusion into the registry, all patients and/or, in the case of children and
adolescents younger than 18 years, their legal guardians provided written informed consent.
The study was approved by the Ethics Committee of the Technical University of Munich
Medical Center (MRI TUM), Germany on 24 February 2021 (116/21 S) and by the Ethics
Committee of Charité—Universitaetsmedizin Berlin on 5 May 2022 (EA/006/22).
2.3. Data Entry System
The MECFS-R database was developed with the open-source data integration system
(DIS), which emerged from an initiative within the Leading Edge Cluster m4 competition,
funded by the German Federal Ministry of Education and Research [
41
]. DIS offers a
secure identity management component and functionality to manage observational data
and biosamples. It allows for the integration of data from different digital sources and
for advanced security measures such as two-tier pseudonymization, data-at-rest and data-
in-transit encryption, role-based access, and audit trails. The ethics and data protection
concepts of the DIS have been approved by the relevant local review boards and are in
line with the policies of the Data Integration for Future Medicine (DIFUTURE) consortium
safeguarding data use and sharing [
42
]. Following these data protection concept guidelines,
a central web-based DIS instance was established at the MRI TUM. Several clinical report
forms (CRFs) are used, encompassing a comprehensive set of routine clinical data from
baseline and follow-up visits and providing technical information about stored biosamples.
A MECFS-R user manual was developed to facilitate data entry and provide use and access
rules. A warning system was introduced into the DIS to inform the user about potential
J. Clin. Med. 2024,13, 3168 4 of 16
errors. A research coordinator at the MCFC is monitoring completeness of study data and
offers online training for each new member.
2.4. Data Protection
The data protection concept of the MECFS-R is based on the relevant concepts of the
Technology, Methods, and Infrastructure (TMF) for Networked Medical Research. Standard
state-of-the-art IT security measures are used to protect the IT systems. The storage and
management of identifying and medical data occur in separate database systems, which
remain organizationally and geographically separate, and they are pseudonymized in two
stages. This separation ensures that any person would need to gain unauthorized access
to at least three spatially and organizationally separate subsystems to obtain medical and
identifying data. A role-based, personal access authorization system is used to access the
registry and managed by the local IT manager.
As a fundamental principle, the registry allows for the sharing of all included data,
including clinical information, questionnaires, and biospecimens stored within the biobanks.
Researchers interested in utilizing the registry for their projects are encouraged to reach
out to the corresponding author. If a research project necessitates data from multiple
participating centers, consent from all relevant centers is mandatory. Any data transfer is
strictly contingent upon obtaining explicit consent declarations by the registry team and
may occur in anonymized or pseudonymized form to safeguard privacy and confidentiality.
All data-receiving researchers must comply with strict data protection measures and sign
a data usage agreement. Any access to data is strictly project-related. The data stored
in the registry may also be used for future research projects approved by the relevant
ethics committee. Patients must explicitly consent to the use of their data for other studies.
Data are stored for 20 years after completion of the registry. The MRI TUM, represented
by its board members, and the participating centers are responsible for data processing.
Patients already enrolled will be informed about the multicenter rolling-out process and
the inclusion of additional centers in the registry.
2.5. Clinical Phenotyping
Since reliable diagnostic markers are lacking, diagnosing ME/CFS relies on a careful
evaluation of the patient’s medical history, clinical symptoms, and an appropriate workup
to exclude alternative diagnoses.
At both MCFC and CFC, patients undergo screening procedures, which include gath-
ering basic information about their symptoms and completing relevant questionnaires
aiming to identify individuals experiencing fatigue, PEM, and limited participation. If
ME/CFS is suspected, patients are encouraged to participate in a clinical appointment.
During this visit, they undergo a comprehensive in-person examination conducted by a
physician specialized in ME/CFS. If required, the involvement of a psychologist and/or
psychiatrist is arranged. Detailed review of previous medical records is performed to
exclude other conditions causing fatigue. Further diagnostic evaluations, including lab-
oratory tests and diagnostic procedures, are carried out based on each patient’s specific
requirements. Due to differences in infrastructure, local capacities, and different target
populations, the diagnostic procedures differ slightly between centers. MCFC primarily
serves children, while CFC serves adults, leading to tailored approaches in each setting.
Comprehensive medical information was derived from patients by semi-structured in-
terviews on the medical history, including comorbidities, prior diagnostic workup, medical
records, and prior treatments, as well as by detailed physical examination conducted at the
visit, psychosocial evaluation, and functional and imaging tests. Comprehensive standard-
ized routine blood analyses, encompassing clinical chemistry, virology, and microbiology,
adhere to the methodologies employed by the respective local institutional departments.
The treatments advised to the patient during the consultation, which may involve
self-management strategies and non-pharmacological and pharmacological treatments, are
J. Clin. Med. 2024,13, 3168 5 of 16
based on the individual physician’s assessment of the specific patient’s symptoms and
needs. Subsequently, these recommendations are documented in the registry.
Multiple questionnaires were used to assess individual symptoms, disease severity,
health-related quality of life (HRQoL), and patient-reported outcome measures (PROMs).
The presence, severity, and duration of PEM were evaluated by the well-established De-
Paul Symptom Questionnaire for PEM (DSQ-PEM) [
34
]. The frequency and severity of
ME/CFS symptoms were assessed in a quantitative manner using the 5-point Likert scale
derived from the DePaul Symptom Questionnaire via the novel Munich Berlin Symptom
Questionnaire (MBSQ) [
19
]. Using the MBSQ’s diagnostic algorithms, up to four sets of
internationally established diagnostic criteria were evaluated, including the CCC and IOM
criteria, recommended by the European Network on ME/CFS (EUROMENE) [
35
] and the
Centers for Disease Control and Prevention (CDC) [
43
] as well as, in the case of children
and adolescents, the age-adapted CDW-R [
2
] and the PCD-J [
44
]. All of these diagnostic
criteria required PEM, as internationally recommended. Table 1provides an overview of
the collected data. To answer basic research questions, a minimal core dataset (level 1)
was defined for participating primary and secondary care institutions with very limited
resources. This level 1 only requires data on age, sex, body mass index (BMI), clinical
scores used to establish the ME/CFS diagnosis, duration of PEM, type of trigger, and Bell
Score [
45
]. To provide data for more comprehensive research questions, a more detailed
dataset (level 2) is offered to tertiary care centers. Contributing centers can apply for
site-specific extension of the minimal level 1 or 2 dataset to reflect site-specific standards
for routine care and to allow for site-specific evaluations. However, to best avoid missing
data in cross-center analyses, any partner site has to agree to providing a complete dataset
at level 1 or 2.
Table 1. Overview of the Data Collected for the German ME/CFS Registry.
Demographics Medical History Therapy Physical
Examination
Laboratory
Evaluation
Functional Tests
and
Consultations
Questionnaires Biosamples
Date of visit
Date of birth
Gender
Occupation
High school
diploma
Domestic
support
Limitations in
daily life, social
and educational
participation
Changes in
health status
Symptoms of
ME/CFS
Information on
the onset of
ME/CFS (trigger,
time, medical
consultations,
laboratory
findings, progres-
sion/duration of
symptoms)
Medical history
Vaccination
status
Previous diagno-
sis/comorbidities
Allergies
Food intolerance
Susceptibility to
infection
Previous
infectious
diseases
Medications
Family history
Non-
pharmaceutical
Interventions
Self-
management
Medical aids
Food
supplements
Medications
Support at
school/education/
work
Degree of
disability
Degree of care
Hypermobile
Ehlers–Danlos
syndrome
screening
Body height
Body weight
BMI
Body
temperature
Cardiorespiratory
examination
Abdominal
examination
Neurological
examination
Musculoskeletal
examination
Hematology
Clinical
chemistry
Microbiology
Virology
Serology
Urine status
Blood gas
analysis
Oxygen
saturation
10 min passive
standing test
(blood pressure,
heart rate)
6 min walking
test
Hand-grip
strength
ECG
ECHO
Cranial MRI
Abdominal
sonography
EEG
Ophthalmological
consultation
Ear, nose, and
throat
consultation
Pain therapy
consultation
Psychological
consultation
MBSQ
Fatigue Severity
Scale
Chalder Fatigue
Scale
DSQ-PEM
Bell Score
SF-36
COMPASS-31
PHQ-4/9
YSR/11-18R
SCL-90-S
CBCL/6-18R
GAD-7
HADS-D
SSS-8
SSD-12
SOMS-KJ 2
PSS-10
BRCS
ERI
PC-PTSD
JTCI 12-18R
Time point of
collection
Type (serum,
plasma, PBMC)
Number of
aliquots
ME/CFS, myalgic encephalomyelitis; BMI, body mass index; ECG, electrocardiography; ECHO, echocardiography;
EEG, electroencephalography; MBSQ, Munich Berlin Symptom Questionnaire [
19
]; DSQ-PEM, DePaul Symptom
Questionnaire Post-Exertional Malaise short form [
34
]; SF-36, Short Form-36 Health Survey [
46
]; COMPASS-31,
Composite Autonomic Symptom Score 31 [
47
]; PHQ-4/9, Patient Health Questionnaire-4/9 [
48
]; YSR/11-18R,
Youth Self-Report/11-18 Revised [
49
]; SCL-90-S, Symptom Checklist-90-Symptom Inventory [
50
]; CBCL/6-18R,
Child Behavior Checklist/6-18 Revised [
49
]; GAD-7, Generalized Anxiety Disorder 7 [
51
]; HADS-D, Hospital
Anxiety and Depression Scale—Depression Subscale [
52
]; SSS-8, Somatic Symptom Score (8 items) [
53
]; SSD-12,
Schizophrenia Symptoms and Functioning 12 [
54
]; SOMS-KJ 2, the Screening of Somatoform Disorders [
55
];
PSS-10, Perceived Stress Scale 10 [
56
]; BRCS, Brief Resilience Coping Scale [
57
]; ERI, effort–reward imbalance
[
58
]; PC-PTSD, Primary Care Posttraumatic Stress Disorder [
59
]; JTCI 12-18R, Junior Temperament and Character
Inventory (12–18 years); PBMC, peripheral blood mononuclear cell.
J. Clin. Med. 2024,13, 3168 6 of 16
2.6. Patient-Reported Outcome Measures
The Short Form-36 health survey (SF-36) is a cross-disease measurement tool to assess
HRQoL with good internal consistency and discriminatory validity [
60
], consisting of
36 items
to assess eight dimensions of subjective health: physical functioning, physical role
functioning, bodily pain, general health perception, vitality, social functioning, emotional
role functioning, and mental well-being, which can be categorized into the fundamental
dimensions of physical and mental health. Scores range from 0 (most severe health impair-
ment possible) to 100 points (no health restriction at all). The Bell Score is a widely used and
concise tool used to assess the functional impairment of patients with ME/CFS [
45
], with
100% indicating normal health and 0% bedriddenness. The Chalder Fatigue Scale (CFQ)
evaluates 14 items to measure the impact and severity of fatigue’s physical and mental
aspects [
61
]. The Composite Autonomic Symptom Score 31 (COMPASS-31) is a concise
instrument to assess autonomic nervous system dysfunction. It comprises 31 validated
items in six domains: orthostatic intolerance, vasomotor, secretomotor, gastrointestinal,
bladder, and pupillomotor function, with a total score ranging from 0 to 100 [62].
2.7. Collection and Storage of Supplementary Biosamples
If patients provided a standard broad consent together with the MECFS-R consent,
serum, plasma, and PBMCs were collected, processed, and stored viable according to the
local central biobank’s standard operating procedures (SOPs), and their processing time,
type, and number of aliquots were documented within the MECFS-R.
2.8. Statistical Analyses
Statistical analysis was performed using IBM SPSS Statistics 29 (IBM, Armonk, New
York, NY, USA) and R version 4.2.1 “Funny Looking Kid” (the R Foundation for Statistical
Computing, Vienna, Austria). We employed descriptive statistics and frequency analyses to
examine sample characteristics, such as demographics and access to medical care. Fisher’s
exact test or Pearson’s
χ2
test was employed for comparing categorical variables, while
the Wilcoxon rank-sum test was utilized for comparing numeric variables between groups.
The significance level was set to α= 0.05.
3. Results
3.1. Baseline Characteristics
Here we describe a pilot cohort of 174 patients with ME/CFS enrolled in the MECFS-
R from 04/2021 to 03/2023. The cohort had a mean age of 32.6 years (SD 14.9; range
11–61)
. Of the patients, 43/174 (24.7%) were children and adolescents and 136/174 (78.2%)
were female and 62/174 (35.6%) patients were recruited at the MCFC, with a mean age
of
18.9 years
(SD 3.4; range 13–28), including 45/62 (72.6%) females. The CFC enrolled
112/174 (64.5%) patients with a mean age of 41.8 years (SD 11.1; range 18–62), including
91/112 (81.3%) females (Figure 1A,B). The percentage of females was higher among adult
patients compared to children and adolescents (81.7% vs. 67.4%, p= 0.050).
3.2. Participation
At the time of enrollment, 59/158 (37.3%) patients were in school or vocational edu-
cation, 87/174 (55.1%) were employed, 3/174 (1.9%) were in early retirement, and 9/174
(5.7%) reported no current activity. Following the onset of ME/CFS, 14/152 (9.2%) patients
(0/36 children and adolescents vs. 14/116 (12%) adults, p< 0.001) were able to maintain
their pre-illness participation. Of the patients, 13/152 (8.6%) (8/36 (22%) children and
adolescents vs. 5/116 (4.3%) adults, p< 0.001) participated partially with more than 50%
of the pre-illness activity level. Additionally, 22/152 (14%) (12/36 (33%) children and
adolescents vs. 10/116 (8.6%) adults, p< 0.001) participated partially with less than 50%
compared with the pre-illness level. The majority of patients (103/152 (68%), including
16/36 (44%) children and adolescents vs. 87/116 (75%) adults, p< 0.001) were unable to
participate at all in previous education or work.
J. Clin. Med. 2024,13, 3168 7 of 16
J. Clin. Med. 2024, 13, x FOR PEER REVIEW 7 of 16
while the Wilcoxon rank-sum test was utilized for comparing numeric variables between
groups. The signicance level was set to α = 0.05.
3. Results
3.1. Baseline Characteristics
Here we describe a pilot cohort of 174 patients with ME/CFS enrolled in the MECFS-
R from 04/2021 to 03/2023. The cohort had a mean age of 32.6 years (SD 14.9; range 11–61).
Of the patients, 43/174 (24.7%) were children and adolescents and 136/174 (78.2%) were
female and 62/174 (35.6%) patients were recruited at the MCFC, with a mean age of 18.9
years (SD 3.4; range 13–28), including 45/62 (72.6%) females. The CFC enrolled 112/174
(64.5%) patients with a mean age of 41.8 years (SD 11.1; range 18–62), including 91/112
(81.3%) females (Figure 1A,B). The percentage of females was higher among adult patients
compared to children and adolescents (81.7% vs. 67.4%, p = 0.050).
Figure 1. Age Distribution. Histograms show the age distribution of patients included in the
MECFS-R depending on the recruiting center (A) and gender (B). The doed lines at age 18 indicate
the transition from pediatric to adult patients.
3.2. Participation
At the time of enrollment, 59/158 (37.3%) patients were in school or vocational edu-
cation, 87/174 (55.1%) were employed, 3/174 (1.9%) were in early retirement, and 9/174
(5.7%) reported no current activity. Following the onset of ME/CFS, 14/152 (9.2%) patients
(0/36 children and adolescents vs. 14/116 (12%) adults, p < 0.001) were able to maintain
their pre-illness participation. Of the patients, 13/152 (8.6%) (8/36 (22%) children and ad-
olescents vs. 5/116 (4.3%) adults, p < 0.001) participated partially with more than 50% of
the pre-illness activity level. Additionally, 22/152 (14%) (12/36 (33%) children and adoles-
cents vs. 10/116 (8.6%) adults, p < 0.001) participated partially with less than 50% com-
pared with the pre-illness level. The majority of patients (103/152 (68%), including 16/36
(44%) children and adolescents vs. 87/116 (75%) adults, p < 0.001) were unable to partici-
pate at all in previous education or work.
0
5
10
15
10 20 30 40 50 60
Age in [Years]
Absolute Frequency
Center
MCFC
CFC
(A) Age by Center
0
5
10
15
10 20 30 40 50 60
Age in [Years]
Absolute Frequency
Sex
male
female
(B) Age by Sex
Figure 1. Age Distribution. Histograms show the age distribution of patients included in the MECFS-
R depending on the recruiting center (A) and gender (B). The dotted lines at age 18 indicate the
transition from pediatric to adult patients.
3.3. Onset of ME/CFS
Of the patients, 160/174 (92.0%) (36/43 (83.7%) children and adolescents vs. 125/131
(95.4%) adults, p= 0.011) reported an acute viral infection before the onset of ME/CFS. The
most frequent confirmed triggers were SARS-CoV-2 in 82/174 (47.1%) patients (78/131
(59.5%) adults vs. 5/43 (11.6%) children and adolescents, p< 0.001) and EBV in 19/174
(10.9%) patients (11/43 (26%) children and adolescents vs. 10/131 (7.6%) adults, p= 0.012).
An influenza virus infection was documented in 2/174 (1.1%) patients (2/43 (4.7%) children
and adolescents vs. 0/131 (0.0%) adults, p= 0.061). In 5/174 (2.9%) patients (2/43 (4.7%)
children and adolescents vs. 3/131 (2.3%) adults, p= 0.421), multiple infectious triggers
were recalled at the time of disease onset (Figure 2A,B). Other confirmed or probable
infectious triggers were coxsackieviruses, mycoplasma, Borrelia burgdorferi, respiratory
syncytial virus, and Group A streptococci.
3.4. Diagnostic Criteria and Post-Exertional Malaise
All patients met at least one of the four ME/CFS case definitions (CCC, IOM, CDW-R,
PCD-J). Among adult patients tested with the indicated questionnaire, 127/129 (98.4%)
fulfilled the CCC, 108/108 (100%) the IOM, and 106/108 (98.1%) both. Among children and
adolescents tested with the indicated questionnaire, 35/42 (83.3%) fulfilled the CCC, 16/16
(100%) the IOM, 39/39 (100%) the CDW-R, and 16/19 (84.2%) the PCD-J criteria. Most
adults fulfilled the CCC (98.1%) and IOM criteria (100%), because until March 2023 only
patients fulfilling CCC were included at the CFC. Using the DSQ-PEM as a PROM prior to
medical assessment at the CFC or MCFC, only 139/153 (90.8%) patients scored positive
for PEM (21/25 (84.0%) children and adolescents vs. 118/128 (92.2%) adults, p= 0.348)
while all patients clearly indicated PEM when interviewed by an ME/CFS-experienced
physician. Using the DSQ-PEM as a PROM, PEM duration was reported to be 2–3 h by
1/138 (0.7%), 4–10 h by 2/138 (1.4%), 14–24 h by 23/138 (16.6%) (18/117 (15.3%) adults
J. Clin. Med. 2024,13, 3168 8 of 16
vs. 5/21 (23.8%) children and adolescents), and >24 h by 112/138 (81.1%) (97/117 (82.9%)
adults vs. 15/2 (71.4%) children and adolescents) of patients, indicating the majority of
patients had long-lasting PEM.
J. Clin. Med. 2024, 13, x FOR PEER REVIEW 8 of 16
3.3. Onset of ME/CFS
Of the patients, 160/174 (92.0%) (36/43 (83.7%) children and adolescents vs. 125/131
(95.4%) adults, p = 0.011) reported an acute viral infection before the onset of ME/CFS. The
most frequent conrmed triggers were SARS-CoV-2 in 82/174 (47.1%) patients (78/131
(59.5%) adults vs. 5/43 (11.6%) children and adolescents, p < 0.001) and EBV in 19/174
(10.9%) patients (11/43 (26%) children and adolescents vs. 10/131 (7.6%) adults, p = 0.012).
An inuenza virus infection was documented in 2/174 (1.1%) patients (2/43 (4.7%) children
and adolescents vs. 0/131 (0.0%) adults, p = 0.061). In 5/174 (2.9%) patients (2/43 (4.7%)
children and adolescents vs. 3/131 (2.3%) adults, p = 0.421), multiple infectious triggers
were recalled at the time of disease onset (Figure 2A,B). Other conrmed or probable in-
fectious triggers were coxsackieviruses, mycoplasma, Borrelia burgdorferi, respiratory
syncytial virus, and Group A streptococci.
Figure 2. Distribution of ME/CFS Triggers. Bar charts display the absolute frequency and relative
percentage of reported ME/CFS triggers by age group (A) and gender (B).
3.4. Diagnostic Criteria and Post-Exertional Malaise
All patients met at least one of the four ME/CFS case definitions (CCC, IOM, CDW-R,
PCD-J). Among adult patients tested with the indicated questionnaire, 127/129 (98.4%) ful-
filled the CCC, 108/108 (100%) the IOM, and 106/108 (98.1%) both. Among children and ado-
lescents tested with the indicated questionnaire, 35/42 (83.3%) fulfilled the CCC, 16/16 (100%)
the IOM, 39/39 (100%) the CDW-R, and 16/19 (84.2%) the PCD-J criteria. Most adults fulfilled
the CCC (98.1%) and IOM criteria (100%), because until March 2023 only patients fulfilling
CCC were included at the CFC. Using the DSQ-PEM as a PROM prior to medical assessment
at the CFC or MCFC, only 139/153 (90.8%) patients scored positive for PEM (21/25 (84.0%)
children and adolescents vs. 118/128 (92.2%) adults, p = 0.348) while all patients clearly indi-
cated PEM when interviewed by an ME/CFS-experienced physician. Using the DSQ-PEM as
a PROM, PEM duration was reported to be 2–3 h by 1/138 (0.7%), 4–10 h by 2/138 (1.4%), 14–
24 h by 23/138 (16.6%) (18/117 (15.3%) adults vs. 5/21 (23.8%) children and adolescents), and
>24 h by 112/138 (81.1%) (97/117 (82.9%) adults vs. 15/2 (71.4%) children and adolescents) of
patients, indicating the majority of patients had long-lasting PEM.
3.5. Patient-Reported Outcome Measures
The SF-36 was used to assess HRQoL and showed significantly reduced scores in this
ME/CFS cohort across all domains compared to a published healthy German population-
based sample (Figure 3). Overall, the lowest SF-36 scores were reported for the domains
77 ( 58.8 %)
10 ( 7.6 %)
38 ( 29 %)
6 ( 4.6 %)
5 ( 11.6 %) 11 ( 25.6 %)
2 ( 4.7 %)
17 ( 39.5 %)
8 ( 18.6 %)
Adult patients
Pediatric patients
SARS−CoV−2 EBV Influenza Other Infectious Non−infectious SARS−CoV−2 EBV Influenza Other Infectious Non−infectious
0
25
50
75
100
Absolute Frequency
(A) Trigger by Age Group
16 ( 42.1 %)
3 ( 7.9 %)
16 ( 42.1 %)
3 ( 7.9 %)
66 ( 48.5 %)
18 ( 13.2 %)
2 ( 1.5 %)
39 ( 28.7 %)
11 ( 8.1 %)
male
female
SARS−CoV−2 EBV Influenza Other Infectious Non−infectious SARS−CoV−2 EBV Influenza Other Infectious Non−infectious
0
25
50
75
100
Absolute Frequency
(B) Trigger by Sex
Figure 2. Distribution of ME/CFS Triggers. Bar charts display the absolute frequency and relative
percentage of reported ME/CFS triggers by age group (A) and gender (B).
3.5. Patient-Reported Outcome Measures
The SF-36 was used to assess HRQoL and showed significantly reduced scores in this
ME/CFS cohort across all domains compared to a published healthy German population-
based sample (Figure 3). Overall, the lowest SF-36 scores were reported for the domains
vitality and role physical, while the highest scores were found for the mental health
and role emotional subscales. Compared to adults, children and adolescents displayed
significantly higher scores on the domains of mental health (67.9 (SD 16.5) vs. 56.3 (SD
18.8), p= 0.009) and role physical (3.8 (SD 10.0) vs. 0.0 (SD 6.2), p= 0.004) compared to
adults. Furthermore, the self-reported health change in the last year was significantly
better in children and adolescents (35.6 (SD 32.5) vs. 22.8 (SD 35.6), p= 0.049). The median
Bell Score of the cohort was 30.0 (IQR 30.0–40.0) (30.0 (IQR 27.5–40.0) in children and
adolescents vs. 30.0 (IQR 30.0–40.0) in adults, p= 0.467), indicating a severely impaired
functional status (Figure 4A,B). The overall score of the CFQ was 27.6 (SD 3.7). Children
and adolescents reported significantly less fatigue than adult patients (24.4 (SD 5.0) vs.
28.0 (SD 3.3), p= 0.022) (Figure 4C,D). Most patients (128/174 (73.6%)) who completed
the COMPASS-31 suffered from autonomic dysfunction, with moderate symptoms, i.e., a
total score between 20 and 40, in 53/128 (41.4%) adults and 61/128 (47.7%) children and
adolescents, respectively. The total weighted score of the COMPASS-31 ranged from 2
to 89.9, with a mean of 40.1 (SD 15.9) (Figure 4E,F). The COMPASS-31 total scores and
subscores of orthostatic, gastrointestinal, vasomotor, pupillomotor, secretory, and bladder
symptoms are presented in Table 2. Children and adolescents had significantly lower
scores in the gastrointestinal, bladder, and pupillomotor subdomains and total scores but
significantly higher scores for orthostatic intolerance.
J. Clin. Med. 2024,13, 3168 9 of 16
J. Clin. Med. 2024, 13, x FOR PEER REVIEW 9 of 16
vitality and role physical, while the highest scores were found for the mental health and role
emotional subscales. Compared to adults, children and adolescents displayed significantly
higher scores on the domains of mental health (67.9 (SD 16.5) vs. 56.3 (SD 18.8), p = 0.009) and
role physical (3.8 (SD 10.0) vs. 0.0 (SD 6.2), p = 0.004) compared to adults. Furthermore, the self-
reported health change in the last year was significantly better in children and adolescents
(35.6 (SD 32.5) vs. 22.8 (SD 35.6), p = 0.049). The median Bell Score of the cohort was 30.0 (IQR
30.0–40.0) (30.0 (IQR 27.5–40.0) in children and adolescents vs. 30.0 (IQR 30.0–40.0) in adults,
p = 0.467), indicating a severely impaired functional status (Figure 4A,B). The overall score of
the CFQ was 27.6 (SD 3.7). Children and adolescents reported significantly less fatigue than
adult patients (24.4 (SD 5.0) vs. 28.0 (SD 3.3), p = 0.022) (Figure 4C,D). Most patients (128/174
(73.6%)) who completed the COMPASS-31 suffered from autonomic dysfunction, with mod-
erate symptoms, i.e., a total score between 20 and 40, in 53/128 (41.4%) adults and 61/128
(47.7%) children and adolescents, respectively. The total weighted score of the COMPASS-31
ranged from 2 to 89.9, with a mean of 40.1 (SD 15.9) (Figure 4E,F). The COMPASS-31 total
scores and subscores of orthostatic, gastrointestinal, vasomotor, pupillomotor, secretory, and
bladder symptoms are presented in Table 2. Children and adolescents had significantly lower
scores in the gastrointestinal, bladder, and pupillomotor subdomains and total scores but sig-
nificantly higher scores for orthostatic intolerance.
Table 2. Composite Autonomic Symptom Score 31 (COMPASS-31).
All
(n = 128)
Adolescents
(n = 15)
Adults
(n = 113)
Healthy Population 1
(n = 20)
Domain
Mean (SD)
Mean (SD)
Mean (SD)
p-Value
Mean (SD)
Orthostatic intolerance
13.8 (11.2)
21.6 (10.0)
12.8 (11.0)
0.004
5.1 (7.5)
Vasomotor
1.0 (1.6)
0.9 (1.4)
1.0 (1.6)
0.986
0.3 (0.7)
Secretomotor
3.3 (3.0)
2.0 (2.4)
3.5 (3.1)
0.093
1.4 (2.1)
Gastrointestinal
8.1 (5.1)
3.5 (3.0)
8.8 (5.0)
<0.001
3.8 (2.9)
Bladder
1.2 (1.7)
0.1 (0.6)
1.4 (1.8)
0.002
0.3 (0.9)
Pupillomotor
2.7 (1.3)
1.9 (1.0)
2.9 (1.3)
0.002
0.9 (0.9)
Total
40.1 (15.9)
29.9 (11.7)
41.5 (15.9)
0.007
11.2 (9.1)
1 [62]. Autonomic symptoms were assessed by COMPASS-31 questionnaire, considering the total
score (0–100) and the scores of the six subdomains orthostatic intolerance (0–40), vasomotor (0–5),
secretomotor (0–15), gastrointestinal (0–25), bladder (0–10), and pupillomotor (0–5).
Figure 3. Results from the SF-36 questionnaire. Spider diagrams display the results from subdo-
mains of the SF-36 questionnaire for pediatric ME/CFS-R patients (age 11–17 years) (top left), adult
ME/CFS-R patients (age 18–61 years) (boom left), as well as for largely age-matched historic,
healthy control populations aged 14 to 20 years (top right) and 17–79 years (boom right).
Pediatric ME/CFS−R Patients (11−17 Years)
0
20
40
60
80
100
Physical functioning
Role physical
Bodily pain
General health
Vitality
Social functioning
Role emotional
Mental health
Healthy Control Population (14−20 Years)
0
20
40
60
80
100
Physical functioning
Role physical
Bodily pain
General health
Vitality
Social functioning
Role emotional
Mental health
Adult ME/CFS−R Patients (18−61 Years)
0
20
40
60
80
100
Physical functioning
Role physical
Bodily pain
General health
Vitality
Social functioning
Role emotional
Mental health
Healthy Control Population (17−79 Years)
0
20
40
60
80
100
Physical functioning
Role physical
Bodily pain
General health
Vitality
Social functioning
Role emotional
Mental health
Figure 3. Results from the SF-36 questionnaire. Spider diagrams display the results from subdomains
of the SF-36 questionnaire for pediatric ME/CFS-R patients (age 11–17 years) (top left), adult ME/CFS-
R patients (age 18–61 years) (bottom left), as well as for largely age-matched historic, healthy control
populations aged 14 to 20 years (top right) and 17–79 years (bottom right).
J. Clin. Med. 2024, 13, x FOR PEER REVIEW 10 of 16
Figure 4. Results from Patient-Reported Outcome Measures. Boxplots display the results from the
Bell Score, Chalder Fatigue Scale, and COMPASS-31 questionnaire for children and adolescents ver-
sus adult patients (A,C,E) and male versus female patients (B,D,F).
4. Discussion
4.1. Aim and Structure of the Registry Study
Here, we report on the aims, structure, and implementation of the German ME/CFS
registry, including data from a pilot cohort of 174 adult and pediatric patients recruited at
the Munich Chronic Fatigue Center for Young People (MCFC) and the Charité Fatigue
Center (CFC) in Berlin.
0
20
40
60
80
100
Adult patients Pediatric patients
Bell Score
(A) Bell Score by Age Group
0
20
40
60
80
100
male female
Bell Score
(B) Bell Score by Sex
0
5
10
15
20
25
30
Adult patients Pediatric patients
Chalder Fatigue Scale
(C) Chalder Fatigue Scale by Age Group
0
5
10
15
20
25
30
male female
Chalder Fatigue Scale
(D) Chalder Fatigue Scale by Sex
0
20
40
60
80
100
Adult patients Pediatric patients
COMPASS−31
(E) COMPASS−31 by Age Group
0
20
40
60
80
100
male female
COMPASS−31
(F) COMPASS−31 by Sex
Figure 4. Results from Patient-Reported Outcome Measures. Boxplots display the results from the
Bell Score, Chalder Fatigue Scale, and COMPASS-31 questionnaire for children and adolescents
versus adult patients (A,C,E) and male versus female patients (B,D,F).
J. Clin. Med. 2024,13, 3168 10 of 16
Table 2. Composite Autonomic Symptom Score 31 (COMPASS-31).
All
(n= 128)
Adolescents
(n= 15)
Adults
(n= 113)
Healthy
Population 1
(n= 20)
Domain Mean (SD) Mean (SD) Mean (SD) p-Value Mean (SD)
Orthostatic
intolerance 13.8 (11.2) 21.6 (10.0) 12.8 (11.0) 0.004 5.1 (7.5)
Vasomotor 1.0 (1.6) 0.9 (1.4) 1.0 (1.6) 0.986 0.3 (0.7)
Secretomotor 3.3 (3.0) 2.0 (2.4) 3.5 (3.1) 0.093 1.4 (2.1)
Gastrointestinal
8.1 (5.1) 3.5 (3.0) 8.8 (5.0) <0.001 3.8 (2.9)
Bladder 1.2 (1.7) 0.1 (0.6) 1.4 (1.8) 0.002 0.3 (0.9)
Pupillomotor 2.7 (1.3) 1.9 (1.0) 2.9 (1.3) 0.002 0.9 (0.9)
Total 40.1 (15.9) 29.9 (11.7) 41.5 (15.9) 0.007 11.2 (9.1)
1
[
62
]. Autonomic symptoms were assessed by COMPASS-31 questionnaire, considering the total score (
0–100)
and the scores of the six subdomains orthostatic intolerance (0–40), vasomotor (0–5), secretomotor (0–15), gastroin-
testinal (0–25), bladder (0–10), and pupillomotor (0–5).
4. Discussion
4.1. Aim and Structure of the Registry Study
Here, we report on the aims, structure, and implementation of the German ME/CFS
registry, including data from a pilot cohort of 174 adult and pediatric patients recruited
at the Munich Chronic Fatigue Center for Young People (MCFC) and the CharitéFatigue
Center (CFC) in Berlin.
The recent COVID-19 pandemic has resulted in a significant rise in the number of
people worldwide experiencing persistent post-viral syndromes, including ME/CFS. Ac-
cordingly, scientific and clinical interest and needs in this field are increasing [
63
]. It is
estimated that 19–58% of patients with PASC, also known as post-COVID-19 condition
(ICD-10 CM U09.9), meet the diagnostic criteria for ME/CFS [
15
,
18
,
64
]. We recently de-
scribed ME/CFS following COVID-19 in children as young as 11–14 years, with severe
impact on their daily function [
19
]. Our user-friendly MECFS-R, with its standard dataset,
novel questionnaires such as the MBSQ [
19
], and accompanying information, can help
PASC teams develop local standard approaches diagnosing and phenotyping ME/CFS
following COVID-19.
Despite the considerable impact on health, participation, and HRQoL of people with
ME/CFS as well as significant socioeconomic costs due to this disabling disorder, limited
knowledge is available regarding the etiology, risk factors, diagnostic markers, treatment
approaches, prognosis, and prevention [
35
,
65
,
66
]. Research on ME/CFS has been hindered
by unsuitable case definitions, relatively small study cohorts, the lack of reliable diagnostic
and prognostic biomarkers, and limited funding for research and care [
67
,
68
]. However,
generating comprehensive and large-scale routine clinical data, registries can help gain
deeper insight into clinical features, pathophysiology, and care options.
To address these issues and facilitate future research on ME/CFS, we developed and
implemented the German ME/CFS registry and biobank at two German tertiary care
centers specialized in diagnosing and treating ME/CFS in adults, adolescents, and children.
This registry aims to harmonize the diagnostic approach to ME/CFS and generate a large,
well-characterized study cohort via standardized deep clinical and biological phenotyping.
Instruction manuals and individual training will be provided to future participating
centers to support a valid comprehensive standard dataset. We expect to generate knowl-
edge about potential ME/CFS subgroups, natural disease trajectories, and current medical
care across all age groups and provide baseline data for clinical and translational research.
Previous ME/CFS case definitions often have not required PEM as a cardinal symp-
tom of ME/CFS, resulting in patient cohorts that included non-ME/CFS cases, possibly
explaining conflicting research findings [
69
]. This registry only includes ME/CFS cases
defined by diagnostic criteria requiring PEM, including the internationally recommended
J. Clin. Med. 2024,13, 3168 11 of 16
IOM criteria, the CCC, and two pediatric criteria sets. To ensure a standardized quantita-
tive evaluation of these criteria, the MBSQ was developed as a novel questionnaire with
diagnostic algorithms for adults and pediatric patients [
19
] and is being suggested for use
at all participating MECFS-R centers.
In addition, several published PROMs have been selected as important diagnostic
tools based on expert recommendations and according to common data elements suggested
by the National Institute of Neurological Disorders and Stroke (NINDS) [
35
]. They address
clinical and psychosocial features of ME/CFS such as distinct symptoms, daily function,
and HRQoL [
70
]. We are currently programming all PROMs and additional questionnaires
in the REDCap format with mapping to the MECFS-R DIS format to facilitate data capture
directly from patients with state-of-the-art data protection measures. The inclusion of
a standard dataset as well as additional parameters allows flexible data entry protocols
according to the local clinical standards of participating centers.
4.2. Clinical Characterization of Pilot Study Participants
The pilot cohort of 174 patients in this registry included 131 adults as well as
43 adolescents and children with ME/CFS. The female predominance and age peaks
observed in this cohort are well-known for ME/CFS [
71
,
72
]. The youngest patient in our
cohort was 11 years old, in line with a lower prevalence of ME/CFS in childhood compared
to adolescence and adulthood [73].
Almost all adult patients fulfilled both the CCC and IOM criteria. The proportion of
study participants who met the evaluated case definition was 100% for IOM and CDW-R
and approximately 89% and 83% for the more stringent PCD-J and CCC, respectively.
According to the medical interview, not all patients with physician-validated PEM ful-
filled the PEM criteria when using the DSQ-PEM as a PROM. This is congruent with our
clinical experience demonstrating that self-assessment of PEM and its duration can be
difficult, especially in young patients and patients who largely avoid PEM by consequent
pacing. The newly established, age-adapted MBSQ, together with the DSQ-PEM, thus
helps in assessing PEM and diagnosing ME/CFS [
19
] but cannot replace a detailed medical
personnel interview.
ME/CFS is known to be most commonly triggered by an acute viral disease, with a
significant impact of the COVID-19 pandemic on ME/CFS prevalence [
74
]. Accordingly,
a predominance of SARS-CoV-2 was identified in adults (59.5%) and EBV in pediatric
patients (26%) in our first cohort. Non-infectious triggers are most likely underrepresented
since both recruiting centers are focused on post-infectious ME/CFS as immunological
departments [
8
,
19
,
64
]. However, the registry allows a very precise documentation of trig-
gering events including clinical and laboratory data from the time of initial symptoms, and
therefore facilitates a stratification of study participants along confirmed versus probable
and self-reported triggers.
Notably, only a minority of study participants were able to work, and more than
half of the children and adolescents were not able to participate in school. This was in
line with previous studies reporting a worrying impact of ME/CFS on education and
social participation [
75
]. The physical and social functioning of MECFS-R participants was
severely reduced as indicated by low Bell and SF-36 scores, while higher scores were found
for emotional role functioning and psychological well-being [
76
,
77
]. This aligns with earlier
reports indicating that the HRQoL of patients with ME/CFS compared to other chronic
diseases is severely compromised, mainly due to physical
impairment [8,19,64,78]
. More-
over, in support of published results [79], MECFS-R participants suffered from significant
autonomic dysfunction as indicated by high COMPASS-31 scores. We recommend the Bell
Score, SF-36, and COMPASS-31 as standard measures for clinical phenotyping to facilitate
both local medical care as well as future studies with secondary use of MECFS-R data.
J. Clin. Med. 2024,13, 3168 12 of 16
4.3. Strengths and Limitations
To our knowledge, this is the first multicenter registry collecting cross-age routine
clinical data and information on biosamples from ME/CFS patients diagnosed by trained
staff and in a standardized manner at specialized tertiary care centers, with obligatory
quantification of ME/CFS symptoms and detailed assessment of PEM as an essential
diagnostic criterion.
To date, a few registries for ME/CFS exist with different scopes and selection criteria.
The UK biobank includes patients diagnosed with ME/CFS by primary care physicians and
complies with the CCC and/or the CDC-1994 (“Fukuda”) criteria [
80
], and the
YOU + ME
registry relies on self-report. Both approaches support collecting large-scale data but might
face the risk of false diagnoses and lack much of the detailed clinical information provided
by the MECFS-R. Furthermore, the Collaborative of Fatigue Following Infection, which
collects data and biosamples from several prospective cohort studies, exists [
81
]. The
MECFS-R offers a comprehensive dataset with more than 10,000 variables per patient for
secondary use in future clinical and translational studies, including standardized data on
clinical phenotypes, patient journeys, and impact on daily life.
A strength of the MECFS-R is the collection of routine data which means that neither
the patient nor the treating physician must make an extra effort to participate, except for
the informed consenting procedure. Furthermore, different levels of data complexity can be
chosen by the participating centers, and datasets can be adapted to local clinical care protocols.
We provide a selected core dataset from a pilot group of study participants as an
example which aligns well with published data from other cohorts. Especially in pediatrics,
the MECFS-R is expected to contribute significant novel evidence in many aspects of this
complex disease.
Since routine data are collected, follow-up visits documented in the MECFS-R do not
follow strict protocols as in prospective cohort studies. However, the registry may serve
as a basis for separate longitudinal follow-up studies. As a second limitation, the quality
and quantity of individual datasets might differ depending on the level of training and
resources available for documentation at the participating hospitals or private practices.
However, subgroup analyses will allow for interpretation without bias and even small
datasets from many patients might contribute important information. Finally, the pilot
group of patients presented here is relatively small and not representative but provided
important data to validate the comprehensive MECFS-R concept.
5. Conclusions
We here first report on a multicenter German ME/CFS registry study, which collects
comprehensive, standardized data on clinical features and biospecimens from adults,
adolescents, and children. The MECFS-R team standardized to a large set of core diagnostic
measures and offers specific training to members of future participating centers. The
inclusion of patients with well-defined ME/CFS and obligatory PEM, together with detailed
information on clinical and laboratory findings as well as collected biosamples, is expected
to significantly enhance clinical and translational research on ME/CFS and thereby improve
medical care for affected patients of any age in Germany and beyond.
Author Contributions: Conceptualization, H.H., R.P., K.G., C.H., K.W., L.L.M., M.H., D.S., Q.D., C.C.,
A.L., Y.M., H.Z., H.F., F.S., S.S., D.B.R.H., A.H., C.S. and U.B.; Methodology, H.H., R.P., K.G., C.H.,
K.W., L.L.M., M.H., D.S., Q.D., C.C., A.G., A.K., A.L., Y.M., H.Z., H.F., F.S., C.W., S.S., D.B.R.H., A.H.,
K.M., C.S. and U.B.; Validation, H.H., R.P., C.H. and L.L.M.; Formal analysis, H.H., R.P., L.L.M. and
U.B.; Investigation, H.H., R.P., L.L.M., M.H., Q.D., C.C., A.G., A.K., A.L., Y.M., H.Z., C.W., S.S., C.S.
and U.B.; Resources, C.S. and U.B.; Data curation, H.H., R.P., K.G., C.H., K.W., L.L.M., D.S., C.C.,
H.F., F.S., A.H. and K.M.; Writing—original draft, H.H., R.P., L.L.M. and U.B.; Writing—review and
editing, H.H., R.P., K.G., C.H., K.W., L.L.M., M.H., D.S., Q.D., C.C., A.G., A.K., A.L., Y.M., H.Z., H.F.,
F.S., C.W., S.S., D.B.R.H., A.H., K.M., C.S. and U.B.; Visualization, R.P. and L.L.M.; Supervision, K.G.,
C.S. and U.B.; Project administration, K.G., C.H., D.S., H.F., A.H., K.M. and U.B.; Funding acquisition,
C.S. and U.B. All authors have read and agreed to the published version of the manuscript.
J. Clin. Med. 2024,13, 3168 13 of 16
Funding: The MECFS-R and biobank was funded by the Menschen fuer Kinder e:V. and the Federal
Ministry of Health (BMG) (project 01EJ2204) and the Weidenhammer-Zoebele Foundation.
Institutional Review Board Statement: The study was approved by the local ethics committee at
TUM on 24 February 2021 (116/21 S) and Charitèon 9 May 2022 (EA/006/22) and conducted in
accordance with the Declaration of Helsinki.
Informed Consent Statement: Patients and legal guardians of patients younger than 18 years gave
written and informed consent prior to inclusion into the MECFS-R.
Data Availability Statement: The data presented in this study are available from the corresponding
author, upon reasonable request.
Conflicts of Interest: U.B. received research grants from the Federal Ministry of Education and
Research (BMBF), the BMG, the Bavarian State Ministry of Health and Care (StMGP), the Bavarian
State Ministry of Science and the Arts (StMWK), the German Center for Infection Research (DZIF), the
People for Children (Menschen fuer Kinder) foundation, the WZS, the Lost Voices Foundation (LVS),
the Siemens Caring Hands Foundation, and the ME/CFS Research Foundation (ME/CFS RF). C.S.
consulted for Roche, Celltrend, and Bayer; she received support for clinical trials by Bayer, Fresenius,
and Miltenyi, honoraria for lectures by Fresenius, AstraZeneca, BMS, Roche, Bayer, and Novartis,
and research grants from the German Research Association (DFG), the BMBF, the BMG, the WZS,
the LVS, and the ME/CFS RF. The authors declare no conflicts of interest. The funders of individual
researchers had no role in the design of the study, the collection, analyses, and interpretation of data,
the writing of the manuscript, or the decision to publish results.
References
1.
David, A.S.; Wessely, S.; Pelosi, A.J. Postviral fatigue syndrome: Time for a new approach. Br. Med. J. (Clin. Res. Ed.) 1988,296,
696–699. [CrossRef] [PubMed]
2.
Rowe, P.C.; Underhill, R.A.; Friedman, K.J.; Gurwitt, A.; Medow, M.S.; Schwartz, M.S.; Speight, N.; Stewart, J.M.; Vallings, R.;
Rowe, K.S. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Diagnosis and Management in Young People: A Primer. Front.
Pediatr. 2017,5, 121. [CrossRef] [PubMed]
3.
Lim, E.J.; Ahn, Y.C.; Jang, E.S.; Lee, S.W.; Lee, S.H.; Son, C.G. Systematic review and meta-analysis of the prevalence of chronic
fatigue syndrome/myalgic encephalomyelitis (CFS/ME). J. Transl. Med. 2020,18, 100. [CrossRef] [PubMed]
4.
IQWiG. Myalgische Enzephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): Aktueller Kenntnisstand. 2023. Available online:
https://www.iqwig.de/download/n21-01_me- cfs-aktueller-kenntnisstand_abschlussbericht_v1-0.pdf (accessed on 15 January
2024).
5.
Cairns, R.; Hotopf, M. A systematic review describing the prognosis of chronic fatigue syndrome. Occup. Med. 2005,55, 20–31.
[CrossRef] [PubMed]
6.
Bakken, I.J.; Tveito, K.; Gunnes, N.; Ghaderi, S.; Stoltenberg, C.; Trogstad, L.; Håberg, S.E.; Magnus, P. Two age peaks in the
incidence of chronic fatigue syndrome/myalgic encephalomyelitis: A population-based registry study from Norway 2008–2012.
BMC Med. 2014,12, 167.
7.
Bested, A.C.; Marshall, L.M. Review of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: An evidence-based approach to
diagnosis and management by clinicians. Rev. Environ. Health 2015,30, 223–249. [CrossRef] [PubMed]
8.
Pricoco, R.; Meidel, P.; Hofberger, T.; Zietemann, H.; Mueller, Y.; Wiehler, K.; Michel, K.; Paulick, J.; Leone, A.; Haegele, M.; et al.
One-year follow-up of young people with ME/CFS following infectious mononucleosis by Epstein-Barr virus. Front. Pediatr.
2023,11, 1266738. [CrossRef]
9.
Buchwald, D.; Cheney, P.R.; Peterson, D.L.; Henry, B.; Wormsley, S.B.; Geiger, A.; Ablashi, D.V.; Salahuddin, S.Z.; Saxinger, C.;
Biddle, R.; et al. A chronic illness characterized by fatigue, neurologic and immunologic disorders, and active human herpesvirus
type 6 infection. Ann. Intern. Med. 1992,116 (Suppl. S1), S103–S113. [CrossRef]
10.
Hickie, I.; Davenport, T.; Wakefield, D.; Vollmer-Conna, U.; Cameron, B.; Vernon, S.D.; Reeves, W.C.; Lloyd, A. Post-infective and
chronic fatigue syndromes precipitated by viral and non-viral pathogens: Prospective cohort study. Bmj 2006,333, 575. [CrossRef]
[PubMed]
11.
Wu, Y.; Ma, S.; Zhang, L.; Zu, D.; Gu, F.; Ding, X.; Zhang, L. Clinical manifestations and laboratory results of 61 children with
infectious mononucleosis. J. Int. Med. Res. 2020,48, 300060520924550. [CrossRef]
12.
Pedersen, M.; Asprusten, T.T.; Godang, K.; Leegaard, T.M.; Osnes, L.T.; Skovlund, E.; Tjade, T.; Oie, M.G.; Wyller, V.B.B. Predictors
of chronic fatigue in adolescents six months after acute Epstein-Barr virus infection: A prospective cohort study. Brain Behav.
Immun. 2019,75, 94–100. [CrossRef] [PubMed]
13.
Dunmire, S.K.; Hogquist, K.A.; Balfour, H.H. Infectious Mononucleosis. Curr. Top. Microbiol. Immunol. 2015,390 Pt 1, 211–240.
[PubMed]
14.
Katz, B.Z.; Shiraishi, Y.; Mears, C.J.; Binns, H.J.; Taylor, R. Chronic fatigue syndrome after infectious mononucleosis in adolescents.
Pediatrics 2009,124, 189–193. [CrossRef]
J. Clin. Med. 2024,13, 3168 14 of 16
15.
Jason, L.A.; Dorri, J.A. ME/CFS and Post-Exertional Malaise among Patients with Long COVID. Neurol. Int. 2022,15, 1–11.
[CrossRef] [PubMed]
16.
González-Hermosillo, J.A.; Martínez-López, J.P.; Carrillo-Lampón, S.A.; Ruiz-Ojeda, D.; Herrera-Ramírez, S.; Amezcua-Guerra,
L.M.; Martínez-Alvarado, M.d.R. Post-Acute COVID-19 Symptoms, a Potential Link with Myalgic Encephalomyelitis/Chronic
Fatigue Syndrome: A 6-Month Survey in a Mexican Cohort. Brain Sci. 2021,11, 760. [CrossRef] [PubMed]
17.
Bonilla, H.; Quach, T.C.; Tiwari, A.; Bonilla, A.E.; Miglis, M.; Yang, P.C.; Eggert, L.E.; Sharifi, H.; Horomanski, A.; Subramanian,
A.; et al. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome is common in post-acute sequelae of SARS-CoV-2 infection
(PASC): Results from a post-COVID-19 multidisciplinary clinic. Front. Neurol. 2023,14, 1090747. [CrossRef] [PubMed]
18.
Reuken, P.A.; Besteher, B.; Finke, K.; Fischer, A.; Holl, A.; Katzer, K.; Lehmann-Pohl, K.; Lemhöfer, C.; Nowka, M.; Puta, C.; et al.
Longterm course of neuropsychological symptoms and ME/CFS after SARS-CoV-2-infection: A prospective registry study. Eur.
Arch. Psychiatry Clin. Neurosci. 2023. [CrossRef] [PubMed]
19.
Peo, L.C.; Wiehler, K.; Paulick, J.; Gerrer, K.; Leone, A.; Viereck, A.; Haegele, M.; Stojanov, S.; Warlitz, C.; Augustin, S.; et al.
Pediatric and adult patients with ME/CFS following COVID-19: A structured approach to diagnosis using the Munich Berlin
Symptom Questionnaire (MBSQ). Eur. J. Pediatr. 2024,183, 1265–1276. [CrossRef] [PubMed]
20.
Komaroff, A.L.; Bateman, L. Will COVID-19 Lead to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome? Front. Med. 2020,7,
606824. [CrossRef] [PubMed]
21.
Mirin, A.A.; Dimmock, M.E.; Jason, L.A. Updated ME/CFS prevalence estimates reflecting post-COVID increases and associated
economic costs and funding implications. Fatigue Biomed. Health Behav. 2022,10, 83–93. [CrossRef]
22.
Scheibenbogen, C.; Freitag, H.; Blanco, J.; Capelli, E.; Lacerda, E.; Authier, J.; Meeus, M.; Castro Marrero, J.; Nora-Krukle, Z.; Oltra,
E.; et al. The European ME/CFS Biomarker Landscape project: An initiative of the European network Euromene. J. Transl. Med.
2017,15, 162. [CrossRef] [PubMed]
23.
Mensah, F.K.F.; Bansal, A.S.; Ford, B.; Cambridge, G. Chronic fatigue syndrome and the immune system: Where are we now?
Neurophysiol. Clin. 2017,47, 131–138. [CrossRef] [PubMed]
24.
Sulheim, D.; Fagermoen, E.; Winger, A.; Andersen, A.M.; Godang, K.; Müller, F.; Rowe, P.C.; Saul, J.P.; Skovlund, E.; Øie, M.G.;
et al. Disease mechanisms and clonidine treatment in adolescent chronic fatigue syndrome: A combined cross-sectional and
randomized clinical trial. JAMA Pediatr. 2014,168, 351–360. [CrossRef] [PubMed]
25.
Klimas, N.G.; Broderick, G.; Fletcher, M.A. Biomarkers for chronic fatigue. Brain Behav. Immun. 2012,26, 1202–1210. [CrossRef]
[PubMed]
26.
Scheibenbogen, C.; Loebel, M.; Freitag, H.; Krueger, A.; Bauer, S.; Antelmann, M.; Doehner, W.; Scherbakov, N.; Heidecke, H.;
Reinke, P.; et al. Immunoadsorption to remove ss2 adrenergic receptor antibodies in Chronic Fatigue Syndrome CFS/ME. PLoS
ONE 2018,13, e0193672. [CrossRef] [PubMed]
27.
Sotzny, F.; Blanco, J.; Capelli, E.; Castro-Marrero, J.; Steiner, S.; Murovska, M.; Scheibenbogen, C. Myalgic Encephalomyeli-
tis/Chronic Fatigue Syndrome—Evidence for an autoimmune disease. Autoimmun. Rev. 2018,17, 601–609. [CrossRef] [PubMed]
28.
Yang, C.A.; Bauer, S.; Ho, Y.C.; Sotzny, F.; Chang, J.G.; Scheibenbogen, C. The expression signature of very long non-coding RNA
in myalgic encephalomyelitis/chronic fatigue syndrome. J. Transl. Med. 2018,16, 231. [CrossRef] [PubMed]
29.
Hajdarevic, R.; Lande, A.; Mehlsen, J.; Rydland, A.; Sosa, D.D.; Strand, E.B.; Mella, O.; Pociot, F.; Fluge, O.; Lie, B.A.; et al. Genetic
association study in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) identifies several potential risk loci. Brain
Behav. Immun. 2022,102, 362–369. [CrossRef] [PubMed]
30.
Kachuri, L.; Francis, S.S.; Morrison, M.L.; Wendt, G.A.; Bosse, Y.; Cavazos, T.B.; Rashkin, S.R.; Ziv, E.; Witte, J.S. The landscape of
host genetic factors involved in immune response to common viral infections. Genome Med. 2020,12, 93. [CrossRef] [PubMed]
31.
Ariza, M.E. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: The Human Herpesviruses Are Back! Biomolecules 2021,11,
185. [CrossRef] [PubMed]
32.
Carruthers, B.M.; Jain, A.K.; De Meirleir, K.L.; Peterson, D.L.; Klimas, N.G.; Lemer, A.M.; Bested, A.C.; Flor-Henry, P.; Joshi, P.;
Powles, A.C.P.; et al. Myalgic encephalomyelitis/chronic fatigue syndrome: Clinical working case definition, diagnostic and
treatment protocols. J. Chronic Fatigue Syndr. 2003,11, 7–115. [CrossRef]
33.
Beyond Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Redefining an Illness. Mil. Med. 2015,180, 721–723. [CrossRef]
[PubMed]
34.
Jason, L.A.; Sunnquist, M. The Development of the DePaul Symptom Questionnaire: Original, Expanded, Brief, and Pediatric
Versions. Front. Pediatr. 2018,6, 330. [CrossRef] [PubMed]
35.
Nacul, L.; Authier, F.J.; Scheibenbogen, C.; Lorusso, L.; Helland, I.B.; Martin, J.A.; Sirbu, C.A.; Mengshoel, A.M.; Polo, O.; Behrends,
U.; et al. European Network on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (EUROMENE): Expert Consensus on the
Diagnosis, Service Provision, and Care of People with ME/CFS in Europe. Medicina 2021,57, 510. [CrossRef] [PubMed]
36.
Baum, E.; Lindner, N.; Andreas, S.; Behrends, U.; Scheibenbogen, C.; Christmann, T.; Horneber, M.; Klassen, O.; Geisler, P.; Maisel,
P. S3-Leitlinie Müdigkeit. AWMF-Register-Nr. 053-002. 2022 November. Available online: https://register.awmf.org/assets/
guidelines/053-002l_S3_Muedigkeit_2023-01_01.pdf (accessed on 14 May 2024).
37.
Froehlich, L.; Hattesohl, D.B.R.; Cotler, J.; Jason, L.A.; Scheibenbogen, C.; Behrends, U. Causal attributions and perceived stigma
for myalgic encephalomyelitis/chronic fatigue syndrome. J. Health Psychol. 2021,27, 2291–2304. [CrossRef] [PubMed]
J. Clin. Med. 2024,13, 3168 15 of 16
38.
Fennell, P.A.; Dorr, N.; George, S.S. Elements of Suffering in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: The
Experience of Loss, Grief, Stigma, and Trauma in the Severely and Very Severely Affected. Healthcare 2021,9, 553. [CrossRef]
[PubMed]
39.
MRI Chronic Fatigue Center for Young People in Munich (MCFC). Available online: https://www.mri.tum.de/chronische-
fatigue-centrum-fuer-junge-menschen- mcfc (accessed on 7 May 2024).
40. CharitéFatigue Center (CFC). Available online: https://cfc.charite.de (accessed on 7 May 2024).
41.
Rothgang, M.; Cantner, U.; Dehio, J.; Engel, D.; Fertig, M.; Graf, H.; Hinzmann, S.; Linshalm, E.; Ploder, M.; Scholz, A.M.; et al.
Cluster policy: Insights from the German leading edge cluster competition. J. Open Innov. Technol. Mark. Complex. 2017,3, 18.
[CrossRef]
42.
Prasser, F.; Kohlbacher, O.; Mansmann, U.; Bauer, B.; Kuhn, K.A. Data Integration for Future Medicine (DIFUTURE). Methods Inf.
Med. 2018,57, e57–e65. [CrossRef] [PubMed]
43. Centers of Disease Control and Prevention (CDC). Available online: https://www.cdc.gov (accessed on 7 May 2024).
44.
Jason, L.A.; Jordan, K.; Miike, T.; Bell, D.S.; Lapp, C.; Torres-Harding, S.; Rowe, K.; Gurwitt, A.; De Meirleir, K.; Van Hoof, E.L.S. A
Pediatric Case Definition for Myalgic Encephalomyelitis and Chronic Fatigue Syndrome. J. Chronic Fatigue Syndr. 2006,13, 1–44.
[CrossRef]
45.
Bell, D.S. The Doctor’s Guide to Chronic Fatigue Syndrome: Understanding, Treating, and Living with CFIDS; Addison-Wesley Pub. Co:
Boston, MA, USA, 1995.
46.
Ware, J.E., Jr.; Sherbourne, C.D. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection.
Med. Care 1992,30, 473–483. [CrossRef] [PubMed]
47.
Suarez, G.A.; Opfer-Gehrking, T.L.; Offord, K.P.; Atkinson, E.J.; O’Brien, P.C.; Low, P.A. The Autonomic Symptom Profile: A new
instrument to assess autonomic symptoms. Neurology 1999,52, 523–528. [CrossRef] [PubMed]
48.
Spitzer, R.L.; Kroenke, K.; Williams, J.B. Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study.
Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. Jama 1999,282, 1737–1744. [CrossRef] [PubMed]
49.
Achenbach, T.M. Manual for ASEBA School-Age Forms & Profiles; University of Vermont, Research Center for Children, Youth &
Families: Burlington, VT, USA, 2001.
50.
Derogatis, L.R. SCL-90-R: Administration, Scoring and Procedures; Manual II for the R (evised) Version and Other Instruments of the
Psychopathology Rating Scale Series; Clinical Psychometric Research: Towson, MD, USA, 1983.
51.
Spitzer, R.L.; Kroenke, K.; Williams, J.B.; Löwe, B. A brief measure for assessing generalized anxiety disorder: The GAD-7. Arch.
Intern. Med. 2006,166, 1092–1097. [CrossRef] [PubMed]
52.
Zigmond, A.S.; Snaith, R.P. The hospital anxiety and depression scale. Acta Psychiatr. Scand. 1983,67, 361–370. [CrossRef]
[PubMed]
53.
Gierk, B.; Kohlmann, S.; Kroenke, K.; Spangenberg, L.; Zenger, M.; Brähler, E.; Löwe, B. The Somatic Symptom Scale–8 (SSS-8): A
Brief Measure of Somatic Symptom Burden. JAMA Intern. Med. 2014,174, 399–407. [CrossRef] [PubMed]
54.
Toussaint, A.; Murray, A.M.; Voigt, K.; Herzog, A.; Gierk, B.; Kroenke, K.; Rief, W.; Henningsen, P.; Löwe, B. Development and
Validation of the Somatic Symptom Disorder-B Criteria Scale (SSD-12). Psychosom. Med. 2016,78, 5–12. [CrossRef] [PubMed]
55.
Kleinstäuber, M.; Hiller, W.; Rief, W. The Screening of Somatoform Disorders (SOMS): Development of a new distress index [Das
Screening für somatoforme Störungen: Entwicklung eines neuen Beeinträchtigungsindex]. Verhal. Verhal. 2013,34, 361–377.
56. Cohen, S.; Kamarck, T.; Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 1983,24, 385–396. [CrossRef]
57.
Sinclair, V.G.; Wallston, K.A. The development and psychometric evaluation of the Brief Resilient Coping Scale. Assessment 2004,
11, 94–101. [CrossRef] [PubMed]
58. Siegrist, J. Adverse health effects of high-effort/low-reward conditions. J. Occup. Health Psychol. 1996,1, 27–41. [CrossRef]
59.
Cameron, R.P.; Gusman, D. The primary care PTSD screen (PC-PTSD): Development and operating characteristics. Prim. Care
Psychiatry 2003,9, 9–14.
60.
Morfeld, M.; Kirchberger, I.; Bullinger, M. SF-36 Fragebogen zum Gesundheitszustand: Deutsche Version des Short Form-36 Health
Survey; Hogrefe: Göttingen, Germany, 2011.
61.
Chalder, T.; Berelowitz, G.; Pawlikowska, T.; Watts, L.; Wessely, S.; Wright, D.; Wallace, E.P. Development of a fatigue scale. J.
Psychosom. Res. 1993,37, 147–153. [CrossRef] [PubMed]
62.
Hilz, M.-J.; Wang, R.; Singer, W. Validation of the Composite Autonomic Symptom Score 31 in the German language. Neurol. Sci.
2022,43, 365–371. [CrossRef] [PubMed]
63.
Komaroff, A.L.; Lipkin, W.I. ME/CFS and Long COVID share similar symptoms and biological abnormalities: Road map to the
literature. Front. Med. 2023,10, 1187163. [CrossRef] [PubMed]
64.
Kedor, C.; Freitag, H.; Meyer-Arndt, L.; Wittke, K.; Hanitsch, L.G.; Zoller, T.; Steinbeis, F.; Haffke, M.; Rudolf, G.; Heidecker,
B.; et al. A prospective observational study of post-COVID-19 chronic fatigue syndrome following the first pandemic wave in
Germany and biomarkers associated with symptom severity. Nat. Commun. 2022,13, 5104. [CrossRef] [PubMed]
65.
Scheibenbogen, C.; Bellmann-Strobl, J.T.; Heindrich, C.; Wittke, K.; Stein, E.; Franke, C.; Prüss, H.; Preßler, H.; Machule, M.-L.;
Audebert, H.; et al. Fighting Post-COVID and ME/CFS—Development of curative therapies. Front. Med. 2023,10, 1194754.
[CrossRef] [PubMed]
J. Clin. Med. 2024,13, 3168 16 of 16
66.
Bateman, L.; Bested, A.C.; Bonilla, H.F.; Chheda, B.V.; Chu, L.; Curtin, J.M.; Dempsey, T.T.; Dimmock, M.E.; Dowell, T.G.;
Felsenstein, D.; et al. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Essentials of Diagnosis and Management. Mayo
Clin. Proc. 2021,96, 2861–2878. [CrossRef]
67.
Nacul, L.; Lacerda, E.M.; Kingdon, C.C.; Curran, H.; Bowman, E.W. How have selection bias and disease misclassification
undermined the validity of myalgic encephalomyelitis/chronic fatigue syndrome studies? J. Health Psychol. 2019,24, 1765–1769.
[CrossRef] [PubMed]
68.
Malato, J.; Graça, L.; Sepúlveda, N. Impact of Misdiagnosis in Case-Control Studies of Myalgic Encephalomyelitis/Chronic
Fatigue Syndrome. Diagnostics 2023,13, 531. [CrossRef] [PubMed]
69.
Clayton, E.W. Beyond myalgic encephalomyelitis/chronic fatigue syndrome: An IOM report on redefining an illness. JAMA 2015,
313, 1101–1102. [CrossRef] [PubMed]
70.
Haywood, K.L.; Collin, S.M.; Crawley, E. Assessing severity of illness and outcomes of treatment in children with Chronic Fatigue
Syndrome/Myalgic Encephalomyelitis (CFS/ME): A systematic review of patient-reported outcome measures (PROMs). Child.
Care Health Dev. 2014,40, 806–824. [CrossRef] [PubMed]
71.
Vyas, J.; Muirhead, N.; Singh, R.; Ephgrave, R.; Finlay, A.Y. Impact of myalgic encephalomyelitis/chronic fatigue syndrome
(ME/CFS) on the quality of life of people with ME/CFS and their partners and family members: An online cross-sectional survey.
BMJ Open 2022,12, e058128. [CrossRef] [PubMed]
72.
Bretherick, A.; McGrath, S.; Devereux-Cooke, A.; Leary, S.; Northwood, E.; Redshaw, A.; Stacey, P.; Tripp, C.; Wilson, J.;
Chowdhury, S.; et al. Typing myalgic encephalomyelitis by infection at onset: A DecodeME study [version 4; peer review: 2
approved]. NIHR Open Res. 2023,3, 20. [CrossRef] [PubMed]
73.
Jason, L.A.; Barker, K.; Brown, A. Pediatric Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Rev. Health Care 2012,3,
257–270. [CrossRef] [PubMed]
74.
Rasa, S.; Nora-Krukle, Z.; Henning, N.; Eliassen, E.; Shikova, E.; Harrer, T.; Scheibenbogen, C.; Murovska, M.; Prusty, B.K. Chronic
viral infections in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). J. Transl. Med. 2018,16, 268. [CrossRef]
[PubMed]
75.
Crawley, E.M.; Emond, A.M.; Sterne, J.A.C. Unidentified Chronic Fatigue Syndrome/myalgic encephalomyelitis (CFS/ME) is a
major cause of school absence: Surveillance outcomes from school-based clinics. BMJ Open 2011,1, e000252. [CrossRef] [PubMed]
76.
Núñez, M.; Núñez, E.; del Val, J.L.; Fernández-Huerta, J.M.; Alegre, C.; Bonet, M.; Roig, D.; Gomez, E.; Godás, T.; Fernández-Solà,
J. Health-related quality of life in chronic fatigue syndrome versus rheumatoid arthritis as control group. J. Chronic Fatigue Syndr.
2007,14, 31. [CrossRef]
77.
Nacul, L.C.; Lacerda, E.M.; Campion, P.; Pheby, D.; Drachler, M.d.L.; Leite, J.C.; Poland, F.; Howe, A.; Fayyaz, S.; Molokhia, M.
The functional status and well being of people with myalgic encephalomyelitis/chronic fatigue syndrome and their carers. BMC
Public. Health 2011,11, 402. [CrossRef] [PubMed]
78.
Falk Hvidberg, M.; Brinth, L.S.; Olesen, A.V.; Petersen, K.D.; Ehlers, L. The Health-Related Quality of Life for Patients with
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). PLoS ONE 2015,10, e0132421. [CrossRef] [PubMed]
79.
Kemp, J.; Sunnquist, M.; Jason, L.A.; Newton, J.L. Autonomic dysfunction in myalgic encephalomyelitis and chronic fatigue
syndrome: Comparing self-report and objective measures. Clin. Auton. Res. 2019,29, 475–477. [CrossRef] [PubMed]
80.
Lacerda, E.M.; Bowman, E.W.; Cliff, J.M.; Kingdon, C.C.; King, E.C.; Lee, J.S.; Clark, T.G.; Dockrell, H.M.; Riley, E.M.; Curran, H.;
et al. The UK ME/CFS Biobank for biomedical research on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)
and Multiple Sclerosis. Open J. Bioresour. 2017,4, 4. [CrossRef] [PubMed]
81.
Katz, B.Z.; Collin, S.M.; Murphy, G.; Moss-Morris, R.; Wyller, V.B.; Wensaas, K.A.; Hautvast, J.L.A.; Bleeker-Rovers, C.P.; Vollmer-
Conna, U.; Buchwald, D.; et al. The International Collaborative on Fatigue Following Infection (COFFI). Fatigue 2018,6, 106–121.
[CrossRef] [PubMed]
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