Access to this full-text is provided by Frontiers.
Content available from Frontiers in Pediatrics
This content is subject to copyright.
EDITED BY
Giusto Trevisan,
University of Trieste, Italy
REVIEWED BY
Andrew R. Lloyd,
University of New South Wales, Australia
Gunnar Houen,
University of Copenhagen, Denmark
*CORRESPONDENCE
Lorenz Mihatsch
l.mihatsch@tum.de
†
These authors have contributed equally to
this work and share last authorship
RECEIVED 25 July 2023
ACCEPTED 20 December 2023
PUBLISHED 18 January 2024
CITATION
Pricoco R, Meidel P, Hofberger T,
Zietemann H, Mueller Y, Wiehler K, Michel K,
Paulick J, Leone A, Haegele M, Mayer-Huber S,
Gerrer K, Mittelstrass K, Scheibenbogen C,
Renz-Polster H, Mihatsch L and Behrends U
(2024) One-year follow-up of young people
with ME/CFS following infectious
mononucleosis by Epstein-Barr virus.
Front. Pediatr. 11:1266738.
doi: 10.3389/fped.2023.1266738
COPYRIGHT
© 2024 Pricoco, Meidel, Hofberger,
Zietemann, Mueller, Wiehler, Michel, Paulick,
Leone, Haegele, Mayer-Huber, Gerrer,
Mittelstrass, Scheibenbogen, Renz-Polster,
Mihtasch and Behrends. This is an open-
access article distributed under the terms of
the Creative Commons Attribution License
(CC BY). The use, distribution or reproduction
in other forums is permitted, provided the
original author(s) and the copyright owner(s)
are credited and that the original publication in
this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms.
One-year follow-up of young
people with ME/CFS following
infectious mononucleosis by
Epstein-Barr virus
Rafael Pricoco1, Paulina Meidel1, Tim Hofberger1,
Hannah Zietemann1, Yvonne Mueller1, Katharina Wiehler1,
Kaja Michel1, Johannes Paulick1, Ariane Leone1,
Matthias Haegele1, Sandra Mayer-Huber1, Katrin Gerrer1,
Kirstin Mittelstrass1, Carmen Scheibenbogen2,
Herbert Renz-Polster3, Lorenz Mihatsch1*†and Uta Behrends1,4†
1
MRI Chronic Fatigue Center for Young People (MCFC), Children’s Hospital, TUM School of Medicine,
Technical University of Munich and Munich Municipal Hospital Schwabing, Munich, Germany,
2
Institute
of Medical Immunology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität
Berlin and Humboldt Universität zu Berlin and Berlin Institute of Health (BIH), Berlin, Germany,
3
Mannheim Institute of Public Health, Social and Preventive Medicine, University Medicine Mannheim,
Heidelberg, Germany,
4
German Center for Infection Research (partner site Munich), Munich, Germany
Background: Infectious mononucleosis after primary infection with Epstein-Barr
virus (EBV-IM) has been linked to the development of myalgic
encephalomyelitis/chronic fatigue-syndrome (ME/CFS) in children, adolescents,
and young adults. Here, we present clinical phenotypes and follow-up data from
afirst German cohort of young people with ME/CFS following EBV-IM.
Methods: 12 adolescents and 13 young adults were diagnosed with IM-triggered
ME/CFS at our specialized tertiary outpatient service by clinical criteria requiring
post-exertional malaise (PEM) and a history of confirmed EBV primary infection
as triggering event. Demographic information, laboratory findings, frequency
and severity of symptoms, physical functioning, and health-related quality of
life (HRQoL) were assessed and re-evaluated 6 and 12 months later.
Results: Young adults displayed more severe symptoms as well as worsening of
fatigue, physical and mental functioning, and HRQoL throughout the study,
compared to adolescents. After one year, 6/12 (54%) adolescents no longer
met the diagnostic criteria for ME/CFS while all young adults continued to
fulfill the Canadian consensus criteria. Improvement in adolescents was
evident in physical functioning, symptom frequency and severity, and HRQoL,
while young adults showed little improvement. EBV serology and EBV DNA
load did not correlate with distinct clinical features of ME/CFS, and clinical
chemistry showed no evidence of inflammation. Remarkably, the median time
from symptom onset to ME/CFS diagnosis was 13.8 (IQR: 9.1–34.9) months.
Abbreviations
ANA, antinuclear antibodies; CCC, Canadian consensus criteria; CDW-R, clinical diagnostic worksheet
developed by Rowe and colleagues; CFQ, chalder fatigue scale; CSI, charité symptom inventory; EA, early
antigen; EBV, Epstein-Barr virus; HHV, human herpes virus; HRQoL, health-related quality of life; IM,
infectious mononucleosis; IOM, institute of medicine (IOM); MCFC, MRI chronic fatigue center for
young people; MCS, mental health component summary score; ME/CFS, myalgic encephalomyelitis/
chronic fatigue syndrome; PCD-J, pediatric case definition by Jason and colleagues; PedsQL, pediatric
quality of life inventory; PEM, post-exertional malaise; PCS, physical health component summary score;
PoTS, postural orthostatic tachycardia syndrome; PID, primary immunodeficiency; PROM, patient-
reported outcome measures; SARS-CoV2, severe acute respiratory coronavirus type 2; SF-36, the short
form-36 health survey; VCA, virus capsid antigen.
TYPE Original Research
PUBLISHED 18 January 2024
|
DOI 10.3389/fped.2023.1266738
Frontiers in Pediatrics 01 frontiersin.org
Conclusions: ME/CFS following EBV-IM is a severely debilitating disease often
diagnosed late and with limited responses to conventional medical care,
especially in adults. Although adolescents may have a better prognosis, their
condition can fluctuate and significantly impact their HRQoL. Our data
emphasize that biomarkers and effective therapeutic options are also urgently
needed to improve medical care and pave the way to recovery.
KEYWORDS
myalgic encephalomyelitis, chronic fatigue syndrome, infectious mononucleosis,
Epstein-Barr virus, EBV, adolescents, ME/CFS, follow-up
1 Introduction
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)
is a complex and debilitating multi-system disease characterized by
fatigue, post-exertional malaise (PEM) and additional symptoms,
including unrefreshing sleep, cognitive impairment, orthostatic
intolerance, and/or chronic pain. Up to 25% patients are severely
affected and bound to home or bed (1,2). ME/CFS has been
identified as an important cause for long-lasting school absence
(3–8) and is associated with a significant reduction of health-
related quality of life (HRQoL) (7,9–11).
Pre-pandemic global prevalence estimates for ME/CFS were
0.3%–0.5%, with age peaks at onset of 11–19 and 30–39 years
(12). The prevalence reported for children and adolescents
ranged from 0.1% to 1.9%, depending on case definitions,
geographical region, and screening methods. Up to 95% of
children with ME/CFS may remain undiagnosed (13). Adolescent
girls represent the majority of pediatric ME/CFS patients, with a
post-pubertal female-to-male ratio of 3–4:1 (8,13).
Infectious triggers of ME/CFS account for 23%–90% pediatric
cases (4,14–16). 80% pediatric ME/CFS patients of a large
Australian cohort recalled an initial infection, and 40% an
infectious mononucleosis (IM) by Epstein-Barr virus (EBV) (7).
ME/CFS was reported in 13%, 7%, and 4% adolescents in the US
at 6, 12, and 24 months (17,18), and in 23% college students at
3–6 months after EBV-IM, respectively (19). While EBV was the
most prominent trigger of ME/CFS until 2019 (7,18–30), it
became outranked by severe acute respiratory coronavirus type 2
(SARS-CoV2), which was estimated to cause at least a doubling
of ME/CFS cases worldwide, including Germany (31–33).
The pathomechanisms of ME/CFS remain unclear. Genetic
polymorphisms might contribute to pathogenic immune
dysregulation (34). Emerging evidence suggests vascular changes
causing hypoperfusion of muscles and brain (35). Microbiome
dysbiosis, defects in energy metabolism, dysregulated hormones,
and vagus nerve dysfunction have been discussed (20,36–38). A
causative role of human herpes virus (HHV) reactivation was
evaluated but has not been proven yet (39–44). We recently
reported, that EBV (HHV4) might initiate autoimmunity by
molecular mimicry (45).
Candidate risk factors for EBV-triggered ME/CFS include
disease severity and days-in-bed during the acute phase, initial
pain and autonomic symptoms, lower mental health scores,
higher scores for anxiety, depression, and perceived stress, female
gender, as well as distinct laboratory findings (e.g., elevated
C-reactive protein and cytokine levels). However, different case
definitions have been used and findings were inconsistent (19,
23,27–29). Jason and colleagues found that baseline anxiety,
stress, depression, or coping skills did not predict the
development of ME/CFS after EBV-IM, while preceding
symptoms of the ME/CFS spectrum increased the risk (19).
ME/CFS is diagnosed according to clinical case definitions and
after thorough differential diagnosis (46). In adults the Institute of
Medicine (IOM) criteria (47) are recommended for screening and
the Canadian Consensus Criteria (CCC) (48) for diagnosis and
research. For children and adolescents the CCC were adapted in
a“pediatric case definition”by Jason and colleagues (PCD-J)
(49) and a “clinical diagnostic worksheet”developed by Rowe
and colleagues (CDW-R) (6). All four scores require PEM.
Comorbidities can include autoimmune thyroiditis, hypermobile
Ehlers Danlos syndrome (hEDS), and postural orthostatic
tachycardia syndrome (PoTS) (6,46).
No specific ME/CFS treatment is available yet. Consequent self-
management with pacing was recommended together with non-
pharmaceutical and pharmaceutical approaches to reduce the
severity and frequency of symptoms. Psychosocial support may
help with implementing coping strategies, and occupational
therapy can support daily life and education (6,46,50).
Promising experimental strategies are targeting the immune,
vascular, and nervous system (51).
With adequate treatment, the course of disease seems to be
better in children and adolescents compared to adults, with
pediatric recovery rates of 5%–83% (4,6–8,14–16,26,52–58).
Recovery rates in young people have been operationalized by
measuring school attendance, symptom frequency and severity,
as well as fulfillment of diagnostic criteria (53,59). In an
Australian pediatric cohort, one and two thirds of the patients
recovered after 5 and 10 years, respectively, with a median
disease duration of 5 (1–14) years in those who recovered (7).
However, in many cases the course of ME/CFS is fluctuating,
with periods of deterioration (“crashes”), stabilization,
improvement, or relapse-remitting cycles (6,7,22). About 40%
of adult patients are estimated to improve over time, but only 5%
fully recover (60,61). Inferior outcomes might in part be due to
inappropriate management resulting from inadequate disease-
specific knowledge of medical staff (3,52,62,63), to a lack of
medical services and barriers to the health care system for
patients with ME/CFS (64–66), and to stigmatization.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 02 frontiersin.org
Here, we present a first German cohort of young ME/CFS
patients diagnosed after confirmed EBV-IM at our MRI Chronic
Fatigue Center for Young People (MCFC) and participating in
our prospective MUC-CFS studies. The MCFC, so far, is
Germany’s sole pediatric university center specialized on ME/
CFS research and care. The MUC-CFS studies offer
comprehensive insights into patient demographics, clinical
phenotypes, and health-related quality of life (HRQoL) at
diagnosis and during follow-up. Our primary objective was to
assess disease trajectories at 6 and 12 months after ME/CFS
diagnosis to explore potential age-sepcific differences.
2 Methods
2.1 Study population, diagnostic work-up,
and standard treatment
A cohort of 12 adolescents and 13 adults was diagnosed with
ME/CFS after confirmed EBV-IM from March 2019 to
November 2022 at our tertiary pediatric university hospital,
enrolled in our single-center prospective MUC-CFS cohort
studies, and reassessed at 6 and 12 months. Confirmed EBV-IM
was defined as a combination of typical symptoms (e.g., fever,
fatigue, sore throat, lymphadenopathy, and/or splenomegaly) and
typical serology (positive IgM and/or IgG antibodies against EBV
viral capsid antigen (VCA) without IgG antibodies against EBV
nuclear antigen 1 (EBNA-1), in some cases with documented
subsequent EBNA-1-IgG seroconversion). Diagnostic ME/CFS
criteria were applied depending on age: For adults (≥18 years)
the CCC were used. Adolescents needed to meet either the CCC
or the less strict CDW-R criteria, with a disease duration of at
least 3 or 6 months, respectively. PEM had to last for more than
14 h after mild exertion. All patients underwent a thorough
differential diagnostic work-up (laboratory analyses, ECG, UCG,
EEG, cMRI, pulmonary function analyses, psychological
evaluation, additional investigations depending on symptoms) as
recommended (6). A 10-minute passive standing test screened
for orthostatic intolerance (OI), PoTS, or orthostatic hypotonia
(OH). All patients received a symptom-oriented, non-
pharmaceutical and/or pharmaceutical treatment, were guided on
self-management, and were provided with psychosocial support,
including adapted school education and home care if needed.
2.2 Data collection
Clinical data were collected from clinical records and
questionnaires. For personal or telephone follow-up visits,
questionnaires were mailed to the families one month in
advance. Five well-established patient-reported outcome measures
(PROM) were used: (i) The Pediatric Quality of Life Inventory
(PedsQL) was used to assess HRQoL in pediatric patients. It
comprises 20 items and four subscales, namely physical,
emotional, social, and school functioning, with good internal
consistency and reliability (67). (ii) The Short Form-36 Health
Survey (SF-36) is a well-validated 36-item questionnaire for
measuring HRQoL in people older than 13 years, with eight
subscales (physical functioning, role physical, general health,
bodily pain, social functioning, vitality, role emotional, and
mental health) ranging from 0 to 100. Lower scores indicate
more impairment (68). (iii) The Chalder Fatigue Scale (CFQ)
measures physical and mental fatigue and consists of eleven
items on a Likert scale from 0 to 3. The total score ranges from
0 to 33, with 33 indicating most severe fatigue (69). (iv) The
Charité Symptom Inventory (CSI), adapted from the CDC
Symptom Inventory, rates frequency and severity of typical
symptoms of ME/CFS within the month prior to the visit. Scales
rate from 0 (not present) to 3 (severe) for severity and from 0
(not present) to 4 (always) for frequency of symptoms (70). (v)
The Bell Score assesses the severity of ME/CFS by evaluating the
impairment of daily activities (71); for adolescents the wording
was adapted (e.g., “school”instead of “work”).
2.3 Statistical analyses
Statistical analyses utilized R version 4.2.1 (“Funny-Looking
Kid”)(72). Categorial variables were compared using Fisher’s
exact test or Pearson’sχ
2
test. Numeric variables were compared
between groups using the Wilcoxon rank-sum or Kruskal–Wallis
test, as appropriate. Spearman’s rank coefficient assessed
correlations. Cox regression analysed association between
independent variables and the time-to first presentation in the
MCFC. Repeated measures correlation gauged within-subject
PROMs’correlation (73). Due to small sample size and no
adjustment for multiple testing, all P-values were considered
exploratory. Significance level was set to α= 0.05.
3 Results
3.1 Baseline demographics and clinical
characteristics
Baseline characteristics are shown in Table 1. All 25 patients
(80% female) had a history of EBV-IM with typival symptoms and
documented serological findings indicating EBV primary infection
at the time of disease onset. Adolescents (48%, median age at
onset 15, IQR 13–15) did not differ from young adults (≥18 years)
(52%, median age at onset 10, IQR: 18–21) with regard to
demographics, medical and family history, and current medical
care. The median time between EBV-IM and ME/CFS diagnosis at
the first visit was 13.8 months (range 4–84), with no significant
difference between males and females (P= 0.272), and/or adults
and adolescents (P= 0.596). The time delay from symptom onset
to diagnosis was less than 6, 12, and 24 months in 1/13 (8%), 5/13
(38%), and 7/13 (54%) adults as well as in 1/12 (8%), 5/12 (42%),
and 10/12 (83%) adolescents (Supplementary Figure S1).
All adults met the CCC and all adolescents the CDW-R criteria
and/or CCC, as required. Adults did not significantly differ from
adolescents with regard to the baseline Bell Score or the SF-36
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 03 frontiersin.org
physical (PCS) and mental health component summary score
(MCS). However, adults showed significantly higher CFQ scores
(adults: 28 ± 4; adolescents: 22 ± 5; P= 0.006), and significantly
lower PedsQL values (adults: 35 ± 11; adolescents: 54 ± 9; P=
0.002) compared to adolescents. At the time of diagnosis, all
adolescents reported school absences, 2/11 (18%) received
complementary home schooling and none had distance
schooling. One patient reported a documented degree of
disability, and none had received medical care at home.
24/25 (96%) patients showed comorbidities, with PoTS in 21/
23 (83%) and allergies in 12/23 (48%) patients. Two patients
droped out of the 10-min passive standing test due to severe OI
symptoms. One patient presented with a diagnosis of anxiety
disorder, and two with a mixed anxiety and depressive disorder.
17/24 (71%) patients took various nutritional supplements, and
11/24 (46%) prescription-only medications, including three
patients on antidepressants. With regard to the family’s medical
history, in 2/25 (8%) cases ME/CFS was reported. 16/25 (64%),
TABLE 1 Baseline demographics and clinical characteristics of the cohort.
Characteristics All Adults Adolescents P-value
a
Number of patients n=25 n=13 n=12
Age and illness duration
b
Age at first visit 18 (16–21) 21 (19–22) 16 (14–16) <0.001
Age at onset 16 (14–19) 19 (18–21) 15 (13–15) <0.001
Illness duration in months from onset to first visit 13.8 (9.1–34.9) 16.9 (9.4–44.1) 13.2 (8.8–22.0) 0.503
Baseline questionnaire results
Chalder fatigue scale
c
25 (5) 28 (4) 22 (5) 0.006
Bell Score
b
40 (30–50) 30 (30–40) 50 (40 –50) 0.056
SF-36 PCS
c
29 (9) 26 (8) 32 (9) 0.151
SF-36 MCS
c
42 (11) 39 (12) 45 (9) 0.211
PedsQL
c
46 (14) 35 (11) 54 (9) 0.002
Gender
d
Female 20/25 (80) 11/13 (85) 9/12 (75) 0.645
ME/CFS criteria
d
CCC 21/25 (84) 13/13 (100) 8/12 (67) 0.039
CDW-R 12/12 (100) N/A 12/12 (100) 0.077
Comorbidity
d
PoTS 19/23 (83) 11/11 (100) 8/10 (80) >0.999
Allergies 12/25 (48) 7/13 (54) 5/12 (42) 0.543
Asthma 1/25 (4) 0/13 (0) 1/12 (8) >0.999
Neurodermatitis 1/25 (4) 1/13 (8) 0/12 (0) >0.999
Psychiatric disorder 3/25 (12) 2/13 (15) 1/12 (8) >0.999
Medical history
d
Trauma/surgery 1/25 (4) 0/13 (0) 1/12 (8) 0.480
Asthma 2/25 (8) 1/13 (8) 1/12 (8) >0.999
Psychiatric disorder 1/25 (4) 0/13 (0) 1/12 (8) 0.480
Current medical care
d
Complete vaccinations 22/22 (100) 11/11 (100) 11/11 (100)
Nutrition supplements 17/24 (71) 10/12 (83) 7/12 (58) 0.319
Prescription medication 11/24 (46) 5/12 (42) 6/12 (50) >0.999
Degree of disability 1/25 (4) 0/13 (0) 1/12 (8) >0.999
Medical aid 0/25 (0) 0/13 (0) 0/12 (0)
Long-term care level 0/25 (0) 0/13 (0) 0/12 (0)
Family history
d
ME/CFS in family 2/25 (8) 1/13 (8) 1/12 (8) >0.999
AID in family 10/25 (40) 6/13 (46) 4/12 (33) 0.688
PID in family 0/25 (0) 0/13 (0) 0/12 (0)
IM in family 16/25 (64) 9/13 (69) 7/12 (58) 0.688
CCC, Canadian consensus criteria (47); CDW-R, clinical diagnostic worksheet (6); PoTS, postural orthostatic tachycardia syndrome; AID, autoimmune disease; PID, primary
immune deficiency; IM, infectious mononucleosis; PedsQL, pediatric quality of life inventory; SF-36 PCS, short form 36 health survey physical component summary score;
SF-36 MCS, short form 36 health survey mental health component summary score; N/A, not applicable.
Bold values denote statistical significance at the P< 0.05 level.
a
Fisher’s exact test; Wilcoxon rank sum test; Pearson’sχ
2
test.
b
Median (IQR).
c
Mean (SD).
d
Number of patients with indicated characteristic/number of patients investigated (%).
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 04 frontiersin.org
10/25 (40%), and 18/25 (72%) patients remembered a family
member with EBV-IM, autoimmune diseases, or either one.
The cohort had consulted several (median 6, range 1–11) private
practice doctors across five different specialties (range 1–11) for ME/
CFS symptoms. 11/20 (55%) patients had visited at least one
hospital. 7/20 (35%) had consulted a psychotherapist/psychologist,
9/20 (45%) a naturopath, 6/20 (30%) traditional Chinese
medicine, 4/20 (20%) homeopathy, and 5/20 (25%) osteopathy.
3.2 Baseline laboratory findings
Laboratory findings at the time of diagnosis were primarily
unremarkable, without significant differences between adolescents
and adults (Table 2). Besides low vitamin D levels in 14/24
(58%) patients (range 7–29 ng/ml), the most frequent laboratory
findings were elevated antinuclear antibodies (ANA) present in
14/25 (56%) (range 1:100–1:800), elevated IgE in 7/25 (28%) and
mild anemia in 4/25 (16%) cases. ANA titers were in the range
of <1:160 in 2/6 (33%) adolescents, of 1:160–1:640 in 2/6 (33%)
adolescents and 8/8 (100%) adults, and of ≥1:640 in 2/6 (33%)
adolescents, with higher ANA titers compared to adults
(P= 0.015). ANA titers did not significantly correlate with
disease severity (Bell Score: P= 0.452; SF-36 PF: P= 0.858), were
not significantly different between males and females (P= 0.521),
and not associated with any sign of connective tissue disorders.
Herpes simplex virus coinfection was not more frequent in adults
compared to adolescents (P> 0.999). Neither total
immunoglobulin serum levels nor phenotypes of peripheral
blood lymphocytes revealed any evidence of primary
immunodeficiency (PID) (Supplementary Table S1).
Results from EBV serology and real-time PCR at the first visit
are displayed in Table 3 and did not differ significantly between
adolescents. No EBV DNA was detected in plasma. 8/20 (40%)
patients showed EBV DNA in peripheral blood cells (5/8 very
low titers, 1/8 17.7 Geq/10
5
, 1/8 70.1 Geq/10
5
, and 1/8 121.8
Geq/10
5
), and 14/25 (66%) in throat washes. EBV DNA load in
throat washes did not significantly correlate with disease severity
TABLE 2 Selected laboratory results at baseline visit.
Laboratory parameter All n/n(%)
a
Adults n/n(%)
a
Adolescents n/n(%)
a
P-value
b
Blood count
Neutropenia (<1,500/ul) 2/25 (8) 1/13 (8) 1/12 (8) >0.999
Lymphocytes ↑5/25 (20) 2/13 (15) 3/12 (25) 0.645
Thrombocytes ↓0/25 (0) 0/13 (0) 0/12 (0)
Hemoglobin ↓4/25 (16) 1/13 (8) 3/12 (25) 0.322
Inflammation
Sedimentation rate ↑1/21 (5) 0/13 (0) 1/8 (12.5) 0.350
C-reactive protein ↑0/25 (0) 0/13 (0) 0/12 (0)
Ferritin ↑2/23 (9) 0/13 (0) 2/10 (20) 0.178
Liver function
GOT ↑1/25 (4) 0/13 (0) 1/12 (8) 0.480
GPT ↑2/25 (8) 0/13 (0) 2/12 (17) 0.220
Bilirubin ↑1/24 (4) 1/13 (8) 0/11 (0) >0.999
Immunoglobulins (Ig)
IgA ↓↑ 0/25 (0) 0/13 (0) 0/12 (0)
IgM ↓↑ 0/25 (0) 0/13 (0) 0/12 (0)
IgG ↓↑ 0/25 (0) 0/13 (0) 0/12 (0)
IgE ↑7/25 (28) 3/13 (23) 4/12 (33) 0.673
Infection Serology
Cytomegalovirus IgG 3/25 (12) 2/13 (15) 1/12 (8) >0.999
Herpes simplex virus IgG 3/25 (12) 2/13 (15) 1/12 (8) >0.999
Toxoplasma IgG 1/25 (4) 1/13 (78) 0/12 (0) >0.999
Borrelia IgG 1/25 (4) 0/13 (0) 1/12 (8) 0.480
Autoantibodies
ANA ↑14/25 (56) 8/13 (62) 6/12 (50) 0.561
ANCA ↑1/25 (4) 1/13 (8) 0/12 (0) >0.999
Anti-dsDNA ↑0/25 (0) 0/13 (0) 0/12 (0)
Endocrinology
Cortisol ↓1/25 (4) 1/13 (18) 0/12 (0) 0.480
ACTH ↑1/23 (4) 0/12 (0) 1/11 (9) 0.478
25-OH-Vitamin-D ↓14/24 (58) 6/12 (50) 8/12 (67) 0.680
↑above normal range; ↓below normal range; ANA, antinuclear antibodies; ANCA, anti-cytoplasmatic antibodies; anti-dsDNA, anti-double strand DNA.
a
Number of patients with indicated laboratory parameter/number of patients investigated (%).
b
Fisher’s exact test; Pearson’sχ
2
test.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 05 frontiersin.org
(Bell Score: P= 0.686; SF-36 PCS: P= 0.871). All patients showed
anti-EBV-VCA IgG as expected, 23/25 (92%) had detectable anti-
EBNA-1 IgG and 6/25 (24%) anti-EBV-VCA IgM. The detection
of anti-EBV-VCA IgM did not significantly correlate with disease
severity (Bell Score: P= 0.877; SF-36 PCS: P= 0.788). Results of
EBV immunoblots revealed IgG antibodies against early antigens
(EA) p54 and p138, the immediate early antigen BZLF1, virus
capsid antigens (VCA) p23 and p18, and EBNA-1 in 8/25 (32%),
5/25 (20%), 18/25 (72%), 23/25 (92%), 24/25 (96%), and 22/25
(88%) patients, respectively.
3.3 ME/CFS criteria
Follow-up data were available at 6 months after ME/CFS
diagnosis from 22/25 (88%) patients, including 10/13 (77%)
adults and 12/12 (100%) adolescents, and at 12 months from 20/
25 (80%) patients, including 9/13 (69%) adults and 11/12 (92%)
adolescents. Reasons for drop out were recovery (one adolescent),
worsening of symptoms (one adult), or unknown (two patients).
Changes in CCC and CDW-R criteria fulfilment are shown in
Figure 1. Seven adults fulfilled the CCC at all three visits. One
became CCC negative at 6 months but met the CCC criteria
again at 12 months (Figure 1A). Six adolescents were still
positive for the CDW-R criteria at 6 months and only four at 12
months follow-up. One patient became CDW-R negative at 6
months but met the CDW-R criteria again at 12 months
(Figure 1B). By 6 months one and by 12 months three additional
pediatric patients had turned 18 years old, and therefore the
CDW-R criteria were not applicable anymore (indicated by N/A
in Figure 1C). The CCC criteria were fulfilled by 8/12 (67%), 4/
12 (33%), and 4/11 (36%) adolescents at the first visit, 6 months
and 12 months. Two adolescents who were CCC positive at 12
months had been negative at the previous visits (Figure 1C). 7/12
(58%) adolescents met either the CCC or the CDW-R criteria at
6 months, and 5/11 (45%) either of both at 12 months
(Figure 1D). Patients with partial recovery still presented with
some of the symptoms. Two patients reported on OI only, one
on fatigue with limitations in daily life and headaches, and three
on several symptoms without fatigue. All patients in partial
remission were adolescents (P= 0.005) and had a relatively short
illness duration of less than three years (mean 24 months, range
15–34 months). They had significantly less fatigue (CFQ Likert
score: P= 0.001) and higher HRQoL (PedsQL: P= 0.026) at
diagnosis compared to patients without partial remission
(Supplementary Table S2). Patients in partial remission did not
significantly differ in any of the other baseline characteristics and
laboratory parameters tested, including EBV antibodies and DNA
(Supplementary Tables S2,S3).
3.4 Number, frequency, and severity of
symptoms
At the baseline visit, patients presented with 27 ± 5 symptoms
(mean ± SD), with 15 ± 5 occurring at least frequently (Figure 2).
The symptoms reported at least frequently (3 or 4 on Likert
scale) included fatigue (96%), limitations in daily life (96%), need
for rest (92%) and PEM (83%). The most common severe (3 on
TABLE 3 EBV serology, PCR and IgG immunoblot at baseline visit.
EBV
diagnostics
All n/n
(%)
a
Adults
n/n(%)
a
Adolescents
n/n(%)
a
P-value
b
EBV PCR
DNA in cell fraction 0.927
–12/20 (60) 7/12 (58) 5/8 (62)
(+) 5/20 (25) 3/12 (25) 2/8 (25)
+ 3/20 (15) 2/12 (17) 1/8 (12)
DNA in plasma
–25/25
(100)
13/13 (100) 12/12 (100)
+ 0/25 (0) 0/12 (0) 0/12 (0)
DNA in throat wash >0.999
–11/25 (44) 6/13 (46) 5/12 (42)
+ 14/25 (66) 7/13 (54) 7/12 (54)
EBV ELISA
VCA IgM 0.110
–18/25 (72) 7/13 (54) 11/12 (92)
(+) 1/25 (4) 1/13 (8) 0/12 (0)
+ 6/25 (24) 5/13 (38) 1/12 (8)
VCA IgG
–0/25 (0) 0/13 (0) 0/12 (0)
+ 25/25
(100)
13/13 (100) 12/12 (100)
EBNA1 IgG 0.220
–2/25 (8) 0/13 (0) 2/12 (17)
+ 23/25 (92) 13/13 (100) 10/12 (83)
EBV IgG Immunoblot
EAp54 0.282
–14/25 (56) 7/13 (54) 7/12 (58)
(+) 3/25 (12) 3/13 (23) 0/12 (0)
+ 8/25 (32) 3/13 (23) 5/12 (42)
EAp138 0.233
–14/25 (56) 6/13 (46) 8/12 (67)
(+) 6/25 (24) 5/13 (38) 1/12 (8)
+ 5/25 (20) 2/13 (15) 3/12 (25)
BZLF1 0.293
–3/25 (12) 3/13 (23) 0/12 (0)
(+) 4/25 (16) 2/13 (15) 2/12 (17)
+ 18/25 (72) 8/13 (62) 10/12 (83)
VCAp23 >0.999
–2/25 (8) 1/13 (8) 1/12 (8)
(+) 0/25 (0) 0/13 (0) 0/12 (0)
+ 23/25 (92) 12/13 (92) 11/12 (92)
VCAp18 0.480
–1/25 (4) 0/13 (0) 1/12 (8)
(+) 0/25 (0) 0/13 (0) 0/12 (0)
+ 24/25 (96) 13/13 (100) 11/12 (92)
EBNA-1 0.344
–2/25 (8) 0/13 (0) 2/12 (17)
(+) 1/25 (4) 1/13 (8) 0/12 (0)
+ 22/25 (88) 12/13 (92) 10/12 (83)
EBV, Epstein-Barr virus; VCA, virus capsid antigen; EBNA, EBV nuclear antigen; EA,
early antigen.
a
Number of patients with indicated laboratory parameter/number of patients
investigated (%).
b
Fisher’s exact test.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 06 frontiersin.org
Likert scale) symptoms were PEM (46%), stress intolerance (38%),
fatigue (33%), limitations in daily life (33%), and unrefreshing sleep
(33%). The number, severity, and frequency of individual
symptoms did not significantly change between the first and
follow-up visits (Supplementary Table S4). Adults reported
slightly more symptoms (29 ± 3) than adolescents (25 ± 7, P=
0.084). Symptoms occurring at least frequently were more
common in adults than adolescents (19 ± 6 vs. 12 ± 3, P= 0.006).
This difference was also evident at the follow-up visits
(Supplementary Table S5).
3.5 Patient-reported outcome measures
At the first visit, the CFQ Likert score of the cohort was 25 ± 5 and
did not significantly change over time. While adults showed a moderate
worsening from the first (28 ± 4) to follow-up visits (28 ± 4 at 6months,
29 ± 4 at 12-months), adolescents demonstrated a moderate
improvement (22 ± 5 at firstvisit,19±9at6months,18±9at12-
months) (Table 4 and Figure 3A). At all visits, adolescents had
significantly less fatigue than adults (first visit: P= 0.006; 6-months:
P= 0.016; 12 months: P= 0.003) (Supplementary Table S6).
The median Bell Score was 40 (IQR: 30–50) and did not
significantly change over time (P= 0.384), with a median adults’
Bell Score of 30 at all visits. The adolescents’Bell Score moderately
but not significantly improved from the first (median: 50, IQR:
40–50) to follow-up visits (both median: 60, IQR: 40–80) (P=
0.232) (Table 4 and Figure 3B). It was significantly better than
adults’Bell Score at all visits (first visit: P= 0.019; 6 months: P=
0.019; 12 months: P= 0.007) (Supplementary Table S6).
The SF-36 summary and subscales did not significantly change
between visits. However, adolescents had a significantly better PCS
at the 12 months than adults (P=0.013) (Table 4 and Figures 3C,
D). Compared to adults, adolescents were significantly better at
the first visit with regard to physical functioning (P= 0.039)
and vitality (P= 0.012), at 6 months to physical functioning
(P= 0.039), pain (P= 0.039), general health (P= 0.032), social
(P= 0.025), and mental health (P= 0.025), and at 12 months to
physical functioning (P= 0.019) and vitality (P= 0.010). There was
no significant difference between adults and adolescents with
regard to the MCS at any visit (Supplementary Table S6). At 12
monthst, 6/10 (60%) adolescents and none of the adults rated
their general health at least somewhat better than in the previous
year (Supplementary Table S7).
FIGURE 1
Alluvial chart illustrating ME/CFS diagnostic criteria fulfillment over time. The chart depicts diagnostic criteria fulfillment (red) or non-fullfillment
(green) at the first visit and at 6 and 12 months. (Non-)fullfillment of the Canadian Consensus Criteria (CCC) is shown for adults (A). (Non)-
fullfillment of CCC only (B), Rowe’s diagnostic worksheet (CDW-R) criteria only, (C) or either of both (CCC or CDW-R) (D) is shown for
adolescents. CDW-R criteria were not applicable anymore (N/A) when adolescents had turned 18 years.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 07 frontiersin.org
The PedsQLtotal score did not significantly change over time. The
subscale scores were lowest for school and physical functioning, and
highest for social functioning. Significant improvements over time
were seen for adolescents’school functioning only (P=0.03)
(Table 4 and Figure 3E). Except for the school and emotional
subscale, all subscales showed significant differences between adults
and adolescents at all visits (Supplementary Table S6).
For all patients best correlations among PROMs were found
for CFQ and PedsQL (r=−0.76, P<0.001), indicating that
more severe fatigue was associated with lower HRQoL
(Figure 4). The most prominent difference between adults and
adolescents was that adolescents’but not adults’CFQ and Bell
Score correlated significantly (adults: r=−0.29, P= 0.209;
adolescents: r=−0.77, P< 0.001).
At 12 months, results from PROMs for patients in partial
remission vs. no remission were median Bell Score 80 (range 40–
100) vs. 40 (range 20–80), mean CFQ Score 12.4 (SD 6.7) vs.
24.4 (SD 6.2), PedsQL total score 76.1 (SD 16.8) vs. 46.6 (SD
15.8), SF-36 PCS 44.7 (SD 7.7) vs. 28.9 (SD 11.5), and SF-36
MCS 50.9 (SD 7.1) vs. 42.9 (SD 10.4). These results again
indicate that patients with partial recovery might still suffer from
impairment of daily life.
4 Discussion
This report contributes to rare follow-up data on young people
with ME/CFS after EBV-IM. We present data on clinical
phenotypes and HRQoL from a first German cohort of
adolescents and young adults over time up to 12 months post
ME/CFS diagnosis at our specialized tertiary pediatric center. So
far, most data on pediatric and/or EBV-triggered ME/CFS
originate from the US, the UK, and Australia, with no pediatric
study from Germany (4,6–8,14–16,26,52–58). While some
prospective pediatric studies examined ME/CFS with PEM after
confirmed EBV-IM (17–19), to our knowledge, none compared
adolescents and young adults with regard to symptom load and
HRQoL over time.
4.1 Baseline demographics and ME/CFS
diagnosis
Our youngest patient was 14 years-old, which was in line with
the published ME/CFS age peak at 15–40 years (12,46,47). The
FIGURE 2
Frequency and severity of symptoms over time. The bar-chart displays individual symptoms on the x-axis. The y-axis shows the frequency (A) and
severity (B) of symptoms on the left and right, respectively. The severity scale for each symptom ranged from 0 (not present) to 4 (severe), and
the frequency scale from 0 (not present) to 5 (always present). At each time point, the chart shows the proportion of patients reporting the
relevant symptom, with rating of severity and frequency rating, indicated by color-code.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 08 frontiersin.org
TABLE 4 Patient-reported outcome measures of the cohort.
All (n= 25) Adults (n= 13) Adolescents (n= 12)
First Visit 6 Months 12 Months P-value
a
First Visit 6 Months 12 Months P-value
a
First Visit 6 Months 12 Months P-value
a
Bell score
b
40 (30, 50) 40 (30, 63) 40 (30, 60) 0.384 30 (30, 40) 30 (30, 40) 30 (25, 35) 0.368 50 (40, 50) 60 (40, 80) 60 (40, 80) 0.232
PedsQL
c
Total score 46 (14) 50 (19) 50 (21) 0.718 35 (11) 37 (15) 37 (15) 0.968 54 (9) 62 (14) 61 (20) 0.368
Physical 40 (18) 46 (24) 40 (26) 0.748 30 (12) 29 (13) 25 (15) 0.842 48 (18) 60 (22) 53 (27) 0.531
Psychosocial 49 (14) 53 (18) 56 (20) 0.698 38 (13) 41 (17) 45 (19) 0.695 58 (6) 63 (14) 64 (18) 0.719
School 33 (14) 43 (22) 47 (28) 0.115 29 (18) 37 (22) 33 (26) 0.871 35 (11) 48 (23) 58 (25) 0.030
Social 66 (21) 64 (20) 64 (20) 0.919 50 (18) 49 (15) 51 (15) 0.916 77 (16) 76 (16) 76 (16) 0.944
Emotional 50 (21) 49 (24) 53 (25) 0.843 34 (15) 36 (23) 44 (21) 0.357 61 (17) 60 (19) 60 (27) 0.921
SF-36
c
Physical functioning 54 (25) 60 (26) 55 (34) 0.792 42 (21) 46 (20) 35 (27) 0.806 65 (25) 71 (25) 73 (31) 0.581
Role physical 12 (15) 18 (33) 22 (37) 0.897 7 (12) 3 (8) 6 (11) 0.677 17 (16) 30 (40) 38 (46) 0.843
Bodily pain 41 (26) 49 (27) 49 (29) 0.433 34 (21) 34 (15) 37 (23) 0.929 47 (29) 62 (29) 60 (31) 0.335
General health 26 (12) 28 (15) 29 (17) 0.865 22 (11) 21 (9) 20 (7) 0.969 30 (12) 35 (15) 37 (20) 0.685
Vitality 22 (14) 29 (22) 27 (26) 0.737 15 (13) 18 (11) 11 (8) 0.481 29 (12) 38 (24) 42 (28) 0.447
Social functioning 41 (27) 43 (33) 41 (35) 0.980 31 (23) 24 (22) 24 (25) 0.520 51 (27) 59 (32) 58 (36) 0.636
Role emotional 71 (39) 55 (41) 65 (44) 0.444 64 (46) 52 (44) 56 (47) 0.824 78 (33) 58 (40) 73 (41) 0.383
Mental health 59 (19) 54 (22) 59 (21) 0.756 52 (20) 43 (20) 51 (18) 0.471 65 (17) 63 (19) 66 (21) 0.923
Physical component summary score 29 (9) 34 (12) 32 (13) 0.434 26 (8) 28 (8) 25 (9) 0.839 32 (9) 38 (13) 38 (13) 0.302
Mental health component summary score 42 (11) 39 (13) 41 (12) 0.589 39 (12) 34 (11) 37 (11) 0.631 45 (9) 42 (14) 45 (12) 0.817
PedsQL, pediatric quality of life inventory; SF-36, short form 36 health survey.
Bold values denote statistical significance at the P< 0.05 level.
a
Kruskal–Wallis rank sum test.
b
Median (IQR).
c
Mean (SD).
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 09 frontiersin.org
FIGURE 3
Results of patient-reported outcome measures over time. Boxplots displaying the dynamics of results from the chalder fatigue scale (CFQ) (A), the bell
score (B), the SF-36 physical (C) (PCS) and mental health component summary score (D) (MCS), and the pediatric quality of life inventory (E) (PedsQL)
for the entire cohort as well as for adolescents and adults only, respectively.
FIGURE 4
Correlation of patient-reported outcomes. Heatmap of repeated measures correlations between patient-reported outcomes (PROMs) for all patients
(A), adults only (B), and adolescents only (C). Repeated measures correlations are a statistical tool to determine the overall within-patient correlation
between a pair of variables.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 10 frontiersin.org
observed female predominance (80%) is a widely recognized in
post-pubertal ME/CFS patients (6,20,47). At the initial visit, all
adults but only 8/12 (66%) met the CCC, supporting the use of
more sensitive criteria for pediatric patients (52,74,75). Some
pediatric follow-up studies employed the polythetic Fukuda
criteria with the addition of mandatory PEM, while others used
the broader Oxford criteria, potentially including individuals
without ME/CFS (4,7,8,14–16,26,53–58). To evaluate the
CCC together with the CDW-R, the PCD-J, and the IOM criteria
(47), we recently developed the Munich Berlin symptom
questionnaire (MBSQ) (76).
The median diagnostic delay of more than one year was in line
with most reports from other countries, indicating long and
difficult patient journeys at any age (3,52,62,63). We did not
find any association of gender, age, or disease severity with time
to diagnosis according to previous studies (62,77). Published
reasons for the diagnostic delay include insufficient knowledge by
families and primary care providers, the requirement for
comprehensive differential diagnosis, as well as negative attitudes
and beliefs by primary care physicians and psychologists (52,77,
78). A lack of ME/CFS specialists most likely exacerbates this
issue. The young adults’longer disease duration prior to
diagnosis possibly reflects challenges during transition from
pediatric to adult health care services (79).
4.2 Postural tachycardia syndrome and
other comorbidities
Comorbidities included PoTS (83%), allergies (48%), and
psychiatric diagnoses (12%). The low prevalence of the latter
alines with other reports on pediatric ME/CFS (6,80,81). PoTS
has been reported in pediatric and adult ME/CFS cohorts with
varying prevalence (6,52). The large span of 5.7%–70% PoTS
cases among adult ME/CFS patients (47) might in part be due to
different PoTS tests and case definitions (82). Since PoTS is a
frequent post-infectious phenomenon in adolescents (83) the
high prevalence in our cohort was not unexpected. Since PoTS
can significantly impair daily activities timely non-
pharmaceutical and, if needed, pharmaceutical treatment is
mandatory. In general, comorbidities are more prevalent in adult
ME/CFS patients (79%–80%) (22,81).
4.3 Lack of medical care
Only one of our patients had previously received a certificate of
disability and none was supported by adequate medical devices or
home care, reflecting poor medical care and barriers to specialized
support (64–66). The large number of medical consultations prior
to diagnosis, large proportion of our patients taking various dietary
supplements and/or receiving complementary medical treatment,
reflects the known lack of adequate, standard medical care and
sets families at risk of financial challenges (7,84).
All pupils in our study reported frequent school absences, and,
remarkably, only a minority had received any educational
assistance such as home or digital schooling. These findings align
with earlier studies showing prolonged school absences and
severely reduced social participation and education of young ME/
CFS patients (3–8). This is particularly concerning, since pediatric
patients with ME/CFS reported that remaining engaged in an
education system that flexibly accommodated their illness and
aspirations was crucial for their long-term functioning (7,85,86).
4.4 Laboratory findings
No established biomarker exist for ME/CFS, and standard
laboratory tests typically yield unremarkable results (6,52). Our
patients mostly exhibited minor deviations, such as elevated
ANA titers (56%), surpassing expectations for this age group (7).
Elevated IgE levels were present in about a third, though
previous studies found no clear associations with ME/CFS (87).
Vitamin D deficiency was prevalent, yet it didn’t seem directly
linked to fatigue levels in another ME/CFS cohorts (88).
As expected, all patients showed anti-EBV VCA IgG as an indicator
of previous EBV infection. Notably, undetectable EBNA-1 IgG and
detection of anti-EBV VCA IgM, anti-EBV EA IgG, EBV DNA in
throat washes weren’tmorecommoninourcohortthaninthe
general population (89–92). Detectable EBV DNA in blood cells was
more frequent than in a U.S. cohort without EBV-associated disorder
(93). We found no significant correlation between EBV-specific
results and disease severity or physical functioning, corresponding
with earlier research that didn’t establish a distinct pattern of EBV-
specific virological results in ME/CFS patients (39,41). However, our
comprehensive EBV-specific immunological analyses suggest that
EBV antigen mimicry might contribute to pathogenic autoimmunity
(34,43,45,94–98). While HHV, including EBV, are being discussed
as potential causes or perpetuating factors of ME/CFS, no definite
causal link has been established (39,40,41).
4.5 Partial recovery
The majority of our adolescent patients partially recovered after
12 months, while all adults still met the CCC. The different health
trajectories were also evident in the self-perceived health transition
item of the SF-36 at 12 months, with 40% and 20% of adolescents
rating their general health as much better or somewhat better, and
45% and 22% of adults much worse or somewhat worse than in the
previous year, respectively. Over the whole study period symptom
load (see below) and school functioning (PedsQL) significantly
improved in adolescents but remained stable or worsened in adults.
These findings are in line with compelling evidence indicating a
better ME/CFS prognosis of children and adolescence compared to
adults, with pediatric studies reporting recovery of up to 83% (4,6–
8,14–16,26,49–58). Dramatic improvement was reported to be
more likely within the first four years (6). Accordingly, partial
remission in our cohort was associated with illness duration of less
than 3 years. A systematic review indicated that prognosis in adults
is fairly poor, with only a minority of adult patients experiencing
full recovery (60).
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 11 frontiersin.org
Only two pediatric patients were largely symptom-free (except
OI) at their last visit. Additionally, we noticed fluctuations of
disease load over time, with some patients not meeting the
diagnostic criteria at 6 but again at 12 months. Remissions and
relapses are frequent in pediatric ME/CFS and can follow
overexertion or additional infectious illnesses (6). Our findings
support the recommendation that patients should be monitored
closely and adviced even after partial recovery. However, it
remains challenging to measure recovery from ME/CFS,
especially in young people, since what they consider as
“recovery”can largely differ (7) and effective pacing might mask
ongoing disease (61).
4.6 Risk factors
Candidate risk factors affecting the prognosis of ME/CFS include
age, female gender, fatigue severity at disease onset, PEM severity,
severity of ME/CFS symptoms, comorbidities, illness duration, life
stressors, and lower socioeconomic status (6,14,15,78,99,100),
although findings remained inconclusive. Our findings suggest
younger age, shorter disease duration, a better Bell Score, and milder
fatigue (CFQ) at initial presentation could potentially indicate a
more favorable disease course in adolescents compared to adults.
The small patient sample size prohibits definite conclusions. The
interpretation of published data on ME/CFS outcome is challenged
by the fact that in many ME/CFS cohorts the initial trigger is less
well characterized than in our cohort (7,8,14–16,26,54,56).
4.7 Symptom load and health-related
quality of life over time
Patients experienced a wide range of persisting symptoms with
little change in severity or frequency over time, showing
interindividual variability and intraindividual fluctuations
throughout the year. Pediatric ME/CFS symptoms typically
fluctuate more than symptoms in adults (6). Adolescents
reported fewer symptoms at 6 and 12 months while adults’
symptom count remained steady. Adults consistently reported
more symptoms and nearly double the frequency of adolescents.
Quantifying frequency and severity of symptoms was
recommended to increase the specificity of ME/CFS diagnosis
(101), since mild symptoms are common in the general
population. Our novel MBSQ can be use to quantify the severity
and frequency of ME/CFS symptoms in a 5-point Likert scale (76).
Previous studies revealed that ME/CFS profoundly affects
social life, education, and HRQoL of children and young adults,
showing poorer HRQoL compared to peers with various other
chronic diseases (7,9–11). Notably, our adolescent cohort’s
PedsQL results closely resembled those from other countries,
depicting similar HRQoL distributions (9,10,102,103), with
worse HRQoL in physical and school function and better results
in social and emotional functioning.
Over time, adolescents showed moderate improvements in
total, physical, and psychosocial score, particularly in the school
domain, although social and emotional aspects remained stable.
These improvements exceeded suggested clinically meaningful
differences in pediatric cohorts (104). Intensive school counseling
might have contributed to better school situations and HRQoL
changes. We found little evidence of improved HRQoL in young
adults, except for some gains in emotional and social
subdomains, likely due to specialized care. Compared to
adolescents, young adults in our cohort reported significantly
lower HRQoL, which aligns with general findings on adult ME/
CFS patients consistently demonstrating very low HRQoL (105,
106). The transition from pediatrics to adult patient medicine
can be particularly challenging for young people with ME/CFS,
with uncertainties regarding health care, education, financials,
and contact to peers. Unrevealing age-specific risk factors will be
crucial for developing effective preventive strategies.
Few studies have investigated HRQoL in adolescents with ME/CFS.
Factors contributing to low HRQoL were identified as high frequency of
PEM, cognitive symptoms, regular school absence, delayed school
progression, and attending physical therapy or rehabilitation. School
support and attendance, along with leisure activities, correlated with
better HRQoL (9,10). Contradictory findings exist about the impact
of depressive symptoms (9,10,103,106). ME/CFS criteria requiring
PEM might select patients with worse HRQoL compared to
polythetic criteria (10), and this might be especially true for the
complex CCC used to diagnose ME/CFS in our adult patients.
4.8 Strengths and limitations
A strength of our study lies in providing long-term data on ME/
CFS after serologically confirmed EBV-IM, supporting earlier
reports on recovery (6,7,17). Confirming an infectious trigger of
ME/CFS years later is challenging due to unreliable self-reports and
to difficulties obtaining prior medical records. A second strength is
the combined analyses of data from adolescents and young adults.
The latter population often gets lost from pediatric as well as non-
pediatric studies (107). Third and importantly, we provide data on
ME/CFS cases that were diagnosed by clinical criteria requiring PEM
as recommended by the European Network on ME/CFS research
(EUROMENE) (46) and the Centers of Disease Control and
Prevention (CDC) (79). Overall, our study adds to the current
understanding of ME/CFS in young people and highlights the
importance of an early diagnosis as well es of a thorough
longitudinal evaluation of patients with ME/CFS following EBV-IM.
The study has limitations to be considered when interpreting
the results. First, the low sample size and a potential selection
bias limit the generalizability of results and may affect the
statistical power. Second, although the drop-out rate of 20% at
12 months was deemed acceptable, it might contribute another
bias. Third, the investigation of preexisting risk factors was
limited, since patients were seen late after ME/CFS onset with
potential recall bias. In addition, a longer follow-up period would
be beneficial. Finally, the lack of a matched control group
challenges the interpretation. Future studies with larger sample
sizes, longer follow-up periods, and appropriate control groups
are necessary to further validate and extend our findings.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 12 frontiersin.org
4.9 Conclusions
In conclusion, ME/CFS after EBV-IM is a debilitating disease
that results in severe functional impairment and poor HRQoL of
both adolescents and young adults, with evidence of partial
recovery in adolescents over time. Access to appropriate
healthcare is a fundamental barrier for young people with ME/
CFS in Germany as well as abroad. ME/CFS patients showed
fluctuating symptoms, with adults reporting more symptoms,
greater physical impairment, and worse HRQoL than adolescents.
Laboratory findings did not provide any evidence for EBV
replication perpetuating the disease. Further research is needed to
clarify the responsible pathomechanisms, identify reliable
biomarkers and risk-factors, and to develop effective strategies
for ME/CFS treatments and prevention in young people.
Data availability statement
The raw data supporting the conclusions of this article will be
made available by the others upon reasonable request.
Ethics statement
Patients and parents (of patients <18 years) provided informed
written consent prior to inclusion. The study was approved by the
Ethics Committee of the Technical University of Munich (529/18,
485/18) and conducted in accordance with the Declaration of
Helsinki and its later amendments.
Author contributions
RP: Conceptualization, Data curation, Formal Analysis,
Investigation, Validation, Visualization, Writing –original draft,
Writing –review & editing. PM: Conceptualization, Investigation,
Validation, Writing –review & editing. TH: Conceptualization,
Writing –review & editing. HZ: Investigation, Writing –review
& editing. YM: Investigation, Writing –review & editing. KW:
Investigation, Writing –review & editing. KaM: Writing –review
& editing. JP: Investigation, Writing –review & editing. AL:
Investigation, Writing –review & editing. MH: Writing –
original draft, Writing –review & editing. SM-H: Formal
Analysis, Writing –review & editing. KG: Conceptualization,
Supervision, Writing –review & editing. KiM: Writing –review
& editing. CS: Writing –review & editing. HR-P: Writing –
review & editing. LM: Data curation, Formal Analysis,
Validation, Visualization, Writing –original draft, Writing –
review & editing. UB: Conceptualization, Formal Analysis,
Funding acquisition, Project administration, Resources,
Supervision, Writing –original draft, Writing –review & editing.
Funding
The author(s) declare financial support was received for the
research, authorship, and/or publication of this article.
This work has been supported by the Lost Voices and
Weidenhammer-Zoebele foundations.
Acknowledgments
We thank all patients who participated in this study and their
parents for supporting their participation.
Conflict of interest
UB received research grants from Federal Ministry of
Education and Research (BMBF), the Federal Ministry of Health
(BMG), the Bavarian Ministry of Health and Care (StMGP), the
Bavarian Ministry of Science and Arts (StMWK), the German
Center for Infection Research (DZIF), the People for Children
(Menschen für Kinder) Foundation, the Weidenhammer-Zöbele
Foundation, the Lost-Voices Foundation, and the ME/CFS
Research Foundation. CS was consulting 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
Weidenhammer-Zoebele Foundation, the Lost-Voices
Foundation, and the ME/CFS Research Foundation.
The remaining authors declare that the research was conducted
in the absence of any commercial or financial relationships that
could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed
or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fped.2023.
1266738/full#supplementary-material
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 13 frontiersin.org
References
1. Unger ER, Lin JS, Tian H, Natelson BH, Lange G, Vu D, et al. Multi-site clinical
assessment of myalgic encephalomyelitis/chronic fatigue syndrome (MCAM): design and
implementation of a prospective/retrospective rolling cohort study. Am J Epidemiol.
(2017) 185(8):617–26. doi: 10.1093/aje/kwx029
2. Pendergrast T, Brown A, Sunnquist M, Jantke R, Newton JL, Strand EB, et al.
Housebound versus nonhousebound patients with myalgic encephalomyelitis and
chronic fatigue syndrome. Chronic Illn. (2016) 12(4):292–307. doi: 10.1177/
1742395316644770
3. Crawley E, Sterne JA. Association between school absence and physical function
in paediatric chronic fatigue syndrome/myalgic encephalopathy. Arch Dis Child.
(2009) 94(10):752–6. doi: 10.1136/adc.2008.143537
4. Van Geelen SM, Bakker RJ, Kuis W, Van De Putte EM. Adolescent chronic
fatigue syndrome. Arch Pediatr Adolesc Med. (2010) 164(9):810–4. doi: 10.1001/
archpediatrics.2010.145
5. Nijhof SL, Maijer K, Bleijenberg G, Uiterwaal CSPM, Kimpen JLL, Van De Putte
EM. Adolescent chronic fatigue syndrome: prevalence, incidence, and morbidity.
Pediatrics. (2011) 127(5):e1169–75. doi: 10.1542/peds.2010-1147
6. Rowe PC, Underhill RA, Friedman KJ, Gurwitt A, Medow MS, Schwartz MS, et al.
Myalgic encephalomyelitis/chronic fatigue syndrome diagnosis and management in
young people: a primer. Front Pediatr. (2017) 5(121). doi: 10.3389/fped.2017.00121
7. Rowe KS. Long term follow up of young people with chronic fatigue syndrome
attending a pediatric outpatient service. Front Pediatr. (2019) 7(21). doi: 10.3389/
fped.2019.00021
8. Crawley EM, Emond AM, Sterne JA. 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(2):e000252.
doi: 10.1136/bmjopen-2011-000252
9. Similä WA, Halsteinli V, Helland IB, Suvatne C, Elmi H, Rø TB. Health-related
quality of life in Norwegian adolescents living with chronic fatigue syndrome. Health
Qual Life Outcomes. (2020) 18(1). doi: 10.1186/s12955-020-01430-z
10. Roma M, Marden CL, Flaherty MAK, Jasion SE, Cranston EM, Rowe PC.
Impaired health-related quality of life in adolescent myalgic encephalomyelitis/
chronic fatigue syndrome: the impact of core symptoms. Front Pediatr. (2019) 7:26.
doi: 10.3389/fped.2019.00026
11. Kennedy G, Underwood C, Belch JJF. Physical and functional impact of chronic
fatigue syndrome/myalgic encephalomyelitis in childhood. Pediatrics. (2010) 125(6):
e1324–30. doi: 10.1542/peds.2009-2644
12. Bakken IJ, Tveito K, Gunnes N, Ghaderi S, Stoltenberg C, Trogstad L, et al. 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(1).
doi: 10.1186/s12916-014-0167-5
13. Jason LA, Katz BZ, Sunnquist M, Torres C, Cotler J, Bhatia S. The prevalence of
pediatric myalgic encephalomyelitis/chronic fatigue syndrome in a community-based
sample. Child Youth Care Forum. (2020) 49(4):563–79. doi: 10.1007/s10566-019-
09543-3
14. Josev EK, Cole RC, Scheinberg A, Rowe K, Lubitz L, Knight SJ. Health,
wellbeing, and prognosis of Australian adolescents with myalgic encephalomyelitis/
chronic fatigue syndrome (ME/CFS): a case-controlled follow-up study. J Clin Med.
(2021) 10(16):3603. doi: 10.3390/jcm10163603
15. Sankey A, Hill CM, Brown J, Quinn L, Fletcher A. A follow-up study of chronic
fatigue syndrome in children and adolescents: symptom persistence and school
absenteeism. Clin Child Psychol Psychiatry. (2006) 11(1):126–38. doi: 10.1177/
1359104506059133
16. Bell DS, Jordan K, Robinson M. Thirteen-year follow-up of children and
adolescents with chronic fatigue syndrome. Pediatrics. (2001) 107(5):994–8. doi: 10.
1542/peds.107.5.994
17. Katz BZ, Jason LA. Chronic fatigue syndrome following infections in adolescents.
Curr Opin Pediatr. (2013) 25(1):95–102. doi: 10.1097/MOP.0b013e32835c1108
18. Hickie I, Davenport T, Wakefield D, Vollmer-Conna U, Cameron B, Vernon SD,
et al. Post-infective and chronic fatigue syndromes precipitated by viral and non-viral
pathogens: prospective cohort study. Br Med J. (2006) 333(7568):575. doi: 10.1136/
bmj.38933.585764.AE
19. Jason LA, Cotler J, Islam MF, Sunnquist M, Katz BZ. Risks for developing
myalgic encephalomyelitis/chronic fatigue syndrome in college students following
infectious mononucleosis: a prospective cohort study. Clin Infect Dis. (2021) 73(11):
e3740–6. doi: 10.1093/cid/ciaa1886
20. Choutka J, Jansari V, Hornig M, Iwasaki A. Unexplained post-acute infection
syndromes. Nat Med. (2022) 28(5):911–23. doi: 10.1038/s41591-022-01810-6
21. Kedor C, Freitag H, Meyer-Arndt L, Wittke K, Hanitsch LG, Zoller T, 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(1):5104. doi: 10.1038/s41467-022-
32507-6
22. Chu L, Valencia IJ, Garvert DW, Montoya JG. Onset patterns and course of
myalgic encephalomyelitis/chronic fatigue syndrome. Front Pediatr. (2019) 7:12.
doi: 10.3389/fped.2019.00012
23. Pedersen M, Asprusten TT, Godang K, Leegaard TM, Osnes LT, Skovlund E,
et al. 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. doi: 10.1016/j.bbi.2018.09.023
24. Moss-Morris R, Spence MJ, Hou R. The pathway from glandular fever to chronic
fatigue syndrome: can the cognitive behavioural model provide the map? Psychol Med.
(2011) 41(5):1099–107. doi: 10.1017/S003329171000139X
25. Katz BZ, Shiraishi Y, Mears CJ, Binns HJ, Taylor R. Chronic fatigue syndrome
after infectious mononucleosis in adolescents. Pediatrics. (2009) 124(1):189–93.
doi: 10.1542/peds.2008-1879
26. Gill AC, Dosen A, Ziegler JB. Chronic fatigue syndrome in adolescents: a
follow-up study. Arch Pediatr Adolesc Med. (2004) 158(3):225–9. doi: 10.1001/
archpedi.158.3.225
27. Candy B, Chalder T, Cleare AJ, Wessely S, White PD, Hotopf M. Recovery from
infectious mononucleosis: a case for more than symptomatic therapy? A systematic
review. Br J Gen Pract. (2002) 52(483):844–51.
28. White PD, Thomas JM, Kangro HO, JBruce-ones WDA, Amess J, Crawford DH,
et al. Predictions and associations of fatigue syndromes and mood disorders that occur
after infectious mononucleosis. Lancet. (2001) 358(9297):1946–54. doi: 10.1016/
S0140-6736(01)06961-6
29. Buchwald DS, Rea TD, Katon WJ, Russo JE, Ashley RL. Acute infectious
mononucleosis: characteristics of patients who report failure to recover. Am J Med.
(2000) 109(7):531–7. doi: 10.1016/S0002-9343(00)00560-X
30. White PD, Thomas JM, Amess J, Crawford DH, Grover SA, Kangro HO, et al.
Incidence, risk and prognosis of acute and chronic fatigue syndromes and psychiatric
disorders after glandular fever. Br J Psychiatry. (1998) 173(6):475–81. doi: 10.1192/bjp.
173.6.475
31. Mirin AA, Dimmock ME, Jason LA. Updated ME/CFS prevalence estimates
reflecting post-COVID increases and associated economic costs and funding
implications. Fatigue: Biomed Health Behav. (2022) 10(2):83–93. doi: 10.1080/
21641846.2022.2062169
32. Komaroff AL, Bateman L. Will COVID-19 lead to myalgic encephalomyelitis/
chronic fatigue syndrome? Front Med. (2021) 7. doi: 10.3389/fmed.2020.606824
33. Roessler M, Tesch F, Batram M, Jacob J, Loser F, Weidinger O, et al. Post-
COVID-19-associated morbidity in children, adolescents, and adults: a matched
cohort study including more than 157,000 individuals with COVID-19 in Germany.
PLoS Med. (2022) 19(11):e1004122. doi: 10.1371/journal.pmed.1004122
34. Piraino B, Vollmer-Conna U, Lloyd AR. Genetic associations of fatigue and
other symptom domains of the acute sickness response to infection. Brain Behav
Immun. (2012) 26(4):552–8. doi: 10.1016/j.bbi.2011.12.009
35. Wirth K, Scheibenbogen C. A unifying hypothesis of the pathophysiology of
myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS): recognitions from
the finding of autoantibodies against ss2-adrenergic receptors. Autoimmun Rev.
(2020) 19(6):102527. doi: 10.1016/j.autrev.2020.102527
36. Renz-Polster H, Tremblay ME, Bienzle D, Fischer JE. The pathobiology of
myalgic encephalomyelitis/chronic fatigue syndrome: the case for neuroglial failure.
Front Cell Neurosci. (2022) 16:888232. doi: 10.3389/fncel.2022.888232
37. Komaroff AL, Lipkin WI. Insights from myalgic encephalomyelitis/
chronic fatigue syndrome may help unravel the pathogenesis of postacute COVID-
19 syndrome. Trends Mol Med. (2021) 27(9):895–906. doi: 10.1016/j.molmed.2021.
06.002
38. Cortes Rivera M, Mastronardi C, Silva-Aldana C, Arcos-Burgos M, Lidbury B.
Myalgic encephalomyelitis/chronic fatigue syndrome: a comprehensive review.
Diagnostics. (2019) 9(3):91. doi: 10.3390/diagnostics9030091
39. Rasa S, Nora-Krukle Z, Henning N, Eliassen E, Shikova E, Harrer T, et al. Chronic
viral infections in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).
JTranslMed. (2018) 16(1):268. doi: 10.1186/s12967-018-1644-y
40. Underhill RA. Myalgic encephalomyelitis, chronic fatigue syndrome: an infectious
disease. Med Hypotheses. (2015) 85(6):765–73. doi: 10.1016/j.mehy.2015.10.011
41. Ruiz-Pablos M, Paiva B, Montero-Mateo R, Garcia N, Zabaleta A. Epstein-Barr
virus and the origin of myalgic encephalomyelitis or chronic fatigue syndrome. Front
Immunol. (2021) 12:656797. doi: 10.3389/fimmu.2021.656797
42. Loebel M, Strohschein K, Giannini C, Koelsch U, Bauer S, Doebis C, et al.
Deficient EBV-specific B- and T-cell response in patients with chronic fatigue
syndrome. PLoS One. (2014) 9(1):e85387. doi: 10.1371/journal.pone.0085387
43. Shikova E, Reshkova V, Kumanova A, Raleva S, Alexandrova D, Capo N, et al.
Cytomegalovirus, Epstein-Barr virus, and human herpesvirus-6 infections in patients
with myalgic еncephalomyelitis/chronic fatigue syndrome. J Med Virol. (2020) 92
(12):3682–8. doi: 10.1002/jmv.25744
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 14 frontiersin.org
44. Komaroff AL. Chronic fatigue syndromes: relationship to chronic viral
infections. J Virol Methods. (1988) 21(1-4):3–10. doi: 10.1016/0166-0934(88)90047-X
45. Sepúlveda N, Malato J, Sotzny F, Grabowska AD, Fonseca A, Cordeiro C, et al.
Revisiting IgG antibody reactivity to Epstein-Barr virus in myalgic encephalomyelitis/
chronic fatigue syndrome and its potential application to disease diagnosis. Front Med.
(2022) 9:921101. doi: 10.3389/fmed.2022.921101
46. Nacul L, Authier FJ, Scheibenbogen C, Lorusso L, Helland IB, Martin JA, 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(5). doi: 10.3390/medicina57050510
47. Clayton EW. Beyond myalgic encephalomyelitis/chronic fatigue syndrome: an
IOM report on redefining an illness. JAMA. (2015) 313(11):1101–2. doi: 10.1001/
jama.2015.1346
48. Carruthers BM, Jain AK, De Meirleir KL, Peterson DL, Klimas NG, Lerner AM,
et al. Myalgic encephalomyelitis/chronic fatigue syndrome. J Chronic Fatigue Syndr.
(2003) 11(1):7–115. doi: 10.1300/J092v11n01_02
49. Jason LA, Jordan K, Miike T, Bell DS, Lapp C, Torres-Harding S, et al. A
pediatric case definition for myalgic encephalomyelitis and chronic fatigue
syndrome. J Chronic Fatigue Syndr. (2006) 13(2-3):1–44. doi: 10.1300/J092v13n02_01
50. Bateman L, Bested AC, Bonilla HF, Chheda BV, Chu L, Curtin JM, et al. Myalgic
encephalomyelitis/chronic fatigue syndrome: essentials of diagnosis and management.
Mayo Clin Proc. (2021) 96(11):2861–78. doi: 10.1016/j.mayocp.2021.07.004
51. Scheibenbogen C, Bellmann-Strobl JT, Heindrich C, Wittke K, Stein E, Franke C,
et al. Fighting post-COVID and ME/CFS –development of curative therapies. Front
Med. 10. doi: 10.3389/fmed.2023.1194754
52. Beyond myalgic encephalomyelitis/chronic fatigue syndrome: redefining an
illness. Mil Med. (2015) 180(7):721–3. doi: 10.7205/MILMED-D-15-00085
53. Moore Y, Serafimova T, Anderson N, King H, Richards A, Brigden A, et al.
Recovery from chronic fatigue syndrome: a systematic review—heterogeneity of
definition limits study comparison. Arch Dis Child. (2021) 106(11):1087–94. doi: 10.
1136/archdischild-2020-320196
54. Norris T, Collin SM, Tilling K, Nuevo R, Stansfeld SA, Sterne JA, et al. Natural
course of chronic fatigue syndrome/myalgic encephalomyelitis in adolescents. Arch
Dis Child. (2017) 102(6):522–8. doi: 10.1136/archdischild-2016-311198
55. Lim A, Lubitz L. Chronic fatigue syndrome: successful outcome of an intensive
inpatient programme. J Paediatr Child Health. (2002) 38(3):295–9. doi: 10.1046/j.
1440-1754.2002.00786.x
56. Rangel L, Garralda ME, Levin M, Roberts H. The course of severe chronic fatigue
syndrome in childhood. J R Soc Med. (2000) 93(3):129–34. doi: 10.1177/
014107680009300306
57. Krilov LR, Fisher M, Friedman SB, Reitman D, Mandel FS. Course and outcome
of chronic fatigue in children and adolescents. Pediatrics. (1998) 102(2 Pt 1):360–6.
doi: 10.1542/peds.102.2.360
58. Smith MS, Mitchell J, Corey L, Gold D, McCauley EA, Glover D, et al. Chronic
fatigue in adolescents. Pediatrics. (1991) 88(2):195–202. doi: 10.1542/peds.88.2.195
59. Devendorf AR, Jackson CT, Sunnquist M, Jason LA. Approaching recovery from
myalgic encephalomyelitis and chronic fatigue syndrome: challenges to consider in
research and practice. J Health Psychol. (2017) 24(10):1412–24. doi: 10.1177/
1359105317742195
60. Cairns R, Hotopf M. A systematic review describing the prognosis of chronic
fatigue syndrome. Occup Med. (2005) 55(1):20–31. doi: 10.1093/occmed/kqi013
61. Collin SM, Crawley E. Specialist treatment of chronic fatigue syndrome/ME: a
cohort study among adult patients in England. BMC Health Serv Res. (2017) 17
(1):488. doi: 10.1186/s12913-017-2437-3
62. Knight S, Harvey A, Lubitz L, Rowe K, Reveley C, Veit F, et al. Paediatric chronic
fatigue syndrome: complex presentations and protracted time to diagnosis. J Paediatr
Child Health. (2013) 49(11):919–24. doi: 10.1111/jpc.12425
63. Solomon L, Reeves WC. Factors influencing the diagnosis of chronic fatigue
syndrome. Arch Intern Med. (2004) 164(20):2241–5. doi: 10.1001/archinte.164.20.2241
64. Froehlich L, et al. Medical care situation of people with myalgic
encephalomyelitis/chronic fatigue syndrome in Germany. Medicina. (2021) 57
(7):646. doi: 10.3390/medicina57070646
65. Friedman KJ. Advances in ME/CFS: past, present, and future. Front Pediatr.
(2019) 7:131. doi: 10.3389/fped.2019.00131
66. Sunnquist M, Nicholson L, Jason LA, Friedman KJ. Access to medical care for
individuals with myalgic encephalomyelitis and chronic fatigue syndrome: a call for
centers of excellence. Mod Clin Med Res. (2017) 1(1):28–35. doi: 10.22606/mcmr.
2017.11005
67. Varni JW, Seid M, Kurtin PS. PedsQL 4.0: reliability and validity of the pediatric
quality of life inventory version 4.0 generic core scales in healthy and patient
populations. Med Care. (2001) 39(8):800–12. doi: 10.1097/00005650-200108000-00006
68. Morfeld M, Kirchberger I, Bullinger M. SF-36 Fragebogen zum
Gesundheitszustand: Deutsche Version des Short Form-36 Health Survey. (2011).
69. Chalder T, Berelowitz G, Pawlikowska T, Watts L, Wessely S, Wright D, et al.
Development of a fatigue scale. J Psychosom Res. (1993) 37(2):147–53. doi: 10.1016/
0022-3999(93)90081-P
70. Wagner D, Nisenbaum R, Heim C, Jones JF, Unger ER, Reeves WC.
Psychometric properties of the CDC symptom inventory for assessment of chronic
fatigue syndrome. Popul Health Metr. (2005) 3(1). doi: 10.1186/1478-7954-3-8
71. Bell DS. The Doctor’s Guide to Chronic Fatigue Syndrome: Understanding,
Treating, and Living With CFIDS. Boston: Addison-Wesley Pub. Co (1995).
72. R Core Team. R: a Language and Environment for Statistical Computing. Vienna,
Austria: R Foundation for Statistical Computing (2023).
73. Bakdash JZ, Marusich LR. Repeated measures correlation. Front Psychol. (2017)
8. doi: 10.3389/fpsyg.2017.00456
74. Geraghty KJ, AdenijiC. The importance of accurate diagnosis of ME/CFS in children
and adolescents: a commentary. Front Pediatr. (2019) 6. doi: 10.3389/fped.2018.00435
75. Collin SM, Nuevo R, van de Putte EM, Nijhof SL, Crawley E. Chronic fatigue
syndrome (CFS) or myalgic encephalomyelitis (ME) is different in children
compared to in adults: a study of UK and Dutch clinical cohorts. BMJ Open. (2015)
5(10):e008830. doi: 10.1136/bmjopen-2015-008830
76. Peo LC, Wiehler K, Paulick J, Gerrer K, Leone A, Viereck A, 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. (2023).
doi: 10.1007/s00431-023-05351-z
77. Webb CM, Collin SM, Deave T, Haig-Ferguson A, Spatz A, Crawley E. What
stops children with a chronic illness accessing health care: a mixed methods study
in children with chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME).
BMC Health Serv Res. (2011) 11:308. doi: 10.1186/1472-6963-11-308
78. Ghali A, Lacout C, Fortrat J-O, Depres K, Ghali M, Lavigne C. Factors
influencing the prognosis of patients with myalgic encephalomyelitis/chronic fatigue
syndrome. Diagnostics. (2022) 12:2540. doi: 10.3390/diagnostics12102540
79. White PH, Cooley WC. Supporting the health care transition from adolescence
to adulthood in the medical home. Pediatrics. (2018) 142(5):e20182587. doi: 10.1542/
peds.2018-2587
80. Loades ME, Sheils EA, Crawley E. Treatment for paediatric chronic fatigue
syndrome or myalgic encephalomyelitis (CFS/ME) and comorbid depression: a
systematic review. BMJ Open. (2016) 6(10):e012271. doi: 10.1136/bmjopen-2016-
012271
81. Loades ME, Read R, Smith L, Higson-Sweeney NT, Laffan A, Stallard P, et al.
How common are depression and anxiety in adolescents with chronic fatigue
syndrome (CFS) and how should we screen for these mental health co-morbidities?
A clinical cohort study. Eur Child Adolesc Psychiatry. (2021) 30(11):1733–43.
doi: 10.1007/s00787-020-01646-w
82. Freeman R, Wieling W, Axelrod FB, Benditt DG, Benarroch E, Biaggioni I, et al.
Consensus statement on the definition of orthostatic hypotension, neurally mediated
syncope and the postural tachycardia syndrome. Clin Auton Res. (2011) 21(2):69–72.
doi: 10.1007/s10286-011-0119-5
83. Katz BZ, Stewart JM, Shiraishi Y, Mears CJ, Taylor R. Orthostatic tolerance
testing in a prospective cohort of adolescents with chronic fatigue syndrome and
recovered controls following infectious mononucleosis. Clin Pediatr. (2012) 51
(9):835–9. doi: 10.1177/0009922812455094
84. Porter NS, Jason LA, Boulton A, Bothne N, Coleman B. Alternative medical
interventions used in the treatment and management of myalgic encephalomyelitis/
chronic fatigue syndrome and fibromyalgia. J Altern Complement Med. (2010) 16
(3):235–49. doi: 10.1089/acm.2008.0376
85. Parslow R, Patel A, Beasant L, Haywood K, Johnson D, Crawley E. What matters
to children with CFS/ME? A conceptual model as the first stage in developing a
PROM. Arch Dis Child. (2015) 100(12):1141–7. doi: 10.1136/archdischild-2015-
308831
86. Knight SJ, Politis J, Garnham C, Scheinberg A, Tollit MA. School functioning in
adolescents with chronic fatigue syndrome. Front Pediatr. (2018) 6:302. doi: 10.3389/
fped.2018.00302
87. Repka-Ramirez MS, Naranch K, Park YJ, Velarde A, Clauw D, Baraniuk JN. Ige
levels are the same in chronic fatigue syndrome (CFS) and control subjects when
stratified by allergy skin test results and rhinitis types. Ann Allergy Asthma
Immunol. (2001) 87(3):218–21. doi: 10.1016/S1081-1206(10)62229-6
88. Earl KE, Sakellariou GK, Sinclair M, Fenech M, Croden F, Owens DJ, et al.
Vitamin D status in chronic fatigue syndrome/myalgic encephalomyelitis: a cohort
study from the North-West of England. BMJ Open. (2017) 7(11):e015296. doi: 10.
1136/bmjopen-2016-015296
89. De Paschale M, Agrappi C, Manco MT, Mirri P, Viganò EF, Clerici P.
Seroepidemiology of EBV and interpretation of the “isolated VCA IgG”pattern.
J Med Virol. (2009) 81(2):325–31. doi: 10.1002/jmv.21373
90. Niller H-H, Bauer G. Epstein-Barr virus: clinical diagnostics, in Epstein Barr
virus: methods and protocols. In: Minarovits J, Niller HH, New York, NY: Springer
New York (2017). p. 33–55.
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 15 frontiersin.org
91. Ikuta K, Satoh Y, Hoshikawa Y, Sairenji T. Detection of Epstein-Barr virus in
salivas and throat washings in healthy adults and children. Microbes Infect. (2000) 2
(2):115–20. doi: 10.1016/S1286-4579(00)00277-X
92. Haque T, Crawford DH. PCR amplification is more sensitive than tissue culture
methods for Epstein-Barr virus detection in clinical material. J Gen Virol. (1997) 78
(12):3357–60. doi: 10.1099/0022-1317-78-12-3357
93. Kanakry JA, Hegde AM, Durand CM, Massie AB, Greer AE, Ambinder RF, et al.
The clinical significance of EBV DNA in the plasma and peripheral blood
mononuclear cells of patients with or without EBV diseases. Blood. (2016) 127
(16):2007–17. doi: 10.1182/blood-2015-09-672030
94. Lerner AM, Beqaj SH, Deeter RG, Fitzgerald JT. Igm serum antibodies to
Epstein-Barr virus are uniquely present in a subset of patients with the chronic
fatigue syndrome. In Vivo. (2004) 18(2):101–6.
95. Sairenji T, Yamanishi K, Tachibana Y, Bertoni G, Kurata T. Antibody responses
to Epstein-Barr virus, human herpesvirus 6 and human herpesvirus 7 in patients with
chronic fatigue syndrome. Intervirology. (1995) 38(5):269–73. doi: 10.1159/000150450
96. Lee JS, Lacerda EM, Nacul L, Kingdon CC, Norris J, O'Boyle S, et al. Salivary
DNA loads for human herpesviruses 6 and 7 are correlated with disease phenotype
in myalgic encephalomyelitis/chronic fatigue syndrome. Front Med. (2021)
8:656692. doi: 10.3389/fmed.2021.656692
97. Kerr JR. Epstein-Barr virus induced gene-2 upregulation identifies a particular
subtype of chronic fatigue syndrome/myalgic encephalomyelitis. Front Pediatr.
(2019) 7:59. doi: 10.3389/fped.2019.00059
98. Loebel M, Eckey M, Sotzny F, Hahn E, Bauer S, Grabowski P, et al. Serological
profiling of the EBV immune response in chronic fatigue syndrome using a peptide
microarray. PLoS One. (2017) 12(6):e0179124. doi: 10.1371/journal.pone.0179124
99. Lievesley K, Rimes KA, Chalder T. A review of the predisposing, precipitating
and perpetuating factors in chronic fatigue syndrome in children and adolescents.
Clin Psychol Rev. (2014) 34(3):233–48. doi: 10.1016/j.cpr.2014.02.002
100. Rimes KA, Goodman R, Hotopf M, Wessely S, Meltzer H, Chalder T.
Incidence, prognosis, and risk factors for fatigue and chronic fatigue syndrome in
adolescents: a prospective community study. Pediatrics. (2007) 119(3):e603–9.
doi: 10.1542/peds.2006-2231
101. Jason LA, Sunnquist M. The development of the DePaul symptom
questionnaire: original, expanded, brief, and pediatric versions. Front Pediatr. (2018)
6:330. doi: 10.3389/fped.2018.00330
102. Knight SJ, Harvey A, Hennel S, Lubitz L, Rowe K, Reveley C, et al. Measuring
quality of life and fatigue in adolescents with chronic fatigue syndrome: estimates of
feasibility, internal consistency and parent–adolescent agreement of the PedsQLTM.
Fatigue: Biomed Health Behav. (2015) 3(4):220–34. doi: 10.1080/21641846.2015.
1090816
103. Winger A, Kvarstein G, Wyller VB, Ekstedt M, Sulheim D, Fagermoen E, et al.
Health related quality of life in adolescents with chronic fatigue syndrome: a cross-
sectional study. Health Qual Life Outcomes. (2015) 13(1):96. doi: 10.1186/s12955-
015-0288-3
104. Varni JW, Burwinkle TM, Seid M, Skarr D. The PedsQL 4.0 as a pediatric
population health measure: feasibility, reliability, and validity. Ambul Pediatr. (2003)
3(6):329–41. doi: 10.1367/1539-4409(2003)003<0329:TPAAPP>2.0.CO;2
105. Falk Hvidberg M, Brinth LS, Olesen AV, Petersen KD, Ehlers L. The health-
related quality of life for patients with myalgic encephalomyelitis/chronic fatigue
syndrome (ME/CFS). PLoS One. (2015) 10(7):e0132421. doi: 10.1371/journal.pone.
0132421
106. Eaton-Fitch N, Johnston SC, Zalewski P, Staines D, Marshall-Gradisnik S.
Health-related quality of life in patients with myalgic encephalomyelitis/chronic
fatigue syndrome: an Australian cross-sectional study. Qual Life Res. (2020) 29
(6):1521–31. doi: 10.1007/s11136-019-02411-6
107. Borch L, Holm M, Knudsen M, Ellermann-Eriksen S, Hagstroem S. Long
COVID symptoms and duration in SARS-CoV-2 positive children—a nationwide
cohort study. Eur J Pediatr. (2022) 181(4):1597–607. doi: 10.1007/s00431-021-04345-z
Pricoco et al. 10.3389/fped.2023.1266738
Frontiers in Pediatrics 16 frontiersin.org
Available via license: CC BY
Content may be subject to copyright.