Content uploaded by Emily Whelan
Author content
All content in this area was uploaded by Emily Whelan on Oct 30, 2023
Content may be subject to copyright.
Citation: Newlands, F.; Goddings,
A.-L.; Juste, M.; Boyd, H.; Nugawela,
M.D.; Pinto Pereira, S.M.; Whelan, E.;
Whittaker, E.; Stephenson, T.;
Heyman, I.; et al. Children and
Young People with Long
COVID—Comparing Those Seen in
Post-COVID Services with a
Non-Hospitalised National Cohort: A
Descriptive Study. Children 2023,10,
1750. https://doi.org/10.3390/
children10111750
Academic Editor: Danilo Buonsenso
Received: 7 September 2023
Revised: 23 October 2023
Accepted: 24 October 2023
Published: 28 October 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
children
Article
Children and Young People with Long COVID—Comparing
Those Seen in Post-COVID Services with a Non-Hospitalised
National Cohort: A Descriptive Study
Fiona Newlands 1, * , Anne-Lise Goddings 1, Maude Juste 1, Holly Boyd 2, Manjula D. Nugawela 1,
Snehal M. Pinto Pereira 3, Emily Whelan 4, Elizabeth Whittaker 5, Terence Stephenson 1, Isobel Heyman 1,
Trudie Chalder 6, Emma Dalrymple 1, CLoCk Consortium †, Terry Segal 2and Roz Shafran 1
1Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
2University College London Hospitals NHS Foundation Trust, London NW1 2BU, UK
3Division of Surgery & Interventional Science, Faculty of Medical Sciences, University College London,
London WC1E 6BT, UK
4School of Psychology, University of Sussex, Brighton BN1 9QH, UK
5Department of Paediatric Infectious Diseases, Imperial College Healthcare NHS Trust, London W2 1NY, UK
6Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
*Correspondence: fiona.newlands.18@ucl.ac.uk
†CLoCk Consortium members are provided in the Acknowledgments.
Abstract:
Background: Post-COVID services have been set up in England to treat children with
ongoing symptoms of Long COVID. To date, the characteristics of children seeking treatment from
these services has not been described. Purpose: (1) to describe the characteristics of children aged
11–17
referred to the Pan-London Post-COVID service and (2) to compare characteristics of these
children with those taking part in the United Kingdom’s largest research study of Long COVID in
children (CLoCk). Design: Data from 95 children seeking treatment from the Post-COVID service
between May 2021 and August 2022 were included in the study. Their demographic characteristics,
symptom burden and the impact of infection are described and compared to children from CLoCk.
Results: A high proportion of children from the Post-COVID service and CLoCk reported experiencing
health problems prior to the pandemic. Almost all Post-COVID service children met the research
Delphi definition of Long COVID (94.6%), having multiple symptoms that impacted their lives.
Symptoms were notably more severe than the participants in CLoCk. Conclusions: This study
describes the characteristics of children seeking treatment for Long COVID compared to those
identified in the largest longitudinal observational study to date. Post-COVID service children have
more symptoms and are more severely affected by their symptoms following infection with COVID-
19 than children in the CLoCk study. Research to understand predisposing factors for severity and
prognostic indicators is essential to prevent this debilitating condition. Evaluation of short- and
long-term outcomes of interventions by clinical services can help direct future therapy for this group.
Keywords:
Post-COVID services; Long COVID; children and young people; paediatric; SARS-CoV-2
1. Introduction
It is widely accepted a significant proportion of children and young people (hereafter
referred to as ‘young people’) experience persistent symptoms following Severe Acute Res-
piratory Syndrome Coronavirus 2 (SARS-CoV-2) exposure [1]. The clinical manifestations
of paediatric COVID-19 are diverse with fever and cough being amongst the most com-
mon reported symptoms [
2
,
3
]. Children who continue to experience symptoms for at least
12 weeks post infection are said to have Long COVID (also known as Post-COVID-19 Condi-
tion) [
4
]. Common symptoms associated with the condition are similar to acute COVID-19
and include fatigue, cognitive difficulties, headache, loss of smell [
1
,
5
]. These symptoms
Children 2023,10, 1750. https://doi.org/10.3390/children10111750 https://www.mdpi.com/journal/children
Children 2023,10, 1750 2 of 13
may fluctuate or relapse over time and have an impact on everyday functioning [
4
,
6
].
Research on Long COVID is ongoing, and several studies indicate the condition can have
lasting effects on various organs and systems in the body including the kidneys, lungs, the
brain and haematological characteristics [
7
–
9
]. Given the complexity of the condition, there
is a need for specialist clinics to provide diagnosis and effective treatment options.
Specialised clinics, research initiatives and support groups have been set up across the
globe to help support young people living with the condition but the availability and extent
of these services vary from country to country (e.g., Ref. [
10
]). In June 2021, NHS England
announced they were setting up 15 specialist paediatric tertiary services as part of a GBP
100 million expansion of care for those suffering from Long COVID. What is offered at
each service is not uniform but the majority aim to offer multidisciplinary assessment and
management with a focus on supported self-management. The announcement of services
was positively received but there was a note of caution that critical evaluation was required
to ensure meaningful benefit [
11
]. In particular, it was suggested the new services should
be run as research hubs and be formally evaluated using in-practice data [11].
Although these research hubs did not come to fruition, there are now many studies
exploring Long COVID in young people and systematic reviews and meta-analyses of
the results have been conducted [
1
,
12
]. This research, combined with national survey
data [
13
] yields a mixed picture, but it is clear many patients infected with SARS-CoV-2
develop long-term symptoms [
14
]. Given over 90% of secondary school pupils in the United
Kingdom are estimated to have been exposed to SARS-CoV-2 [
15
], this has the potential to
be extremely concerning. Even with a conservative estimate of 0.51% of 12–16-year-olds
having Long COVID [
16
], with an estimated 4.9 million young people aged 10–16 in the
United Kingdom [
17
], it has the potential to overwhelm services. However, these data do
not detail symptom severity or impact on functionality, which may explain why prevalence
estimates do not map to demand for services. We do not yet know what factors result in
young people seeking treatment.
This study had two objectives: (1) describe the characteristics of young people aged
11–17 being referred to a Post-COVID service (PCS); and (2) compare these characteristics
with those of young people taking part in the Children and Young People with Long
COVID (CLoCk) study [
18
]. CLoCk is the largest matched cohort study of young people in
England, in which non-hospitalised young people reported symptoms after a laboratory-
confirmed SARS-CoV-2 infection and were compared to age- sex- and geographically
matched controls with a laboratory-confirmed SARS-CoV-2 negative test. Demographic
variables, symptoms and their impact were assessed using the questionnaire that had also
been used in some of the paediatric PCSs. This paper reports on data collected from the
Pan-London paediatric PCS.
Based on a combination of clinical observation and the existing literature, we had two
main hypotheses. Firstly, patients referred to the PCS would have similar demographics
to participants in CLoCk. Second, those referred to the PCS would experience the same
range of symptoms as those in CLoCk, but have more symptoms that were more impairing,
and a higher proportion of patients would meet the Delphi research definition of Long
COVID [4].
2. Methods
2.1. Study Design
This is a descriptive study comparing characteristics of patients aged 11–17 referred to
a PCS compared to young people in a national research study (CLoCk).
2.2. Setting
This paper reports on data collected from the Pan-London PCS established in April 2021.
Local triage and assessment are undertaken by a paediatrician or primary care provider (if
aged 16–18 yrs) to exclude other aetiological causes and secondary organ damage. This is
conducted by local National Health Service (NHS) paediatricians if the young person is
Children 2023,10, 1750 3 of 13
under 16 or by family physicians (‘General Practitioners’—GP—in England) if the patient is
16–18 years old. Where required, referrals to a PCS are made. The patient’s case is presented
to the virtual multidisciplinary team at the PCS who, after discussion, recommend the
patient be seen in person at the clinic or remain with their local service. Approximately
65% of patients are seen in person. The main reason for being seen at the service is severity
of symptoms and impact on functioning (for example, poor educational attendance and
not taking part in sports or activities).
For CLoCk, potential participants were identified using the national SARS-CoV-2
testing dataset held by the UK Health Security Agency (UKHSA) [
18
]. UKHSA received
results of all SARS-CoV-2 PCR tests in England irrespective of the reason they were taken.
Using this dataset, potential participants were approached by post and invited to take part
in the study.
2.3. Participants
All PCS young people were asked to complete the self-report questionnaire at referral.
For the PCS group, inclusion criteria were young people aged 11–17 years old who com-
pleted the questionnaire between 13 May 2021 and 17 August 2022. Patients did not require
a positive SARS-CoV-2 test to be referred to the service. PCS young people who did not
complete the survey were excluded from the analysis, as were PCS young people who were
under 11 and over 17 years old to make the sample more comparable to CLoCk participants.
For CLoCk participants, inclusion criteria were young people aged 11–17 who had a
positive PCR test between January 2021 and March 2021 and completed the questionnaire
between 13 April and 3 August 2021 [
5
]. This comparison group were those who completed
the questionnaire within 24 weeks of their PCR test to minimise the potential for recall bias.
Those participants who had a negative PCR between January 2021 and March 2021 and
who completed the questionnaire more than 24 weeks after their PCR test were excluded
from the study.
2.4. Variables/Measures
The questionnaire was based on the International Severe Acute Respiratory and
emerging Infection Consortium (ISARIC) working group [
19
] and contained demographic
information including age, gender and ethnicity coded using Office of National Statistical
categories [
20
]. It included an assessment of health prior to the pandemic, current health
and health during the acute COVID-19 phase (retrospective) and standardised well-being
measures. Standardised measures were selected to assess emotional wellbeing (Strengths
and Difficulties Questionnaire (SDQ)) [
21
], quality of life and everyday functioning (EQ-5D-
Y and EQ VAS) [
22
], fatigue (Chalder Fatigue Scale (CFS)) [
23
] and loneliness (UCLA-3) [
24
].
The Supplementary Materials and Table S1 present the questionnaire and details on how
measures were interpreted.
The Index of Multiple Deprivation (IMD) was used as a proxy for socioeconomic
status and was derived from the participants’ lower super output area (a small local area
level-based geographic hierarchy) [
25
]. IMD quintiles were calculated from most (quintile
1) to least (quintile 5) deprived.
PCS patients completed the questionnaire on a paper which was then entered into
Excel. A random sample of 10% of questionnaires were checked for quality assurance.
CLoCk participants completed an online version of the questionnaire [18].
2.5. Statistical Methods
The analysis was conducted using STATA v17. Descriptive statistics were used to
describe demographics (sex, age, ethnicity and region of residence), symptoms experi-
enced before the COVID-19 pandemic, symptoms during the acute SARS-CoV-2 phase
(retrospective) and at the time of completing the questionnaire (current). Histograms and
Shapiro–Wilk tests were conducted to assess the distribution of data. Data were sum-
marised as frequency and prevalence, means and standard deviations or medians and
Children 2023,10, 1750 4 of 13
interquartile ranges (IQR) as appropriate. Two-tailed Chi-squared, Fisher’s exact or Mann–
Whitney U tests were used to assess whether differences exist between PCS and CLoCk
young people, with a p-value < 0.05 considered significant. The Benjamini–Hochberg
method [
26
] was applied to account for the exploratory nature of analyses. p-values that
remained significant after accounting for the false discovery rate (FDR) were reported in
bold. Since the study was descriptive and explorative in nature, a power analysis was
not conducted.
The completeness of the PCS questionnaire data ranged from 89% (SDQ total score) to
100% with a mean completeness ratio of 97%. The completeness of the CLoCk questionnaire
data ranged from 99 to 100% with a mean completeness ratio of 100%. Where there were
missing data, the reported percentage is based on the complete data for that variable.
A sub-group analysis was conducted replicating the analysis described above to
compare PCS young people with CLoCk participants who met the Delphi definition of
Long COVID [4].
2.6. Ethics
The CLoCk study was approved by the Yorkshire and The Humber—South Yorkshire
Research Ethics Committee (REC reference: 21/YH/0060; IRAS project ID:293495). The
project was registered as a service evaluation and was approved by the Paediatrics and
Adolescent Division Quality and Safety Lead (registered on 30 March 2023).
3. Results
Between May 2021 and August 2022, 209 patients were referred to the PCS and
112 young people completed the questionnaire (completion rate 53.6%); 17 young people
were excluded because they were under 11 or over 17 years old, leaving 95 in the final
analysis. PCS young people took a test between 1 October 2020 and 1 May 2022 and
completed the questionnaire between 13 May 2021 and 17 August 2022. For patients
who reported a positive SARS-CoV-2 test (n= 70), the median time between the test and
completing the questionnaire was 29.8 weeks (IQR 19.6–37.7).
Of the 23,048 PCR test-positive young people invited to take part in CLoCk, 3065 con-
sented and completed the questionnaire within 24 weeks of their PCR test (response rate
13.3%). Young people took PCR tests that were registered on the UKHSA database between
1 January 2021 and 31 March 2021 and completed the questionnaire between 13 April 2021
and 3 August 2021 (median 14.6 weeks after PCR test).
The median age of PCS young people was 14 years (IQR 13, 15) compared to 15 years
(IQR 13, 16) for CLoCk young people (Table 1). PCS consisted of more females and White
young people than CLoCk (females: 67.4% (PCS), 63.5% (CLoCk); White: 84.2% (PCS),
72.8% (CLoCk); p
≤
0.001 for both). Based on IMD, PCS young people were from less
deprived areas than CLoCk young people, for example, 28.4% of PCS were from the ‘least
deprived’ quantile compared to 20.4% from CLoCk (X2(4) = 13.4; p= 0.009).
A high proportion of young people reported experiencing health symptoms prior
to the pandemic including allergies (PCS: 39.4%; CLoCk: 30.9%) and often feeling tired
(PCS: 36.2%; CLoCk: 40.2%). There were no significant differences between groups for
these symptoms (p> 0.05). PCS young people were significantly more likely to report
experiencing problems with stomach, gut, liver, kidneys or digestion (PCS: 16.1%; CLoCk:
4.3%; p< 0.001), a neurological disease (PCS: 4.3%; CLoCk: 1.4%; p= 0.05), a physical
disability (PCS: 11.7%; CLoCk: 2.2%; p< 0.001), a learning difficulty (PCS: 13.8%; CLoCk:
8.0%; X2(1) = 4.1; p< 0.04), problems with sleep (PCS: 28.3%; CLoCk: 17.9%; X2(1) = 6.4;
p= 0.01), tummy aches (PCS: 32.3%; CLoCk: 16.3%; X2(1) = 16.4; p< 0.001) and other
serious illness (PCS: 13.0%; CLoCk: 2.2%; p< 0.001). Table S2 displays the comparative
statistics for symptoms prior to the pandemic.
Children 2023,10, 1750 5 of 13
Table 1. Characteristics of participants in the Post-COVID service and CLoCk.
Post-COVID Service
(n= 95) 1
CLoCk 2
(n= 3065)
# % # %
Sex 3Female 64 67.4% 1945 63.5%
Male 29 30.5% 1120 36.5%
Prefer not to say 2 2.1%
Age 11 6 6.3% 283 9.2%
12 11 11.6% 285 9.3%
13 17 17.9% 315 10.3%
14 24 25.3% 361 11.8%
15 18 19.0% 477 15.6%
16 14 14.7% 622 20.3%
17 5 5.3% 722 23.6%
Mean age (SD) 14.0 (1.6) 14.7 (2.0)
Median (IQR) 14 (13, 15) 15 (13, 16)
Ethnicity White 80 84.2% 2231 72.8%
Asian/Asian/British 2 2.1% 491 16.0%
Black/African/Caribbean/British
1 1.1% 109 3.6%
Mixed 10 10.5% 147 4.8%
Other 1 1.1% 60 2.0%
Prefer not to say/unknown 1 1.1% 27 0.9%
IMD 41 (most deprived) 5 5.8% 643 21.0%
2 18 20.7% 633 20.7%
3 19 21.8% 571 18.6%
4 20 23.0% 593 19.3%
5 (least deprived) 25 28.4% 625 20.4%
1
NB: # varies due to missing data from 87 (for IMD) to 95 (for age, ethnicity and sex).
2
Children and Young
People with Long COVID (CLoCk) study.
3
Data were provided by UKHSA who have a record of assigned sex at
birth. 4Index of Multiple Deprivation.
PCS young people were more likely to report ‘some’ or ‘a lot’ of problems with daily
function prior to the pandemic on the mobility (PCS: 14.0%; CLoCk: 4.4%; p< 0.001), self-
care (PCS: 8.6%; CLoCk: 3.7%; p= 0.009), doing usual activities (PCS: 12.9%; CLoCk: 10.8%;
p< 0.001) and pain (PCS: 19.4%; CLoCk: 14.7%; p< 0.009) domains of the EQ-5D-Y. There
was no difference between the two groups on the sad/worried domain of the EQ-5D-Y
(X2(2) = 2.6; p= 0.28).
3.1. Symptoms during Acute COVID-19 Phase (Retrospective)
During the acute COVID-19 phase, PCS young people reported more symptoms than
those in CLoCk (median number of symptoms PCS: 10.0, IQR 7.0–14; CLoCk: 0.0, IQR
0.0–4.0; p< 0.001). Common symptoms are reported in Table S3.
3.2. Current Symptoms
A higher proportion of PCS young people met the Delphi definition of Long COVID
(i.e., had at least 1 symptom which was causing functional impairment as indicated by the
EQ-5D-Y) than CLoCk young people (PCS: 94.6%, 95% CI 87.8–98.2%; CLoCk: 25.6%; 95%
CI 24.0–27.1%).
Children 2023,10, 1750 6 of 13
The majority of PCS young people (77.7%) experienced 5 or more symptoms at the
time of completing the questionnaire (median 29.8 weeks after acute COVID-19 infection)
compared to 13.4% of young people in CLoCK (median 14.6 weeks after PCR test-positive;
X2(5) = 296.4; p< 0.001). The median number of symptoms reported by PCS young people
was 8.0 (IQR 5.0–10.0) compared to 1.0 (0.0–3.0) in CLoCk.
The same symptoms were most common in both groups including tiredness, headaches,
dizziness or light-headedness and shortness of breath; however, symptom prevalence was
higher in the PCS group than in CLoCk. See Table 2.
Table 2. Heat map demonstrating current symptom prevalence in PCS and CLoCk populations 1.
Symptom PCS (n = 95) 2CLoCk (n = 3065) Statistical Test 3
Tiredness 97.8% 39.0% X2(1)= 127.9; p< 0.001
Headaches 74.2% 23.2% X2(1)= 126.5; p< 0.001
Dizziness or
light-headedness 70.7% 13.7% X2(1)= 223.4; p< 0.001
Shortness of breath 64.8% 23.4% X2(1)= 79.1; p< 0.001
Confusion,
disorientation or
downiness
47.9% 6.5% X2(1)= 220.3; p< 0.001
Unusual eye soreness 46.8% 5.9% X2(1)= 229.3; p< 0.001
Unusually sore
muscle pains 45.3% 5.4% X2(1)= 238.3; p< 0.001
Skipping meals 43.0% 9.7% X2(1)= 105.6; p< 0.001
Unusual chest pain 41.5% 7.0% X2(1)= 145.8; p< 0.001
Unusual abdominal
pain 436.9% 3.9% p< 0.001
Earache or ringing in
the ears 35.1% 6.2% X2(1)= 115.4; p< 0.001
Loss of smell/taste 26.9% 13.5% X2(1)= 13.5; p< 0.001
Raised welts on skin
or swelling 426.9% 1.6% p< 0.001
Chills 26.4% 8.8% X2(1) = 32.5; p< 0.001
Diarrhoea 422.0% 3.0% p< 0.001
Sore throat 21.1% 9.5% X2(1)= 13.9; p< 0.001
Persistent cough 49.8% 3.2% p= 0.003
Unusually hoarse
voice 49.6% 1.8% p< 0.001
Red or purple sores
or blisters on feet 49.7% 1.1% p< 0.001
Fever 46.5% 1.6% p= 0.005
1
Darker colour cells represent symptoms with the highest prevalence.
2
NB: # varies due to missing data from
88 (shortness of breath) to 95 (sore throat).
3
Number of comparisons = 68; false discovery rate (FDR) = 0.0375;
p-values presented in bold were still significant after accounting for the FDR.
4
Fisher’s exact test was used where
assumptions for Chi-squared were not met.
PCS young people were significantly more likely to report ‘some’ or ‘a lot’ of on all
domains of the EQ-5D-Y (p< 0.001), suggesting a poorer health-related quality of life (see
Figure 1and Table S4). EQ-VAS scores were significantly lower in PCS young people
indicating a poorer health-related quality of life (PCS: 35.0%, 20.0–55.0%; CLoCk: 90.0%,
80.0–95.0%; z = −14.7; p< 0.001).
Children 2023,10, 1750 7 of 13
Children 2023, 10, x FOR PEER REVIEW 7 of 13
Figure 1 and Table S4). EQ-VAS scores were significantly lower in PCS young people in-
dicating a poorer health-related quality of life (PCS: 35.0%, 20.0–55.0%; CLoCk: 90.0%,
80.0–95.0%; z = −14.7; p < 0.001).
Figure 1. Current health-related quality of life measured by the EQ-5D-Y. 1 NB: The number of par-
ticipants in the PCS varies due to missing data from 91 to 92. ** Significant difference between PCS
and CLoCk sample at p < 0.001.
There was no difference between the two groups in emotional well-being as assessed
by total SDQ scores (median 12 (7–17) for PCS young people and 11 (6–15) for young peo-
ple in CLoCk (z = −1.8; p = 0.07)). However, SDQ impact scores were significantly higher
in PCS young people (PCS: 2 (0–5); CLoCk 0 (0-1); z = −7.7; p < 0.001) indicating symptoms
were having a greater impairment and causing more distress.
Additionally, 96.7% of PCS young people were ‘fatigued’ compared to 35.5% of
CLoCk young people (X2(1) = 136.9; p < 0.001). PCS young people were more likely to
report feeling lonely as indicated by UCLA-3 loneliness scores (PCS: 13.2%; CLoCk: 6.5%;
X2(1) = 6.4; p = 0.01).
3.3. Subgroup Analysis-PCS and CLoCk Delphi Young People
Of the 3065 test-positive respondents, 783 (25.6%) met the research Delphi definition
of Long COVID [4]. As with the main CLoCk sample, Delphi young people were predom-
inantly Female (74.2%) and White (74.3%). There were fewer CLoCk Delphi participants
from the least deprived areas of England than in the main sample (16.45% and 20.4%,
respectively). Table S5 presents the demographic characteristics of CLoCk Delphi young
people.
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
Post
COVID
service
CLoCk Post
COVID
service
CLoCk Post
COVID
service
CLoCk Post
COVID
service
CLoCk Post
COVID
service
CLoCk
Mobility
(walking
about)**
Looking after
myself**
Having pain or
discomfort**
Doing usual
activities**
Feeling worried
or sad**
Current health-related quality of life measured by the EQ-5D-Y1
No problems Some problems A lot of problems
Figure 1.
Current health-related quality of life measured by the EQ-5D-Y.
1
NB: The number of
participants in the PCS varies due to missing data from 91 to 92. ** Significant difference between
PCS and CLoCk sample at p< 0.001.
There was no difference between the two groups in emotional well-being as assessed
by total SDQ scores (median 12 (7–17) for PCS young people and 11 (6–15) for young people
in CLoCk (z =
−
1.8; p= 0.07)). However, SDQ impact scores were significantly higher in
PCS young people (PCS: 2 (0–5); CLoCk 0 (0-1); z =
−
7.7; p< 0.001) indicating symptoms
were having a greater impairment and causing more distress.
Additionally, 96.7% of PCS young people were ‘fatigued’ compared to 35.5% of
CLoCk young people (X2(1) = 136.9; p< 0.001). PCS young people were more likely
to report feeling lonely as indicated by UCLA-3 loneliness scores (PCS: 13.2%; CLoCk: 6.5%;
X2(1) = 6.4; p= 0.01).
3.3. Subgroup Analysis-PCS and CLoCk Delphi Young People
Of the 3065 test-positive respondents, 783 (25.6%) met the research Delphi defini-
tion of Long COVID [
4
]. As with the main CLoCk sample, Delphi young people were
predominantly Female (74.2%) and White (74.3%). There were fewer CLoCk Delphi par-
ticipants from the least deprived areas of England than in the main sample (16.45% and
20.4%, respectively). Table S5 presents the demographic characteristics of CLoCk Delphi
young people.
The majority of CLoCk Delphi young people reported no symptoms during the acute
SARS-CoV-2 phase (63.7%; median: 0; IQR: 0, 7). Symptom prevalence was highest for
headaches (30.9%), tiredness (27.7%) and sore throat (27.1%).
Children 2023,10, 1750 8 of 13
3.4. Current Symptoms
Out of the CLoCk Delphi young people, 36.0% reported experiencing 5+ symptoms
compared to 77.7% of PCS young people (X2(5) = 70.9; p< 0.001). Common symptoms
experienced by the CLoCk Delphi group were similar to those reported by PCS patients
including tiredness (77.3%), shortness of breath (52.4%) and headaches (44.1%). However,
symptom prevalence was lower in the CLoCk Delphi group than the PCS group. See
Figure 2for a comparison of symptom prevalence across PCS, CLoCk and CLoCk Delphi
young people.
Children 2023, 10, x FOR PEER REVIEW 8 of 13
The majority of CLoCk Delphi young people reported no symptoms during the acute
SARS-CoV-2 phase (63.7%; median: 0; IQR: 0, 7). Symptom prevalence was highest for
headaches (30.9%), tiredness (27.7%) and sore throat (27.1%).
3.4. Current Symptoms
Out of the CLoCk Delphi young people, 36.0% reported experiencing 5+ symptoms
compared to 77.7% of PCS young people (X2(5) = 70.9; p < 0.001). Common symptoms
experienced by the CLoCk Delphi group were similar to those reported by PCS patients
including tiredness (77.3%), shortness of breath (52.4%) and headaches (44.1%). However,
symptom prevalence was lower in the CLoCk Delphi group than the PCS group. See Fig-
ure 2 for a comparison of symptom prevalence across PCS, CLoCk and CLoCk Delphi
young people.
Figure 2. Comparison of symptom prevalence across PCS, CLoCk and CLoCk Delphi young peo-
ple. Coloured lines represent the comparison of symptom prevalence across groups.
PCS young people were more likely to report problems with daily function on mo-
bility (p < 0.001), self-care (p < 0.001), doing usual activities (X2(2) = 223.3; p < 0.001) and
pain or discomfort (X2 (2) = 80.4; p < 0.001) domains of the EQ-5D-Y compared to the
CLoCk Delphi group. However, there was no difference between the two groups for the
sad/worried domain with 77.2% of PCS young people and 74.6% of CLoCk Delphi young
people reporting ‘some problems’ or ‘a lot of problems’ (X2(2) = 3.3; p = 0.2).
SDQ impact scores remained significantly higher for PCS young people indicating
symptoms were causing greater impairment and more distress (PCS: 2 (0–5); CLoCk Del-
phi: 1(0–3); (z = −2.3; p = 0.019)).
Out of the CLoCk Delphi young people, 70.9% were ‘fatigued’ compared to 96.6% of
PCS young people (X2(1) = 26.8; p < 0.001). A similar proportion of both groups reported
feeling lonely as captured by the UCLA-3 loneliness scale PCS: 13.2%; CLoCk Delphi:
17.4%; X2(1) = 1.0; p = 0.3).
Figure 2.
Comparison of symptom prevalence across PCS, CLoCk and CLoCk Delphi young people.
Coloured lines represent the comparison of symptom prevalence across groups.
PCS young people were more likely to report problems with daily function on mobility
(p< 0.001), self-care (p< 0.001), doing usual activities (X2(2) = 223.3; p< 0.001) and pain or
discomfort (X2 (2) = 80.4; p< 0.001) domains of the EQ-5D-Y compared to the CLoCk Delphi
group. However, there was no difference between the two groups for the sad/worried
domain with 77.2% of PCS young people and 74.6% of CLoCk Delphi young people
reporting ‘some problems’ or ‘a lot of problems’ (X2(2) = 3.3; p= 0.2).
SDQ impact scores remained significantly higher for PCS young people indicating
symptoms were causing greater impairment and more distress (PCS: 2 (0–5); CLoCk Delphi:
1(0–3); (z = −2.3; p= 0.019)).
Out of the CLoCk Delphi young people, 70.9% were ‘fatigued’ compared to 96.6% of
PCS young people (X2(1) = 26.8; p< 0.001). A similar proportion of both groups reported
feeling lonely as captured by the UCLA-3 loneliness scale PCS: 13.2%; CLoCk Delphi:
17.4%; X2(1) = 1.0; p= 0.3).
4. Discussion
This is the first study to compare symptoms and characteristics between a population
sample and a sample presenting to a PCS.
This study found a number of important differences between the PCS and CLoCk
samples. Almost all PCS young people met the Delphi definition of Long COVID [
4
]
Children 2023,10, 1750 9 of 13
compared to a significantly smaller proportion of CLoCk young people. Based on IMD,
PCS young people were from less deprived areas than CLoCk young people and were more
likely to report experiencing a range of symptoms such as problems with the stomach, gut,
liver or kidneys. They were also more likely to report ‘some’ or ‘a lot’ of problems with
several areas of daily function prior to the pandemic. The majority of PCS young people
experienced 5 or more symptoms at the time of completing the questionnaire compared
to a minority of the young people in CLoCk (13.4%). Strikingly, the median number of
symptoms reported by PCS young people was 8.0 compared to 1.0 in CLoCk. Although
the same symptoms were most common in both groups including tiredness, headaches,
dizziness or light-headedness and shortness of breath, symptom prevalence was higher in
the PCS group than in CLoCk. PCS young people were significantly more likely to have a
poorer health-related quality of life with mental health symptoms having greater impact
in the PCS young people than the CLoCk sample. Almost all the PCS young people were
‘fatigued’ compared to only a third of the CLoCk sample, and they were also more likely
to report loneliness. Within the subsample of the CLoCk participants who met the Delphi
research definition of Long COVID, symptoms were similar in nature to the PCS young
people but they had far fewer of them and they were less impairing. The findings can
be summarised as showing that compared to the CLoCk young people, the PCS young
people had more symptoms, and those symptoms were more severe and having a greater
negative impact.
The findings from this study should be viewed within the context of relevant existing
literature. Systematic reviews of paediatric Long COVID and adult Long COVID typi-
cally report similar symptom profiles as to those found in the current PCS and CLoCk
samples [
1
,
27
]. However, such reviews have grouped together young people recruited from
different sources. Our finding that PCS young people experienced more symptoms that
were having a greater impact than those in CLoCk is in line with other studies detailing the
severity and long-lasting nature of symptoms experienced by patients presenting at clinics
including Pulmonary Circulation Dysfunction [
28
] and morphologic abnormalities [
29
].
The finding that PCS young people reported significantly more symptoms during the acute
COVID-19 phase than CLoCk young people, with the majority experiencing more than
5 symptoms at onset, aligns with studies in adult populations suggesting the presence of
multiple symptoms at disease onset is predictive of Long COVID [
30
–
32
]. There are many
possible explanations for this, including increased viral load. Although no specific biomark-
ers have yet been established that differentiate Long COVID from other disease entities, it
is hoped that sensitive and reliable diagnostic biomarkers will emerge which may further
help identify which children are in need of clinical interventions [
33
]. Monitoring young
people reporting multiple symptoms during infection may also enable early intervention
and support.
The high proportion of PCS young people reporting symptoms prior to the pan-
demic is congruous with research suggesting health pre-pandemic is associated with Long
COVID [
34
,
35
]. Young people experiencing poor health prior to the pandemic may find
it more challenging to function with the burden of additional symptoms. Additionally,
experiencing poor health prior to the pandemic could be indicative of a pre-existing con-
dition [
36
]. We cannot rule out the high prevalence of symptoms reported prior to the
pandemic in retrospectively describing health has led to recall bias. Moreover, chronic
non-specific symptoms have been experienced by young people in multiple studies prior
to the pandemic and may be typical for this age group. For example, fatigue has been
described in up to 40% of one cohort of young people pre-pandemic [37].
Some additional findings have important implications for clinical services, in particular,
that PCS young people were from less deprived areas than CLoCk young people. This
could be because the CLoCk sample was recruited nationally whereas the PCS young
people were attending the Pan-London service. Should the results be replicated across
different PCS services, it is important to consider methods to ensure equality of access.
Self-referral to such services may be an option to consider to reduce inequalities as has been
Children 2023,10, 1750 10 of 13
the case in other areas of health [
38
]. Self-referral may also be an opportunity to address
the data from CLoCk suggesting there is a large proportion of young people experiencing
symptoms more than 3 months after infection who are not being referred to a PCS. This
could suggest the majority of young people who meet the definition do not need specialist
care and are self-managing or being managed through local services. Alternatively, it
could indicate an unmet need and young people who require treatment are npt receiving
it. Overall, only 3.8% of young people in a study related to CLoCk but infected with the
Omicron variant reported seeing a GP for their COVID-related symptoms and less than
1% had stayed overnight due to COVID-related symptoms in the six months since the
original infection [
39
]. These findings would indicate that the former explanation i.e., the
majority of infected young people are self-managing, is the more likely one, facilitated by
programmes such as ‘your COVID recovery’ by the NHS [
40
]. However, increasing access
to services for young people with Long COVID via self-referral would ensure those in need
are able to be treated appropriately.
Limitations
This study has several limitations. The two samples completed the questionnaire
over different time periods, with some overlap in the time of infection. Samples were not
matched in terms of demographic variables and duration between the test or contracting
the virus and completing the questionnaire. This highlights challenges in comparing a
research-based sample and a clinical group where the time from symptoms to presentation
in a tertiary service is likely longer than 3 months. Long COVID was a new diagnosis when
the questionnaire was designed, and some symptoms were not yet recognised. As a result,
‘brain fog’ is not captured as a symptom in the questionnaire. This study benchmarks
a single clinic audit against data collected in a national survey and therefore cannot be
generalised to other populations. Finally, PCS young people were included if they filled in
the questionnaire, which was a self-selected group accounting for 53.0% and may infer bias.
This also applies to the CLoCk sample which reported a response of 13.3%.
5. Conclusions
This study is important as it demonstrates findings from research studies such as
CLoCk cannot simply be generalised to the young people meeting referral criteria to PCS;
while symptom profiles are similar, the number of symptoms experienced and their impact
is far higher in the clinical sample. These findings may help focus resources on those most
in need. Importantly, the focus of this study was to describe the characteristics of young
people from a PCS and compare them to young people in a national research study. Further
studies are required to determine causal associations. Additionally, research is needed that
is methodologically rigorous and that can evaluate outcomes of intervention for young
people and their families who are experiencing significant distress.
Supplementary Materials:
The following supporting information can be downloaded at: https://
www.mdpi.com/article/10.3390/children10111750/s1, Table S1: Information on measures included
in the CLoCk questionnaire and details on how they have been dichotomised; Table S2: Symptom
profile before COVID-19 pandemic in March 2020 (retrospective reports); Table S3: Symptoms during
acute COVID phase; Table S4: Current health related quality of life; Table S5: Demographics of CLoCk
Delphi CYP.
Author Contributions:
Conceptualization, F.N., A.-L.G., S.M.P.P., E.W. (Elizabeth Whittaker), E.D.,
T.C., I.H. and T.S. (Terry Segal); CLoCk Consortium, T.S. (Terence Stephenson) and R.S.; methodology,
F.N., A.-L.G., S.M.P.P., M.D.N., T.S. (Terry Segal) and R.S.; software, F.N., S.M.P.P. and M.D.N.;
validation, F.N. and M.D.N.; formal analysis, F.N.; investigation, F.N.; resources, M.J., E.W. (Emily
Whelan) and H.B.; data curation, F.N., H.B., S.M.P.P. and M.D.N.; writing—original draft preparation,
F.N., T.S. (Terence Stephenson) and R.S.; writing—review and editing, F.N., A.-L.G., M.J., H.B.,
E.W. (Emily Whelan), M.D.N., S.M.P.P., E.W. (Elizabeth Whittaker), T.C., E.D., I.H., T.S. (Terence
Stephenson), T.S. (Terry Segal) and R.S.; supervision, A.-L.G., T.C., I.H., T.S. (Terence Stephenson), T.S.
(Terry Segal) and R.S.; funding acquisition, E.D., T.C., I.H., E.W. (Elizabeth Whittaker) and T.S. (Terry
Children 2023,10, 1750 11 of 13
Segal); CLoCk Consortium, R.S. and T.S. (Terence Stephenson). All authors have read and agreed to
the published version of the manuscript.
Funding:
Funded by The Department of Health and Social Care, in their capacity as the National
Institute for Health Research (NIHR), and by UK Research & Innovation (UKRI) who have awarded
funding, grant number COVLT0022. The Department of Health and Social Care, as the NIHR, and
UKRI were not involved in study design, data collection, analysis or interpretation of the data, nor
the writing of the present study or the decision to submit the article for publication. All research
at Great Ormond Street Hospital NHS Foundation Trust and UCL Great Ormond Street Institute
of Child Health is made possible by the NIHR Great Ormond Street Hospital Biomedical Research
Centre. The views expressed are those of the authors and not necessarily those of the NHS, the
NIHR, UKRI or the Department of Health. S.M.P.P. is supported by a UK Medical Research Council
Career Development Award (ref: MR/P020372/1). F.N. is funded by a Beryl Alexander Charity Ph.D.
studentship (sponsor reference: W1168; award number: 183885).
Institutional Review Board Statement:
The CLoCk study was conducted in accordance with the
Declaration of Helsinki and approved by the Health Research Authority on 16 March 2021 (REC
reference: 21/YH/0060; IRAS project ID: 293495). Data from the Post COVID Service were analysed
as part of a service evaluation approved by the Paediatrics and Adolescent Division Quality and
Safety Lead (registered on 30/03/2023).
Informed Consent Statement:
Informed consent was obtained from all participants who partici-
pated in the CLoCk study. Data from the Post COVID service were collected as part of a service
evaluation approved by the Paediatrics and Adolescent Division Quality and Safety Lead (registered
on 30/03/2023).
Data Availability Statement:
Data are not publicly available. All requests for CLoCk data will be
reviewed by the study team to verify whether the request is subject to any intellectual property or
confidentiality obligations. Requests for access to the data from this study can be submitted via email
to Clock@phe.gov.uk with detailed proposals for approval. A signed data access agreement with the
CLoCk team is required before accessing shared data.
Acknowledgments:
Michael Lattimore, UKHSA, as Project Officer for the CLoCk study. Olivia
Swann and Elizabeth Whittaker designed the elements of the ISARIC Paediatric COVID-19 follow-up
questionnaire. The Pan-London Post-COVID research group (alphabetical): Benjamin Baig; Ronny
Cheung; Simon Drysdale; Anna Gregorowski; Jenny McClure; Nathalie McDermott; Karyn moshal;
Emma Parish; Clarissa Pilkington; Monica Samuel; Samantha Sonnappa; Michael Wacks; Deborah
Woodman. Additional co-applicants on the grant application and CLoCk Consortium members
(alphabetical): Marta Buszewicz, University College London, (Orcid ID: 0000-0003-4016-5857); Es-
ther Crawley, University of Bristol, (Orcid ID: 0000-0002-2521-0747); Bianca De Stavola, University
College London, (Orcid ID: 0000-0001-7853-0528); Shruti Garg, University of Manchester, (Orcid ID:
0000-0002-4472-4583); Dougal Hargreaves, Imperial College London, (Orcid ID: 0000-0003-0722-9847);
Anthony Harnden, Oxford University, (Orcid ID: 0000-0003-0013-9611); Michael Levin, Imperial
College London, (Orcid ID: 0000-0003-2767-6919); Vanessa Poustie, University of Liverpool (Orcid
ID: 0000-0003-2338-8768); Kishan Sharma, Manchester University NHS Foundation Trust (sadly
deceased); Elizabeth Whittaker, Imperial College London, (Orcid ID: 0000-0002-7944-8793).
Conflicts of Interest:
Terence Stephenson is Chair of the Health Research Authority and therefore
recused himself from the Research Ethics Application. Trudie Chalder has been a member of the
National Institute for Health and Care Excellence committee for long COVID-19. She has written
self-help books on chronic fatigue and has done workshops on chronic fatigue and post-infectious
syndromes. All remaining authors have no conflicts of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or
in the decision to publish the results.
References
1.
Behnood, S.A.; Shafran, R.; Bennett, S.D.; Zhang, A.X.D.; O’Mahoney, L.L.; Stephenson, T.J.; Ladhani, S.N.; De Stavola, B.L.; Viner,
R.M.; Swann, O.V. Persistent Symptoms Following SARS-CoV-2 Infection amongst Children and Young People: A Meta-Analysis
of Controlled and Uncontrolled Studies. J. Infect. 2022,84, 158–170. [CrossRef] [PubMed]
2.
Viner, R.M.; Ward, J.L.; Hudson, L.D.; Ashe, M.; Patel, S.V.; Hargreaves, D.; Whittaker, E. Systematic Review of Reviews of
Symptoms and Signs of COVID-19 in Children and Adolescents. Arch. Dis. Child. 2020,106, 802–807. [CrossRef] [PubMed]
Children 2023,10, 1750 12 of 13
3. Zachariah, P. COVID-19 in Children. Infect. Dis. Clin. 2022,36, 1–14. [CrossRef]
4.
Stephenson, T.; Allin, B.; Nugawela, M.D.; Rojas, N.; Dalrymple, E.; Pinto Pereira, S.; Soni, M.; Knight, M.; Cheung, E.Y.; Heyman,
I.; et al. Long COVID (Post-COVID-19 Condition) in Children: A Modified Delphi Process. Arch. Dis. Child.
2022
,107, 674–680.
[CrossRef]
5.
Stephenson, T.; Pereira, S.M.P.; Shafran, R.; Stavola, B.L.; de Rojas, N.; McOwat, K.; Simmons, R.; Zavala, M.; O’Mahoney, L.;
Chalder, T.; et al. Physical and Mental Health 3 Months after SARS-CoV-2 Infection (Long COVID) among Adolescents in England
(CLoCk): A National Matched Cohort Study. Lancet Child Adolesc. Health 2022,6, 230–239. [CrossRef]
6.
World Health Organization (WHO). A Clinical Case Definition for Post COVID-19 Condition in Children and Adolescents by Expert
Consensus; WHO: Geneva, Switzerland, 2023.
7.
Dobrijevi´c, D.; Katani´c, J.; Todorovi´c, M.; Vuˇckovi´c, B. Baseline Laboratory Parameters for Preliminary Diagnosis of COVID-19
among Children: A Cross-Sectional Study. São Paulo Med. J. 2022,140, 691–696. [CrossRef] [PubMed]
8.
Dobrijevi´c, D.; Andrijevi´c, L.; Anti´c, J.; Raki´c, G.; Pastor, K. Hemogram-based Decision Tree Models for Discriminating COVID-19
from RSV in Infants. J. Clin. Lab. Anal. 2023,37, e24862. [CrossRef]
9.
Baillie, J.K.; Lone, N.I.; Jones, S.; Shaw, A.; Hairsine, B.; Kurasz, C.; Henson, H.; Armstrong, L.; Shenton, L.; Dobson, H.; et al.
Multiorgan MRI Findings after Hospitalisation with COVID-19 in the UK (C-MORE): A Prospective, Multicentre, Observational
Cohort Study. Lancet Respir. Med. 2023. [CrossRef]
10.
Science News Where Are the Long COVID Clinics? 2022. Available online: https://www.sciencenews.org/article/long-covid-
clinics-map-locations-prevalence (accessed on 21 February 2023).
11. McCartney, M.; Byng, R. Long Covid Clinics Should Be Run as Research Hubs. BMJ 2021,374, n1996. [CrossRef] [PubMed]
12.
Kauhanen, L.; Wan Mohd Yunus, W.M.A.; Lempinen, L.; Peltonen, K.; Gyllenberg, D.; Mishina, K.; Gilbert, S.; Bastola, K.; Brown,
J.S.L.; Sourander, A. A Systematic Review of the Mental Health Changes of Children and Young People before and during the
COVID-19 Pandemic. Eur. Child Adolesc. Psychiatry 2023,32, 995–1013. [CrossRef]
13.
Bosworth, M.; Ayoubkhani, D.; Pawelek, P. Prevalence of Ongoing Symptoms Following Coronavirus (COVID-19) Infec-
tion in the UK—Office for National Statistics. Available online: https://www.ons.gov.uk/peoplepopulationandcommunity/
healthandsocialcare/conditionsanddiseases/bulletins/prevalenceofongoingsymptomsfollowingcoronaviruscovid19infectionintheuk/
5january2023 (accessed on 15 January 2023).
14.
Lopez-Leon, S.; Wegman-Ostrosky, T.; Ayuzo del Valle, N.C.; Perelman, C.; Sepulveda, R.; Rebolledo, P.A.; Cuapio, A.; Villapol,
S. Long-COVID in Children and Adolescents: A Systematic Review and Meta-Analyses. Sci. Rep.
2022
,12, 9950. [CrossRef]
[PubMed]
15.
Lelii, F.; Leeson, R. COVID-19 Schools Infection Survey, England: Pupil Antibody Data and Vaccine Sentiment, March to April
2022. Available online: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/
bulletins/covid19schoolsinfectionsurveyengland/pupilantibodiesandvaccinesentimentmarch2022
(accessed on 21 February 2023).
16.
Office for National Statistics Prevalence of Ongoing Symptoms Following Coronavirus (COVID-19) Infection in the UK
Statistical Bulletins 2022. Available online: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/
conditionsanddiseases/bulletins/prevalenceofongoingsymptomsfollowingcoronaviruscovid19infectionintheuk/previousReleases
(accessed on 21 February 2023).
17.
Office for National Statistics Population and Household Estimates, England and Wales: Census 2021, Unrounded Data. Available
online: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/
populationandhouseholdestimatesenglandandwales/census2021unroundeddata#cite-this-statistical-bulletin (accessed on
21 February 2023).
18.
Stephenson, T.; Shafran, R.; De Stavola, B.; Rojas, N.; Aiano, F.; Amin-Chowdhury, Z.; McOwat, K.; Simmons, R.; Zavala, M.;
Consortium, C.L.; et al. Long COVID and the Mental and Physical Health of Children and Young People: National Matched
Cohort Study Protocol (the CLoCk Study). BMJ Open 2021,11, e052838. [CrossRef] [PubMed]
19.
Sigfrid, L.; Maskell, K.; Bannister, P.G.; Ismail, S.A.; Collinson, S.; Regmi, S.; Blackmore, C.; Harriss, E.; Longuere, K.-S.; Gobat,
N.; et al. Addressing Challenges for Clinical Research Responses to Emerging Epidemics and Pandemics: A Scoping Review.
BMC Med. 2020,18, 190. [CrossRef]
20.
Ethnic Group, National Identity and Religion—Office for National Statistics. Available online: https://www.ons.gov.
uk/methodology/classificationsandstandards/measuringequality/ethnicgroupnationalidentityandreligion (accessed on 22
March 2023).
21.
Youthinmind Information for Researchers and Professionals about the Strengths & Difficulties Questionnaires. Available online:
https://www.sdqinfo.org/norms/UKSchoolNorm.html (accessed on 22 August 2023).
22.
Wille, N.; Badia, X.; Bonsel, G.; Burström, K.; Cavrini, G.; Devlin, N.; Egmar, A.-C.; Greiner, W.; Gusi, N.; Herdman, M.; et al.
Development of the EQ-5D-Y: A Child-Friendly Version of the EQ-5D. Qual. Life Res. 2010,19, 875–886. [CrossRef] [PubMed]
23.
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]
24.
Russell, D.W. UCLA Loneliness Scale (Version 3): Reliability, Validity, and Factor Structure. J. Pers. Assess.
1996
,66, 20–40.
[CrossRef] [PubMed]
25.
Ministry of Housing, Communities & Local Government English Indices of Deprivation 2015. Available online: https://www.
gov.uk/government/statistics/english-indices-of-deprivation-2015 (accessed on 1 March 2023).
Children 2023,10, 1750 13 of 13
26.
Benjamini, Y.; Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J. R.
Stat. Soc. Ser. B Methodol. 1995,57, 289–300. [CrossRef]
27.
O’Mahoney, L.L.; Routen, A.; Gillies, C.; Ekezie, W.; Welford, A.; Zhang, A.; Karamchandani, U.; Simms-Williams, N.; Cassambai,
S.; Ardavani, A.; et al. The Prevalence and Long-Term Health Effects of Long Covid among Hospitalised and Non-Hospitalised
Populations: A Systematic Review and Meta-Analysis. eClinicalMedicine 2022,55, 101762. [CrossRef]
28.
Buonsenso, D.; Di Giuda, D.; Sigfrid, L.; Pizzuto, D.A.; Di Sante, G.; De Rose, C.; Lazzareschi, I.; Sali, M.; Baldi, F.; Chieffo,
D.P.R.; et al. Evidence of Lung Perfusion Defects and Ongoing Inflammation in an Adolescent with Post-Acute Sequelae of
SARS-CoV-2 Infection. Lancet Child Adolesc. Health 2021,5, 677–680. [CrossRef]
29.
Heiss, R.; Tan, L.; Schmidt, S.; Regensburger, A.P.; Ewert, F.; Mammadova, D.; Buehler, A.; Vogel-Claussen, J.; Voskrebenzev, A.;
Rauh, M.; et al. Pulmonary Dysfunction after Pediatric COVID-19. Radiology 2023,306, e221250. [CrossRef]
30.
Righi, E.; Mirandola, M.; Mazzaferri, F.; Dossi, G.; Razzaboni, E.; Zaffagnini, A.; Ivaldi, F.; Visentin, A.; Lambertenghi, L.; Arena,
C.; et al. Determinants of Persistence of Symptoms and Impact on Physical and Mental Wellbeing in Long COVID: A Prospective
Cohort Study. J. Infect. 2022,84, 566–572. [CrossRef]
31.
Sudre, C.H.; Murray, B.; Varsavsky, T.; Graham, M.S.; Penfold, R.S.; Bowyer, R.C.; Pujol, J.C.; Klaser, K.; Antonelli, M.; Canas,
L.S.; et al. Author Correction: Attributes and Predictors of Long COVID. Nat. Med. 2021,27, 1116. [CrossRef] [PubMed]
32.
Aiyegbusi, O.L.; Hughes, S.E.; Turner, G.; Rivera, S.C.; McMullan, C.; Chandan, J.S.; Haroon, S.; Price, G.; Davies, E.H.;
Nirantharakumar, K.; et al. Symptoms, Complications and Management of Long COVID: A Review. J. R. Soc. Med.
2021
,114,
428–442. [CrossRef] [PubMed]
33.
Tsilingiris, D.; Vallianou, N.G.; Karampela, I.; Christodoulatos, G.S.; Papavasileiou, G.; Petropoulou, D.; Magkos, F.; Dalamaga, M.
Laboratory Findings and Biomarkers in Long COVID: What Do We Know So Far? Insights into Epidemiology, Pathogenesis,
Therapeutic Perspectives and Challenges. Int. J. Mol. Sci. 2023,24, 10458. [CrossRef] [PubMed]
34.
Nugawela, M.D.; Stephenson, T.; Shafran, R.; De Stavola, B.L.; Ladhani, S.N.; Simmons, R.; McOwatt, K.; Rojas, N.; Cheung, E.Y.;
Ford, T.; et al. Predictive model for long COVID in children 3 months after a SARS-CoV-2 PCR test. BMC Med
2022
,20, 465.
[CrossRef] [PubMed]
35.
Thompson, E.J.; Williams, D.M.; Walker, A.J.; Mitchell, R.E.; Niedzwiedz, C.L.; Yang, T.C.; Huggins, C.F.; Kwong, A.S.F.;
Silverwood, R.J.; Di Gessa, G.; et al. Long COVID Burden and Risk Factors in 10 UK Longitudinal Studies and Electronic Health
Records. Nat. Commun. 2022,13, 3528. [CrossRef] [PubMed]
36.
Merzon, E.; Weiss, M.; Krone, B.; Cohen, S.; Ilani, G.; Vinker, S.; Cohen-Golan, A.; Green, I.; Israel, A.; Schneider, T.; et al. Clinical
and Socio-Demographic Variables Associated with the Diagnosis of Long COVID Syndrome in Youth: A Population-Based Study.
Int. J. Environ. Res. Public. Health 2022,19, 5993. [CrossRef] [PubMed]
37.
Findlay, S.M. The Tired Teen: A Review of the Assessment and Management of the Adolescent with Sleepiness and Fatigue.
Paediatr. Child Health 2008,13, 37–42. [CrossRef]
38.
Brown, J.S.L.; Ferner, H.; Wingrove, J.; Aschan, L.; Hatch, S.L.; Hotopf, M. How Equitable Are Psychological Therapy Services in
South East London Now? A Comparison of Referrals to a New Psychological Therapy Service with Participants in a Psychiatric
Morbidity Survey in the Same London Borough. Soc. Psychiatry Psychiatr. Epidemiol. 2014,49, 1893–1902. [CrossRef]
39.
Pinto Pereira, S.M.; Mensah, A.; Nugawela, M.D.; Stephenson, T.; Ladhani, S.N.; Dalrymple, E.; Dudley, J.; McOwat, K.; Simmons,
R.; Heyman, I.; et al. Long COVID in Children and Young after Infection or Reinfection with the Omicron Variant: A Prospective
Observational Study. J. Pediatr. 2023,259, 113463. [CrossRef] [PubMed]
40.
NHS Your COVID Recovery—Supporting Recovery for Long Covid 2022. Available online: https://www.yourcovidrecovery.nhs.
uk (accessed on 29 September 2023).
Disclaimer/Publisher’s Note:
The statements, opinions and data contained in all publications are solely those of the individual
author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to
people or property resulting from any ideas, methods, instructions or products referred to in the content.
