Improving clinical assessment of asthma by studying the
relation between spirometry and assessment of EIB
‘Never judge a book by its cover’
Exercise-induced bronchoconstriction (EIB) in children
Maaike van Hoesel, 1726420
Dr. B. Thio, pediatrician
Department of Pediatrics, Medisch Spectrum Twente, Enschede
Improving clinical assessment of asthma by studying the relation between spirometry and assessment of EIB
M.H.T. van Hoesel
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Summary
English Background Exercise induced bronchoconstriction (EIB) is a highly specific symptom of
asthma in childhood and a strong sign of uncontrolled asthma. The diagnosis of EIB from a
medical history is difficult; perception of EIB by children and recognition by others can be low.
EIB can be identified with an exercise challenge test (ECT), however these tests are time-
consuming and expensive. There is a need for objective tools to diagnose EIB in asthmatic
children. Video evaluation of asthma symptoms could be a potential low-end and objective
addition for diagnosis and monitoring of EIB, improving asthma treatment, reducing cost and
increasing efficiency.
Objective The aim of this study is to investigate whether paediatricians can predict the severity
of EIB as measured with an ECT from the medical history, physical examination and pre-
exercise video, and if the addition of pre-exercise lungfunction can improve this prediction.
The second aim of this study is to investigate the relation between asthma dyspnoea scores, as
assessed by pediatricians from videos, and the severity of airway obstruction as measured with
pulmonary function.
Methods 20 asthmatic children (age 4-17 years) performed an ECT. Pulmonary function testing
was measured before and after exercise. Children with a fall of ≥ 10% in FEV1 were considered
to have EIB. A fall of <10% but >25% was considered mild, >25% but <50% moderate and
>50% or >30% if treated with inhaled corticosteroids (ICS) was considered severe EIB. Before
and after exercise video recordings were made. Pediatricians predicted the severity of EIB,
based on a pre-exercise video, medical history and physical examination, and again predicted
the severity of EIB when they were informed about the pre-exercise pulmonary function.
Further they assessed dyspnoea from a post-exercise video and their assessment was compared
with the severity of EIB as categorised above.
Results 20 children (11 male, 9 female) with a mean age of 11.6 ± 3.4 had a median fall in
FEV1 of 15.1% (1.2-65.1) after exercise. 9 children showed no EIB, 4 children showed mild, 2
children showed moderate and 5 children showed severe EIB. Pediatrician’s prediction of the
severity of EIB from the medical history, physical examination and pre-exercise video was
poor. This poor prediction was not improved when pediatricians were informed about the pre-
exercise pulmonary function. Pediatrician’s assessments of dyspnoea on post-exercise videos
correlated fairly well with the severity of EIB.
Conclusion There still seems to be a substantial need of an ECT to identify EIB. Pediatricians
have a fair ability to assess EIB from post-exercise videos. This provides opportunities to
diagnose EIB from home made post-exercise videos.
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M.H.T. van Hoesel
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Summary
Nederlands Achtergrond Inspanningsastma is een specifiek symptoom van kinderen met astma en een
duidelijk teken van ongecontroleerd astma. Diagnosestelling van inspanningsastma op basis
van anamnese en lichamelijk onderzoek is moeilijk, omdat de perceptie en herkenning zeker
bij jonge kinderen lastig is. De diagnose inspanningsastma wordt vaak gesteld met behulp van
een inspanningstest, wat een tijdrovende en dure diagnostische test is. Er is derhalve behoefte
aan objectieve metingen om de ernst van inspanningsastma in kinderen vast te stellen. Video
evaluatie zou een objectieve en kosten-effectieve toevoeging zijn aan de hedendaagse astma-
diagnostiek en zou kunnen leiden tot een verbetering van de astma zorg door en sneller
diagnostisch proces en monitoring van dagelijkse astmaklachten.
Doel Het doel van deze studie is om te onderzoeken of kinderartsen de ernst van
inspanningsastma, gemeten met een inspanningstest, kunnen voorspellen op basis van
anamnese en lichamelijk onderzoek en videos voor inspanning, en of toevoeging van een
longfunctie gemeten voor inspanning deze voorspelling kan verbeteren.
Het tweede doel van deze studie is om de relatie te onderzoek tussen astma scores, voorspeld
door kinderartsen op basis van video’s, en de ernst van de benauwdheid gemeten met
longfunctie.
Methoden 20 kinderen (4-17 jaar oud) ondergingen een inspanningstest. Voor en na inspanning
werden er longfunctie metingen verricht. Kinderen met een FEV1-daling ≥ 10% werden
beschouwd als hebbende inspanningsastma. Een daling van >10% en <25% werd als milde,
>25% en <50% als matige en >50% als ernstige benauwdheid (of >30% wanneer ze behandeld
zijn met corticosteroïden). Voor en na inspanning zijn er video’s gemaakt. Kinderartsen
voorspelden de ernst van inspanningsastma na de inspanningstest, op basis van een video voor
de inspanning, anamnese en lichamelijk onderzoek. Ook voorspelden zij de ernst van de
benauwdheid wanneer aan deze informatie de longfunctie voor inspanning werd toegevoegd.
Kinderartsen beoordeelden ook de ernst van inspanningsastma aan de hand van een video na
inspanning, welke werden vergeleken met de ernst van inspanningsastma zoals hierboven
gecategoriseerd
Resultaten 20 kinderen (11 jongens, 9 meisjes) met een gemiddelde leeftijd van 11.6 ± 3.4
lieten een gemiddelde FEV1-daling zien van 15.1% (1.2-65.1) na inspanning. 9 kinderen hadden
geen EIB, 4 kinderen een milde, 2 kinderen een matige en 5 kinderen een ernstige EIB. De
resultaten van onze studie laten zien dat de voorspelling van inspanningsastma op basis van een
video voor inspanning, anamnese en lichamelijk onderzoek slecht is. Deze slechte voorspelling
verbeterde niet wanneer een electieve longfunctie meting werd toegevoegd. Wel konden
kinderartsen redelijk de ernst van inspanningsastma inschatten wanneer een video werd
toegevoegd.
Conclusie Dit onderzoek laat zien dat met het gebruik van videomateriaal in de praktijk
voorzichtig moet worden omgegaan. Ook lijkt het nog steeds nodig te zien om een
inspanningstest te laten doen als onderdeel van de diagnostiek. Kinderartsen kunnen
inspanningsastma redelijk voorspellen aan de hand van videos na inspanning. Dit geeft
mogelijkheden in het maken van video’s in de thuissituatie. Objectieve metingen, zoals
longfunciemetingen, zouden dit verder kunnen verbeteren en de behandeling optimaliseren.
Tevens moet er meer onderzoek worden gedaan naar validatie met longfunctiemetingen.
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List of abbreviations ACQs Asthma Questionnaires
ASM Airway Smooth Muscles
BHR Bronchial Hyperreactivity
BPT Bronchial Provocation Test
(C)ACT (Childhood) Asthma Control Test a score ≤19 indicates uncontrolled
asthma CI Confidence Intervals
ECT Exercise Challenge Test
EIB Exercise Induced Bronchoconstriction
FEV1 Forced Expiratory Volume, the volume air that can be exhaled in the
first second during a forced exhalation maneuver started from the level
of the total lung capacity
FEV1% from Predicted value of forced expiratory volume in 1 s of the patient
predicted compared with the average predicted value of FEV1 in the population
for any person of similar age, sex and height
ICS Inhaled corticosteroids
LTRAs Leukotriene Receptor Antagonists
METC Medical Ethics Committee
SABAs Short-acting β2-agonist
SD Standard Deviation
QOL Quality of Life
WHO World Health Organization
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Table of contents 1. Introduction ........................................................................................................................7
1.1 Pathophysiology of EIB ................................................................................................7
1.2 Exercise induced bronchoconstriction ...........................................................................8
1.3 Diagnosis of asthma .................................................................................................... 10
1.3.1 Spirometry ............................................................................................................ 10
1.3.2 Bronchial provocation tests ................................................................................... 11
1.3.3 Questionnaires ...................................................................................................... 12
1.4 Classification of exercise induced bronchoconstriction ................................................ 12
1.5 Treatment .................................................................................................................... 12
1.5.1 Prophylactic treatment of EIB ............................................................................... 13
1.5.2 Premedication ....................................................................................................... 13
1.6 Video-analysis ............................................................................................................ 13
2.1 Research questions ...................................................................................................... 15
2.2 Hypothesis .................................................................................................................. 15
2.3 Primary outcome ......................................................................................................... 15
2.4 Secundary outcome ..................................................................................................... 15
3. Methods............................................................................................................................ 16
3.1 Study design and procedure ......................................................................................... 16
3.1.1 Design .................................................................................................................. 16
3.1.2 Procedure.............................................................................................................. 16
3.2 Study population ......................................................................................................... 16
3.2.1 Inclusion criteria ................................................................................................... 16
3.2.2 Exclusion criteria .................................................................................................. 17
3.2.3 Exclusion criteria for selection of videos ............................................................... 17
3.2.4 Exclusion criteria for subanalysis of asthma questionnaires................................... 17
3.2.5 Sample size calculation ......................................................................................... 17
3.3 Methods ...................................................................................................................... 17
3.3.1 Measurement instruments ..................................................................................... 17
3.3.2 Video material ...................................................................................................... 18
3.3.3 Questionnaires ...................................................................................................... 19
3.3.4 Randomization ...................................................................................................... 19
3.3.5 Statistical analysis ................................................................................................. 19
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4. Results .............................................................................................................................. 20
4.1 Baseline characteristics of included children ............................................................... 20
4.2 Baseline characteristics of pediatricians....................................................................... 21
4.3 Prediction of EIB by specialists ................................................................................... 21
4.4 Prediction of EIB by parents and children ................................................................... 22
4.4.1 Baseline characteristics of asthma questionnaires .................................................. 22
4.4.2. Validation of dyspnoea scores against pulmonary function .................................. 23
5. Discussion ........................................................................................................................ 27
5.1 Result analysis ............................................................................................................ 27
5.2 Strengths and limitations ............................................................................................. 27
5.3 Further research .......................................................................................................... 28
6. Conclusion ....................................................................................................................... 28
7. References ........................................................................................................................ 29
8. Appendix ....................................................................................................................... 34
8.1 CRF video study ......................................................................................................... 34
8.2 Crosstabs ..................................................................................................................... 36
8.3 Questionnaires ............................................................................................................ 39
8.4 Instruction assessment videos ...................................................................................... 42
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1. Introduction Asthma is the most common chronic disease worldwide and currently around 235 million
people are diagnosed with asthma.1 Asthma is a serious health issue that affects people from all
ages, but especially children are affected. In 2008, the prevalence of asthma in Dutch children
between 4-12 years old, was approximately 10%.2
Exercise induced bronchoconstriction (EIB) is the most common trigger for asthma. The
prevalence of EIB in the pediatric population is between 6 and 20% and it increases with the
severity of asthma.3,4,5 In children with moderate or severe asthma, prevalence is even greater.
However, research of Cabral et al. showed that the severity of EIB is not consistently related to
the severity of asthma.6 The prevalence of asthma is still increasing in most countries around
the world. When it remains uncontrolled, it can lead to severe limitations in daily life and it can
even be fatal.
Asthma is characterized by chronic airway inflammation and bronchial hyperreactivity
(BHR), which can cause reversible airway obstruction. This leads to recurrent attacks of
dyspnoea, cough and wheezing. These attacks vary in severity, time and frequency from person
to person. Frequency of symptoms can vary from a few times a week till daily. Besides physical
activity, other factors that can trigger asthma symptoms are a change in weather circumstances,
viral respiratory infections and allergen exposure.7 These stimuli can cause an increase of
responsiveness of airways, which can be partially or completely reversible.8
1.1 Pathophysiology of EIB
The pathophysiology of asthma is complex. Airway inflammation, hyperresponsiveness of
airways to different allergic and non-specific triggers and hypersecretion of mucus are the
components included in the pathophysiology.
EIB characterizes the transient narrowing of airways, which is provoked by vigorous exercise.
It is measured as the reduction of pulmonary function post-exercise. The mechanism of EIB is
still under debate, but there are two major hypothesis: the thermal hypothesis and the osmotic
hypothesis.9,10
The osmotic hypothesis proposes that EIB is the result of dehydration of the airways, caused
by evaporation of mucosal water. Dehydration causes a transient hyperosmolarity of the
tracheal surface, which could lead to release of degranulation of mast cells, airway narrowing
and constriction of airway smooth muscles (ASM).10 ASM surrounds the airway and reduces
the luminal diameter in the airways. This plays a major role in acute bronchoconstriction and
causes airflow obstruction. In asthma, ASM become more sensitive to these stimuli by repeated
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exposure, which can lead to airway hyperresponsiveness.11 A study of Smith et al. also showed
that the use of hypertonic saline stimulates airway narrowing in asthmatic subjects, which
reveals potential for EIB.12
Another hypothesis is the thermal hypothesis. The thermal hypothesis considers that airway
cooling during exercise and rapid rewarming after exercise, causes hyperemia of the bronchial
vasculature and edema of the airways after exercise, resulting in broncho-obstruction. The more
rapidly the airways rewarm, the more severe the EIB.13 A study by Stensrud et al. demonstrated
that airway cooling during exercise increases symptoms of EIB diminishing athletic
performance.14
The proposed mechanism of EIB could also be both osmotically an thermally driven. In adults
EIB can also occur without the syndrome of asthma, which is a consequence of repeated
exposure to osmotic and thermal stress. This causes injury and alterations of ASM contractile
properties by a inflammation cascade.15,16 A study of Hallstrand showed that during EIB mast
cell activation occurs and that the balance between bronchoconstricting CysLTs and histamine
and bronchodilating PGE2 is altered, which leads to injury of airway epithelium. This causes
development and progression of EIB.17 The severity of EIB depends on the severity of
inflammation, which showes that the presence of EIB indicates not well controlled asthma.
1.2 Exercise induced bronchoconstriction
Exercise induced dyspnoea is not always a sign of asthma. Symptoms can also be caused by a
lack of cardiovascular fitness, exercise-induced laryngeal obstruction, dysfunctional breathing
or other diseases. EIB is the most common cause of exercise-induced dyspnoea in children. EIB
describes acute, reversible narrowing of airways provoked by exercise and is characterized by
the same symptoms as normal asthma. 80% of asthmatic patients experience these symptoms.3
Children noted EIB as the most frustrating part of their asthma and if they could eliminate one
feature, it would be EIB.18
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Exercise comes with a lot of short and longterm benefits. It improves self-esteem, physical
conditioning, it reduces cardio-vascular diseases and obesity, it improves quality of life and it
can increase academic performance.19,20 It can also decrease the need for maintenance
medication for symptoms of asthma in asthmatic patients.21,22
But, because of EIB, children and young adults often avoid participation in sports. This can
have negative influences in psycho-motor development, cardio-vascular condition and quality
of life. Quality of life (QoL) is defined by the World Health Organization (WHO) as the
individual’s perecption of their position of life in the context of the culture and value systems
in which they live and in relation to their goals, expectations, standards and concerns.23 A study
of Merikallio et al. showed that the QoL was impaired in children with symptoms of asthma
compared to healthy children.24
Especially children and young adults are at risk of EIB, because they participate in a lot of
strenuous activities.25 Also, children are supposed to have a higher activity rate, compared to
adults, and they are also more active in environments with a higher level of pollution. Research
of Esposito et al. showed that especially children with pre-existing asthma who are exposed to
traffic-related polution have an increased risk of respiratory morbidity.26 Moreover lungs of
children are still developing and vulnerable to toxicants potentially changing pulmonary
function.
Younger children have different breathing rates and patterns. As they breathe more to their
mouth compared to adults, air will not pass the nasal-filter and higher levels of pollutants will
deposit in the respiratory tract.27 A high level of physical activity combined with their mostly
immature lungs make them more prone to inhalational toxicants. These toxicants can worsen
EIB.28
EIB can be documented as a reduction in pulmonary function after exercise.29
Bronchoconstriction develops around 2-4 minutes and reaches its maximum within 5-10
minutes post-exercise. Normally recovery of pulmonary function appears spontaneous, after 3-
till 60 minutes, but in 30% of children with EIB, it can take 45 minutes up till 3 hours.3,30
However, several studies assessing EIB during exercise discovered that EIB can also occur
during exercise. This is called breakthrough EIB and is defined as a decrease in pulmonary
function (FEV1) of 15% during exercise and occurs between 2 and 10 minutes after starting
exercise.31,32 Breakthrough EIB is a strong sign of uncontrolled asthma. The time to maximal
post-exercise bronchoconstriction varies between children and adults, but it occurs faster in
younger childen.32,33
Approximately 9% of all individuals with EIB claim to have no medical history of asthma
symptoms or allergies. In a study of Kattal et al., around 50% of children with EIB who claimed
not to have a history of asthma were responding positively to exercise tests.34 Also, severe
airway obstruction can be present in patients without symptoms. Patients who are diagnosed
with EIB could have a normal pulmonary function while resting, but while exercising they can
have a severe airway obstruction and a totally different pulmonary function outcome.3
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1.3 Diagnosis of asthma
Diagnosis of asthma is often based on
clinical features, medical history and
physical examination, wich are not
specific measurements for diagnosing
asthma.35 Variability of symptoms
during different seasons and a positive
family history of atopy and asthma are
also helpful diagnostic tools.7
Although wheezing is a specific
feature of asthma, not every child with
asthma wheezes. Previous studies have
shown a poor association between
physical appearance of dyspnoeic
children and the severity of airway obstruction.36 As respiratory symptoms occur outside of the
hospital and are mostly absent during a visit to the doctor, diagnosing asthma based on clinical
judgement is challenging.7,37
Asthma can have its onset at every age, but the majority of all asthma patients start to having
symptoms in early childhood.38,39 A study of Bergmann et al. showed that the incidence of
wheezing in young children is very high.40 Although the prevalence and incidence of asthma
in young children is high, it is one of the most difficult diseases for physicians to diagnose,
mainly due to this age group and other non-specific wheezing disorders.
Approximately 35% of children worldwide had asthmatic symptoms in their first years of
their life, which is associated with viral respiratory illnessess, but not specifically with
asthma.41,42 A study of Yunginger et al. demonstrated that in the majority of cases
distinguishment between different wheezing disorders is difficult to make.38
There is evidence that over 70% of people with asthma and 63% of people newly diagnosed
with asthma at the age of 22 years, had recurrent episodes of wheezing during their early
childhood.43 Development of the immune response in children and exposure to allergens and
infectious substances during the first few years in childhood are important factors that could
change the risk of devopment of asthma in people who are genetically susceptible.7
A study of Porsbjerg et al. showed that absence of wheezing in young children, allergic
sensitization to house dust mite and a medical history of atopy decreases the risk of developing
of asthma in adulthood.44 For children who will reveal asthma, an early diagnosis of asthma is
important. Diagnosis in early childhood will lead to early anti-inflammatory treatment, which
can lead to prevention of long-term remodelling of the airway wall in children and improvement
of prognosis of asthma in childhood and adolescence.45
1.3.1 Spirometry
Spirometry is non-invasive and objective and acknowledged as the gold standard for assessment
of asthma.46 Pulmonary function tests are frequently used as a diagnostic tool and have a big
impact in asthma classification. Clinical evaluation with anamnesis and physical examination
alone is less sensitive for assessing airway obstruction than pulmonary function measurement.
A study by Kerem et al. showed that some patients could have severe airway obstruction, which
is not suggested by clinical evaluation. If these patients would be treated after clinical
evaluation alone, they would be given undertreatment.36 This shows that diagnosis with asthma
should be confirmed with pulmonary function tests.7,47,48
It can also help prevent misclassification of the severity of asthma among pediatric patients.
A study by Holt et al. showed that one third of the treatment plans were changed after
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spirometry results.49 Especially in pre-school children physical examination alone cannot
always predict the degree of airway obstruction and pulmonary function abnormalities, which
makes additional pulmonary function testing considerable to obtain more objective information
to diagnose asthma.50
Most children over 5 years of age are
capable of performing spirometry, which
can aid to confirm a diagnosis of asthma.
But, a normal pulmonary function does not
exclude a diagnosis of asthma.51 Spirometry
measures the ventilatory function of the
lung. Besides diagnosing asthma, it can help
in following the history of disease,
demonstrate the degree of airflow limitation
and its reversibility and assess the effects of
treatment.52 Spirometry uses the maximal
forced expiratory volume in one second
(FEV1) initiated at full inspiration as a
variable to identify limitations in expiratory
airflow. Many lung diseases result in
reduced FEV1, therefore FEV1/VC ratio is
used to assess airflow limitation. Normally,
the FEV1/VC ratio is between >75-80% for
adults and >90% for children. A lower ratio
implies airflow limitation.7
EIB is defined as the maximum
percentage fall in FEV1 post-exercise
compared to baseline. Children with a fall
of ≥ 10% in FEV1 are considered to have
EIB, but a fall of 15% is also used as diagnostic for EIB.53
Particularly the degree of reversibility contributes to a diagnosis of asthma. Testing for
reversibility has high specificity and low sensitivity. Reversibility refers to changes in
symptoms, or changes in airflow limitation spontaneously or after treatment with a short-acting
bronchodilator. Reversibility of ≥ 12% from the pre-bronchodilator FEV1 value, indicates
asthma.7,54
Without pulmonary function testing the degree of asthma can be either overrated or
underestimated, which could result in suboptimal therapy.55
1.3.2 Bronchial provocation tests
Stimuli, such as exercise, hyperventilation, inhalation of histamine or metacholine leads to
BHR, which is often used to diagnose and evaluate asthma by bronchoprovocation tests (BPT).
BPTs are often used to assess BHR and they are helpful in diagnosing asthma. BPTs are divided
in two categories: ‘direct’ challenges and ‘indirect’ challenges. Direct challenges are tests in
which bronchoconstriction is induced by inhalation of metacholine or histamine. Metacholine
acts on smooth muscle receptors. Indirect challenges, such as exercise, hypertonic saline and
mannitol, act on inflammatory cells, which release pro-inflammatory mediators and cause
airflow limitation.56
Exercise is widely used as an indirect BPT to assess and diagnose EIB in patients with a
history of wheezing or breathlessnes after exercise. Exercise is also used to determine the
effectiveness of medication prescribed for prevention of EIB. A study by Carlsen et al. showed
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that children with asthma demonstrate a greater reduction in pulmonary function after exercise
compared to children with other chronic lung diseases. Besides, cold air inhalation influences
the exercise tolerance much more in ashtmatic children, which results in a larger increase of
EIB compared to children with other chronic lung diseases. Although both direct- and indirect
challenge tests are sensitive for identifying asthma, indirect challenge tests showed a higher
sensitivity and maintained the specificity for asthma.57 There is evidence that direct challenges
are inferior for confirming asthma and indirect challenges would be preferred for diagnosing
and monitoring asthma.58
1.3.3 Questionnaires
Asthma questionnaires are often used for assessment and monitoring the severity of EIB. For
assessment of EIB it is important that children and their parents adequately report on asthma
symptoms. Their observations need to be accurate, because a pediatricians rely on their
observations to make decisions about modifying therapy. A study of Panditi et al. showed that
children and parents have poor perception and report of asthma symptoms is not adequately,
which can lead to under- or overestimation of asthma severity and over- or undertreatment.59
Bacharier et al. showed that pulmonary function tests relate well to asthma severity as
assessed by medication, or a combination of symptom reports and medication requirements, but
that there’s no relationship found for symptom reports alone. This suggests a disconnection
between perception and degree of airflow obstruction.47,60
Perception of dyspnoea does not only depend on the degree of narrowing in their airways,
symptoms and drug therapy. It depends on psychological influences, such as previous
experiences and in case of children, the opinion of their parents.61 Poor perception could also
be associated with a low level of fear and adaptation to asthma resulting of a long-standig
airway obstruction.62 Children with a long history of asthma are less likely to complain about
dyspnoea compared to children with acute symptoms of asthma. This may result presentations
with hypoxia during an exacerbation, which could lead to severe or life threatening asthma
attacks.63 Adequate reporting of asthma enables pediatricians to evaluate the severity of asthma
and asthma control and prevent these life threatening events.
1.4 Classification of exercise induced bronchoconstriction
Classification of asthma is useful in determining treatment in patients, which divides between
mild, moderate en severe, based on airflow limitation and pulmonary function variability. The
severity of EIB is expressed as the maximum percentage reduction in FEV1 after exercise.64
Table 1. Classification of severity of EIB. Adapted from Anderson et al.63
Degree of severity of EIB Maximum fall in FEV1 after exercise (%)
No EIB <10%
Mild EIB >10% but <25%
Moderate EIB >25% but <50%
Severe EIB >50% for steroid-naïve patients
>30% for steroid-naïve patients
1.5 Treatment
EIB is a sign of uncontrolled asthma. The goal of treatment of EIB is to achieve control of
asthma, minimize exacerbations and most of all preventing children from avoiding exercise.
Optimal treatment of asthma is important for children to participate in sports and other physical
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activities.4 It is very important that symptoms of EIB are recognized, because EIB can be treated
very effectively and with maintenance medication even be prevented.21
Non-pharmalogical measures, such as physical activity, are important in achieving
rehabilitation.4 Many asthmatic atheletes have succeeded in sports, demonstrating that having
asthma does not limit participation in sports and physical training can improve cardiopulmonary
fitness. But medical supervision is neccesary for monitoring ashtma and adjustment of
treatment, when needed.21,65
Non-pharmalogical measures are a warm up and cooling down prior and after exercise and
reducing loss of water and heat for example by wearing a scarf before the nose.48,66
Besides non-pharmalogical measures, pharmacological interventions can be considered. For
pharmacological treatment there are two main paths: prophylactic treatment and premedication.
1.5.1 Prophylactic treatment of EIB
Presentation with EIB indicates inflammation of the airways. Anti-inflammatory treatment by
inhaled corticosteroids (ICS) is the most important and effective treatment in managing EIB.
Jonasson et al. found that daily treatment with ICS provided significant protection against EIB
and improvement in airway hyperresponsiveness. It also reduced other symptoms during the
treatment and improvement in severity of asthma symptoms.67,68 A study of Waalkens et al.
showed that EIB improved after 1 week of treatment with ICS, but 3-4 weeks of treatment were
necessary to improve pulmonary function. Long-term treatment with ICS reduced the
prevalence by 33% and the severity by 50%. Still, around 50% of patients who were treated
with ICS for 2 months and supposingly controlled asthma exhibit EIB while exercising.69
When ICS are not effective enough, there are 3 options for anti-inflammatory treatment:
leukotriene antagonists (LTRA), nasal corticosteroids (NCS) or increasing the use of ICS. The
step-up therapy that is mostly used, are LTRA’s.70 Leff et al. showed that LTRA provided a
significant protection against EIB compared with placebo treatment over a 12-week period.71
1.5.2 Premedication
The preferred group of pre-medication are short-acting β2-agonists (SABA), but this is not
feasible in kids as they usually have multiple exercise bouts on a daily base and this would lead
to over consumption of SABA’s.7,70 Ineffectiveeness of SABA’s suggests another cause of
exercise induced dyspnoea, such as dysfunctional breathing or reduced cardiovascular fitness.
1.6 Video-analysis
Diagnosis and monitoring of asthma in the clinical practice depends on adequate perception of
symptoms by children and parents, anamnesis and physical examination. Those measurements
are not specific nor sensitive in diagnosing asthma. Also elective pulmonary function testing is
not informative. As normal pulmonary function tests have low diagnostic sensitivity.70
Pulmonary function tests which make use of a bronchial provocative stimulus are an exemption.
In this type of test, a bronchial provocative stimulus induces bronchial obstruction, which gives
an objective measurement of bronchial hyper-reactivity. A specific stimulus for provocation of
asthma in children is exercise, however exercise challenge tests can only be executed according
to guidelines specialized facilities.
Frequency and content of monitoring of children with asthma is based on the presence of
symptoms, exacerbations, use of corticosteroids or antibiotics, school absence, compliance,
inhalation technique, asthma symptom scores and more. Suboptimal treatment leads to frequent
and costly emergency visits to the doctor.70
Moreover, research by Bekhof et al. showed that there is a poor inter-observer reliability of
clinical dyspnoea assessment in children and there are limits to its usefulness in clinical practice
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and research. Therefore, there is a need for low-cost and objective measurements to assess
severity of symptoms in asthmatic children. Not only to improve diagnostic process, but also
to enhance self-management.72
A study of Wolf et al. stated that education of parents and children with asthma (targeted at
improved self-management) may lead to better pulmonary functions, than usual care and that
there's a desirability of including self-management education consisting of prevention and
attack management into routine asthma care for children.73
Evaluation of asthma symptoms in a home setting could lead to better insight in presence of
symptoms, severity and control of asthma symptoms in children. Video evaluation of asthma
symptoms could be a potential low-end and objective addition to the clinical practice of asthma,
which could lead to improvement of the diagnostic process and monitoring of asthma in order
to optimalize treatment, reduce cost and increase efficiency.
In order to use videos in a home setting, it has to be investigated if and how well specialists
can assess dyspnoea on video material. By making video recordings of children before and
after ECTs, the relationship between assesment of dyspnoea by specialist based on videos and
pulmonary function can be explored in an experimental setting.
The aim of this study is to investigate whether paediatricians can predict the severity of EIB
as measured with an ECT from the medical history, physical examination and pre-exercise
video, and if the addition of pre-exercise lungfunction can improve this prediction.
The second aim of this study is to investigate the relation between asthma dyspnoea scores, as
assessed by pediatricians from videos, and the severity of airway obstruction as measured with
pulmonary function.
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2. Problem definition
2.1 Research questions
1. Can specialists predict the severity of EIB based on video recordings?
1.1 Can physicians recognise asthma symptoms based on post-exercise videos?
1.2 Can spirometry after an ECT improve the the prediction of EIB?
1.3 Can parents and children recognise asthma symptoms?
2.2 Hypothesis
We hypothesize that prediction of dyspnoea from videos are not related to asthma scores of
physicians. We also hypothesize results of spirometry will not improve prediction and
management of asthma.
2.3 Primary outcome
To study the reliability of assessment of airway obstruction by specialists;
To compare the relation between prediction of EIB by specialists, pulmonary function
results and pre- and post-exercise videos;
We consider comparison between the prediction of specialists, video-analysis and pulmonary
function tests as an objective addition to the clinical practice of asthma.
2.4 Secundary outcome
To study the relation between asthma symptoms, spirometry and the VAS dyspnea score
filled in by the subjects (children) and their parents before and after the ECT.
We encounter patient- and parent-recorded findings as a valuable secondary study-endpoint,
because how a patient or parent perceive the severity of asthma and the level of control, is of
great importance for the ability to self-manage the asthma.
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3. Methods 3.1 Study design and procedure
3.1.1 Design
We performed a cross-sectional study to investigate the relation between asthma dyspnoea
scores, as assessed by pediatricians from videos, and the severity of airway obstruction as
measured with pulmonary function.
3.1.2 Procedure
The child’s medical history, anamnesis, need or use of medication and physical examination
were performed in a standardised way (appendix 8.1). Exercise challenge test were completed
as a part of the routine evaluation of asthma, with the addition of recording the patients before
and after the ECT. Before and after exercise spirometry was performed. No short- or
longacting bronchodilators were used 24 hours before testing.
Pre- and post-exercise videos were made from the patient’s head and upperchest, recorded on
an ipad before and after ECT (2x20 seconds). The pre-and post-exercise videos included
recording of sound. These videos were edited in short fragments before and after exercise and
assessed by pediatricians.
The (selected) children followed the procedure below:
Anamnesis with pediatrician/ investigator about medical history, symptoms and treatment;
Anthropometric measurements (height, weight);
Pulmonary auscultation;
An ECT, which either consisted of running on a treadmill or jumping on a jumping castle
for 6 minutes;
Pulmonary function measurements before (duplicated), during and after exercise at t=1, 3,
6, 9, 12 and 15 minutes;
Recording videos 20 seconds before and after ECT.
3.2 Study population
Approximately 39 children, aged 4 to 17 years, were consecutively recruited from the
outpatient clinic of the pediatric department of the Medisch Spectrum Twente in the period of
May 2015 to July 2015. These children must have a pediatrician diagnosed asthma and be
referred to a specialized centre for a bronchial challenge test, or, children must be suspected
of having asthma and referred to an exercise challenge test as part of the diagnostic workup.
These videos were assessed by pediatricians of 4 different hospitals (Medisch Spectrum
Twente, Isala Klinieken Zwolle, ZGT Almelo and ZGT Hengelo).
This study was approved the Medical Ethics Committee of Medisch Spectrum Twente (METC),
Enschede. All children and parents/guardians received written patient information, and signed
an informed consent form before acceptance in the study.
3.2.1 Inclusion criteria
- Clinical history of asthma or suspected of having asthma;
- Age between 4-17 years;
- Ability to perform reproducible pulmonary function tests, i.e. coefficient of the
predicted value variation in 3 of 5 consecutive measurements < 5%.
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3.2.2 Exclusion criteria
- Airflow limitiation in baseline spirometry (forced expiratory volume in the first
second (FEV1), <60% of predicted);74,75
- Spirometry induced bronchoconstriction;
- Use of short- or longacting bronchodilators <24 hours before testing.
3.2.3 Extra exclusion criteria for selection of videos
- Less than ½ of the chest visible on pre- or postexercise video
- Fully dressed children before and after ECT
- Speaking less than one sentence before or after ECT
3.2.4 Exclusion criteria for subanalysis of asthma questionnaires
- Missing pre-FEV1 or post-FEV1
- Non-independent assessment of dyspnoea by parent or child
3.2.5 Sample size calculation
In our study 39 children were consecutively enrolled. After inclusion of the participants, 20
participants were included in our study. Every case was assessed independently by five
different pediatricians. To assess every case five times, we calculated that we needed 20
pediatricians.
3.3 Methods
3.3.1 Measurement instruments
3.3.1.1 Excercise challenge test
All ECT’s were performed in a climate chamber at ZGT Hengelo, the Netherlands. Cold and
dry air was obtained during ECT with a temperature of 10.0-12.0°C. During the study ECT
was performed following standard protocol.53
Children aged 10-17 years performed the ECT on a treadmill (H/P-Cosmos Quasar 4.0) for 6
minutes with a submaximal exercise load and their nose clipped.48 The inclination of the
treadmill was 10%. The speed of the treadmill was accelerated until a steady-state heart rate
was achieved of at least 180 beats per minute. The heartrate was continuously measured by a
radiographic ECG-device (Custo cardio 100 BT).
Children aged 4-9 years old performed the ECT by jumping on a jumping castle for 6 minutes.
Van Leeuwen et al, showed that an age-adjusted ECT is preferable in younger children and
using a jumping castle is a feasible method to assess and diagnose EIB.32,76
3.3.1.3 Spirometry
Pulmonary function was measured by using standard pulmonary function tests before
(baseline), after exercise and after inhalation of salbutamol. We used a MicroLoop® MK 8
hand-held spirometer (ML3535). Baseline spirometry was performed in duplicate.48 After
exercise the expiratory flow volume curves were replicated twice. Maximal effort was
enhanced by visual incentives. The children were seated while performing spirometry.75 At
least three acceptable pulmonary function measurements were obtained, with less than 5%
variability between the three measurements.74,75
During spirometry FEV1 was measured. Spirometry was performed before exercise, after 1
minute, and 3, 6, 9, 12 and 15 minutes after cessation of exercise. After 15 minutes
bronchodilator therapy was administered and 5 minutes after inhalation, spirometry was
performed to measure reversibility. When patients experienced severe bronchoconstriction or a
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fall of ≥ 60% in FEV1 post-exercise before completing the protocol, bronchodilator therapy
with SABA was administered to reverse bronchoconstriction. Children with a fall of ≥ 10% in
FEV1 post-exercise were considered to have EIB.
Maximum fall in FEV1 after exercise challenge test was calculated by:
3.3.2 Video material
We used an iPad mini attached to a tripod in the consultation room, where the consultation and
pulmonary function measurements took place. The optimal settings for recording were
examined and the main goal was to have video-material of the children’s upper chest and head.
Video-recordings were made during consultation to for an overall view of the child. Pre- and
post-exercise a 20 second video was made in the same setting, but with the child’s face straight
into the camera. Below in figure 5 an overview of the camera position.
3.3.2.1 Assessment of video recordings
We used a panel of pediatricians in different hospitals for assessment of the videos. The
recorded video material of all cases of children with dyspnoea were randomised and assigned
to different pediatricians. Every case was assessed independently by five different pediatricians.
Before assessment they were given verbal and written instructions.
Each pediatrician scored the videos on different features of airway obstruction; wheezing,
prolonged expirium, nasal flaring, jugular retractions and supraclavicular retractions. These
features weren chosen based on previous literature and graded as a binary variable (present or
absent).77 The pediatricians were also asked to give an prediction of the severity of EIB based
on the classification of EIB (table 1) and on a Likert scale ranging from no EIB to very severe
EIB (0 to 10).
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The (selected) pediatricians followed the procedure
below (Figure 6.)
Predicting classification of EIB, features of
dyspnoea and likert scale based on medical history,
physical examination and a pre-exercise video;
Predicting classification of EIB and likert scale
based on the addition of baseline spirometry before
exercise;
Predicting classification of EIB, features of
dyspnoea and likert scale based on a post-exercise
video.
3.3.3 Questionnaires
Asthma control questionnaires, such as (Childhood)
Asthma Control Test (C-ACT)78,79, Asthma Control
Test (ACT) and the VAS-score, are widely used and
validated questionnaires to complement assessment of
asthma control.7 The C-ACT is designed for children
aged 4-11 years old, which consists of 7 question for
either child or parent. There were 4 questions for the
child, scoring 0-3, and 3 for the parent, scoring 1-5.
Scores of the questions were summed, ranging 3-27. A C-ACT-score of ≤19 indicates poor
asthma control.
The ACT is designed for children older than 12 years, which consists of 5 questions, scoring 1-
5. Scores of the questions were summed, ranging 5-25. An ACT-score of ≤19 indicates poor
asthma control. Children and parents filled out both questionnaires in Dutch and before the start
of the ECT. The VAS score was filled out before exercise, 2 minutes after exercise and 6
minutes after bronchodilator therapy.
3.3.4 Randomization
Every case was allocated five times to five different pediatricians. When a case was allocated
five time, it could not be selected anymore. The randomization list was designed with the aid
of a computerized randomization method using SPSS® version 22.0 analytical software.
3.3.5 Statistical analysis
Results were expressed as mean values ± standard deviations (SD) for normally distributed
data, as median (minimum;maximum) for non-normally distributed data, or as numbers with
correpsonding percentages if nominal or ordinal. For the measure of concordance between the
prediction of classification of EIB before ECT, baseline pulmonary function and after ECT, and
the validated classification of EIB by pulmonary function, we calculated a weighted Cohen’s
kappa. Cohen’s kappa values were classified as following: <0, poor; 0-0.2, slight; 0.2-0.4, fair;
0.4-0.6, moderate; 0.6-0.8, substantial; 0.8-1.0, almost perfect.80 To assess the difference of two
correlated proportions a McNemar test was used. For our subanalysis, correlations were
calculated with Pearson’s correlation coefficient for normally distributed continuous variables,
or with Spearman’s rho for non-normally distributed continuous variables. A two-sided p-value
of less than 0.01 was considered statistically significant. All data analyses were performed with
SPSS® Statistics, version 22.0.
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4. Results 4.1 Baseline characteristics of included children
Thirty-nine children participated in this study. They performed an ECT in dry and cold air and
videos were taken before and after exercise. They also performed spirometry before and after
exercise. Three children were excluded because of spirometry-induced bronchoconstriction and
one child had taken salbutamol <24h before the ECT. With fifteen children we were not able to
make usefull videos. Twenty children (11 male) with a mean age of 11.6 ± 3.4 were included
in the analysis. The baseline characteristics of the included patients were shown in table 2. Table 2. Baseline characteristics of included children
Characteristics Value
Number of children 20 Age (years) 11.6 ± 3.4
Male 11 (55.0)
Treadmill 17 (85.0) Height (cm) 155.1 ± 19.2
Weight (kg) 49.1 ± 21.7
BMI (kg/m2) 19.4 ± 4.7
Allergy* 11 (55.0) Exercise induced symptoms 8 (40.0)
Medication use:
SABA 13 (65.0)
ICS 10 (50.0) LABA 2 (10.0)
LTRA 6 (30.0) NCS 5 (25.0)
Baseline FEV₁ (% predicted) 92.7 ± 13.9
Maximum decrease in FEV₁ (%) 15.1 (1.2;65.1)
Classification
No EIB (<10%) 9 (45.0)
Mild EIB (10-25%) 4 (20.0)
Moderate EIB (25-50%) 2 (10.0)
Severe EIB (>50%) or if ICS (> 30%) 5 (25.0)
Reversibility (%) 18.9 (-11.0;62.3)
Results expressed as medians (minimums;maximums), mean values ± SDs, or numbers (percentages). SABA,
short-acting β2-agonist; LABA, long-acting β2-agonist; ICS, inhaled corticosteroid; NCS, nasal corticosteroid;
LTRA, leukotriene receptor antagonist; EIB, exercise induced bronchoconstriction; FEV1, forced expiratory
volume in 1 second; *allergy screening in 11 of 38 children.
The included children showed a mean baseline FEV1 of 92.7% (±13.9) and a median fall in
FEV1 of 15.1% (1.2-65.1). Eleven children (6 male, 5 female) showed EIB (decrease in FEV1
of >10% from baseline). Four children showed mild, two children moderate and five children
showed severe EIB.
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4.2 Baseline characteristics of pediatricians
Twenty pediatricians were selected to assess pre- and postvideos of children with dyspnoea.
Two pediatricians were subspecialized in pediatrician-pulmonologist. Their years of experience
have a mean of 14.4 years (±9.8). There baseline characteristics were shown in table 3.
Results expressed as medians (minimums;maximums), mean values ± SDs, or numbers (percentages).
4.3 Prediction of EIB by specialists
We included and video-recorded 20 children. Each child had two videos, one before and one
after an ECT. Every child was randomly assigned five times to a different pediatrician. Every
pediatrician viewed videos of five children, resulting in 100 assessments. Characteristics of the
included children are listed in table 2. The included children showed a mean baseline FEV1 of
92.7% (±13.9) and a median fall in FEV1 of 15.1% (1.2-65.1) after exercise (table 3). Children
were categorised in a classification model (table 1) and showed no, mild, moderate or severe
EIB (table 2). Pediatricians predicted in which classification children were after a 6-minute
ECT.
Table 4 shows the agreement between the predicted classifications. Agreement between
predicted classification of pre-exercise videos and predicted classification of pre-pulmonary
function was substantial (Kappa = 0.70 (95% CI 0.58-0.81)). Agreement between predicted
classification of pre-pulmonary function and predicted classification of post-exercise videos
was fair (Kappa = 0.39 (95% CI 0.25-0.52)). Agreement between predicted classification of
pre-exercise videos and predicted classification of post-exercise videos was slight to fair (Kappa
= 0.20 (95% CI 0.06-0.34)). Agreement between predicted classification of pre-exercise videos
and the classification validated with pulmonary function was slight (Kappa = 0.05 (95% CI
0.00-0.17)). Agreement between predicted classification of pre-pulmonary function and the
classification validated with pulmonary function was slight (Kappa = 0.19 (95% CI 0.06-0.32)).
Agreement between predicted classification of post-exercise videos and the classification
validated with pulmonary function was fair (Kappa = 0.36 (95% CI 0.23-0.48)).
Table 3. Baseline characteristics of pediatricians
Characteristics Value
Number of specialists 20
Years of experience 14.4 (±9.8)
Pediatrician-pulmonologist 2 (10.0)
Table 4. Agreement between predicted classifications
Kappa* (95% CI) Approx. Sig.
Classification Pre * classification PreLf 0.70 (0.58-0.81) P < 0.001
Classification PreLf * classification Post 0.39 (0.25-0.52) P < 0.001
Classification Pre * classification Post 0.20 (0.06-0.34) P = 0.128
Classification Pre * classification validated 0.05 (0.00-0.17) P = 0.400
Classification PreLf * classification validated 0.19 (0.06-0.32) P = 0.005
Classification Post * classification validated 0.36 (0.23-0.48) P < 0.001
* Weighted Cohen’s kappa; CI, confidence interval.
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Pediatrician’s prediction of the severity of EIB from the medical history, physical examination
and pre-exercise video was poor. This poor prediction was not improved when pediatricians
were informed about the pre-exercise pulmonary function. Pediatrician’s assessments of
dyspnoea on post-exercise videos correlated fairly well with the severity of EIB.
4.4 Prediction of EIB by parents and children
4.4.1 Baseline characteristics of asthma questionnaires
For this sub-analysis forty-seven children were enrolled. Nine children were excluded because
of missing pre-FEV1 or post-FEV1. One child was excluded because of non-independent
completion of the questionnaires. Thirty-eight children were included for analysis. The baseline
characteristics of these patients were shown in table 2.
Table 7. Baseline characteristics of asthma questionnaires ((C)-ACT and VAS-scores)
Characteristics Value
Number of children 38
Age (years) 10.8 ± 3.3
Male 22 (57.9)
(C)-ACT score 19 (10;27)
PreVASscore Child 1.4 ± 1.8
PostVASscore Child 5.1 ± 3.1
PreVASscore Parent 1.1 ± 1.4
PostVASscore Parent 4.1 ± 2.6
Results expressed as medians (minimums;maximums), mean values ± SDs, or numbers (percentages). (C)ACT, (childhod) asthma control test; VAS, visual analogue scale.
Table 5. Agreement of concordance
McNemar-Bowker Asymp. Sig. (2-sided)
Classification Pre * classification PreLf 7.571 P = 0.181
Classification PreLf * classification Post 6.733 P = 0.241
Classification Pre * classification Post 4.333 P = 0.502
Classification Pre * classification validated 38.734 P < 0.001
Classification PreLf * classification validated 35.876 P < 0.001
Classification Post * classification validated 29.591 P < 0.001
Table 6. Prevalence of dyspnoea features
100 assessments Prevalence
Wheezing (pre-video) 2.0%
Wheezing (post-video) 15.0%
Prolonged expirium (pre-video) 9.0%
Prolonged expirium (post-video) 49.0%
Nasal flaring (pre-video) 2.0%
Nasal flaring (post-video) 22.0%
Jugular retractions (pre-video) 16.0%
Jugular retractions (post-video) 56.0%
Supraclavicular retractions (pre-video) 8.0%
Supraclavicular retractions (post-video) 47.0%
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The pre-VAS scores of the included children showed a mean score of 1.4 (±1.8). The post-VAS
scores showed a mean score of 5.1 (±3.1). The pre-VASscores of the parents showed a mean
score of 1.1 (±1.4). The post-VAS scores showed a mean score of 4.1 (±2.6).
4.4.2. Validation of dyspnoea scores against pulmonary function
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When plotting the postVASscoreChild against the postVASscoreParent, a significant
correlation was found (Spearman’s rho 0,738; p = 0.000). When plotting the
postVASscoreChild against the post-FEV1, no correlation was found (Spearman’s rho -0,238;
p = 0.151). When plotting the postVASscoreParent against the post-FEV1, no correlation was
found (Spearman’s rho -0,276; p = 0.099).
Table 8. Correlation between dyspnoea scores before exercise and baseline pulmonary function
PreVASscore
Child
PreVASscore
Parent
PreFEV1
(baseline)
Spearman's rho PreVASscore
Child
Correlation Coefficient 1,000 ,500** -,133
Sig. (2-tailed) . ,001 ,427
N 38 38 38
PreVASscore
Parent
Correlation Coefficient ,500** 1,000 -,299
Sig. (2-tailed) ,001 . ,068
N 38 38 38
PreFEV1 Correlation Coefficient -,133 -,299 1,000
Sig. (2-tailed) ,427 ,068 .
N 38 38 38
**. Correlation is significant at the 0.01 level (2-tailed).
When plotting the preVASscoreChild against the preVASscoreParent, a significant
correlation was found (Spearman’s rho 0,500; p = 0.001). When plotting the
preVASscoreChild against the baseline FEV1, no correlation was found (Spearman’s rho -
0,133; p = 0.427). When plotting the preVASscoreParent against the baseline FEV1, no
correlation was found (Spearman’s rho -0,299; p = 0.068).
Table 9. Correlation between dyspnoea scores after exercise and pulmonary function after exercise
PostVASscore
Child
PostVASscore
Parent
PostFEV1
Spearman's rho PostVASscore
Child
Correlation Coefficient 1,000 ,738** -,238
Sig. (2-tailed) . ,000 ,151
N 38 37 38
PostVASscore
Parent
Correlation Coefficient ,738** 1,000 -,276
Sig. (2-tailed) ,000 . ,099
N 37 37 37
PostFEV1 Correlation Coefficient -,238 -,276 1,000
Sig. (2-tailed) ,151 ,099 .
N 38 37 38
**. Correlation is significant at the 0.01 level (2-tailed).
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5. Discussion 5.1 Result analysis
The results of our study show that pediatrician’s prediction of the severity of EIB from the
medical history, physical examination and pre-exercise video was poor. This poor prediction
was not improved when pediatricians were informed about the pre-exercise pulmonary
function. Pediatrician’s assessments of dyspnoea on post-exercise videos correlated fairly well
with the severity of EIB. These results implicate that an ECT is a valuable tool to identify EIB
and that videos of children after exercise may be a future tool to diagnose and monitor EIB.
To our knowledge, this is the first study using videomaterial of asthmatic children
performing an ECT and relating pediatrician’s assessments of video’s with EIB as measured
with pulmonary function.
Our results implicate that exercise challenge tests are still needed to identify EIB and are
therefore a useful tool in diagnostics of asthma. The diagnosis of EIB from a medical history is
difficult; perception of EIB by children and recognition by others can be low.36,60 Moreover
Bekhof et al. showed that there’s a poor inter- and intraobserver variability in clinical dyspnoea
assessment and that use of more objective parameters should be taken into account in the
diagnostic process.72 Holt et al. also showed that one third of the treatment plans are changed
after pulmonary function tests.49 Pulmonary function tests could give a more reliable
assessment of dyspnoeic children.
Our study show that the addition of a pre-exercise pulmonary function did not improve the
ability of pediatricians to predict EIB compared to the prediction of EIB based on pre-exercise
videos, medical history and physical examination. This is consistent with previous literature
showing that elective pulmonary function testing is not sensitive and useful mostly during
symptoms.70 But a normal pulmonary function does not always exclude asthma, because
children who are diagnosed with asthma could have a normal pulmonary function before
exercise and a totally different pulmonary function after exercise.3
Our results show that there is no significant relation between assessment of EIB from VAS
scores of both children and parents compared to the severity of EIB as measured by pulmonary
function. This is in line with previous literature that showed that both children and parents have
a poor perception of the severity of dyspnoea.60,81 This disconnection could be the result of
adaptation to severe asthma and a longterm airway obstruction.62 Van Leeuwen et al. also found
that there was no difference in asthma scores between children with or without EIB, which
confirms our results and there is great caution needed with interpretation of these scores.32
5.2 Strengths and limitations
The major strengths of this study include the use of spirometry results. Pulmonary function
testing is acknowledged as the gold standard for assessment of asthma and it is non-invasive
and objective.46 Besides an objective measurement of the severity of asthma, it can assess the
effects of treatment. Recently, Bekhof et al. described that no dyspnoea scoring system has
been sufficiently validated against pulmonary function and that there’s a need for further
validation of scoring systems.77 Eventhough, there are studies which report validation of
scoring systems against pulmonary function82, there has never been assessment of dyspnoea
on videos with validation against pulmonary function, which makes this study unique.
Also, all ECTs were performed in a standardized ‘climate room’, which simulates the air
condition in the Netherlands in the winter, where most patients experience symptoms of EIB.
ECTs mimic real life circumstances in which periods of airway obstruction can be provoked.
The before- and after ECT video recordings provide pediatricians insight in symptoms, which
are mostly absent during elective doctor visits.
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Another strength is that child- and parent-assessed EIB both are validated against pulmonary
function. Current literature included a validated assessment of the child’s symptom scores, but
lacked validated parent-assesed dyspnoea scores.83
We acknowledge the following limitations in our study. First, the use of videomaterial has
its limitations. The length of the videos were relatively short (30 sec-1minute), which could
have lead to missed observations and less accurate detection of subtle signs of dyspnoea. For
our study purpose, to find a more low-cost measurements to use in a home setting, video
recordings were the only practical method.
Also, assessment of EIB was based on different scoring systems, which included different
characteristics of dyspnoea.77 During recording of the videos we did not expose the whole chest,
which also could have led to less accurate assessment and prediction of the severity of EIB. In
experimental setting you can create these perfect circumstances, but our purpose was to use
video recordings in a home setting, were these circumstances cannot always be realized.
Thirdly, the lack of chest auscultation after the ECT could also be recognized as a limitation.
A few specialists reported that they could not assess EIB without chest auscultation, because
chest auscultation in dyspnoeic children helps the pediatrician to detect lower airway
obstruction. Chest auscultation is mostly used in clinical practice. However, our study
investigates prediction of EIB in videos for the purpose of usefulness in a home setting, where
no chest auscultation is possible. But although chest auscultation is very subjective and requires
specific skills, it can be argued that the degree of EIB can only be assessed with chest
auscultation.
Classification of EIB based on decrease in FEV1 was used to validate prediction of EIB by
pediatricians. Pediatricians are not used to estimate the degree of EIB and the dyspnoea scoring
system was judged impractical to use for prediction, which could lead to a less reliable
prediction. Our results also suggest that the use of classification of EIB by pulmonary function
as validation instrument is not suitable for the use in clinical practice.
5.3 Further research
Pediatricians were fairly capable of identifying severity of EIB from videos of children with
EIB. This provides opportunities to diagnose EIB outside the hospital where symptoms of EIB
occur. Future research should investigate the feasibility and validity of home videos of children
with putative symptoms of EIB. This may reduce the need for expensive hospital based ECTs.
Furthermore measuring VAS scores of children and parents during ECTs can identify children
poor perception and parents with poor recognition of EIB. Videos of symptomatic children can
show these parents (subtle) signals of EIB of their child preventing patient related delay in
treatment. Future research could investigate this potential reduction in delayed treatment.
6. Conclusion In conclusion, as prediction of EIB from medical history, physical examination and lung
function is poor ECTs are still needed to identify EIB. Pediatricians have a fair ability to assess
EIB from post-exercise videos, providing opportunities to diagnose EIB from home made post-
exercise videos. Our results also show that average perception of children and parents of the
severity of EIB is poor. Individual assessment of perception could identify asthmatic children
at risk for patient related delay in therapy.
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Page 29
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8. Appendix 8.1 CRF video study
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8.2 Crosstabs
Table 10. Crosstabs Classification Pre compared with Classification_PreLf
Classification_PreLf
Total 1 2 3 4
Classification_Pre 1 Count 18 2 1 0 21
% within Classification_Pre 85,7% 9,5% 4,8% 0,0% 100,0%
% within Classification_PreLf 90,0% 4,7% 3,3% 0,0% 21,0%
2 Count 2 37 10 2 51
% within Classification_Pre 3,9% 72,5% 19,6% 3,9% 100,0%
% within Classification_PreLf 10,0% 86,0% 33,3% 28,6% 51,0%
3 Count 0 4 19 2 25
% within Classification_Pre 0,0% 16,0% 76,0% 8,0% 100,0%
% within Classification_PreLf 0,0% 9,3% 63,3% 28,6% 25,0%
4 Count 0 0 0 3 3
% within Classification_Pre 0,0% 0,0% 0,0% 100,0% 100,0%
% within Classification_PreLf 0,0% 0,0% 0,0% 42,9% 3,0%
Total Count 20 43 30 7 100
% within Classification_Pre 20,0% 43,0% 30,0% 7,0% 100,0%
% within Classification_PreLf 100,0% 100,0% 100,0% 100,0% 100,0%
Table 11. Corsstabs Classification_PreLf compared to Classification_Post
Classification_Post
Total 1 2 3 4
Classification_PreLf 1 Count 13 6 1 0 20
% within Classification_PreLf 65,0% 30,0% 5,0% 0,0% 100,0%
% within Classification_Post 43,3% 14,3% 4,5% 0,0% 20,0%
2 Count 14 21 7 1 43
% within Classification_PreLf 32,6% 48,8% 16,3% 2,3% 100,0%
% within Classification_Post 46,7% 50,0% 31,8% 16,7% 43,0%
3 Count 3 14 11 2 30
% within Classification_PreLf 10,0% 46,7% 36,7% 6,7% 100,0%
% within Classification_Post 10,0% 33,3% 50,0% 33,3% 30,0%
4 Count 0 1 3 3 7
% within Classification_PreLf 0,0% 14,3% 42,9% 42,9% 100,0%
% within Classification_Post 0,0% 2,4% 13,6% 50,0% 7,0%
Total Count 30 42 22 6 100
% within Classification_PreLf 30,0% 42,0% 22,0% 6,0% 100,0%
% within Classification_Post 100,0% 100,0% 100,0% 100,0% 100,0%
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Table 12. Crosstabs Classification_Pre compared with Classification_Post
Classification_Post
Total 1 2 3 4
Classification_Pre 1 Count 12 7 2 0 21
% within Classification_Pre 57,1% 33,3% 9,5% 0,0% 100,0%
% within Classification_Post 40,0% 16,7% 9,1% 0,0% 21,0%
2 Count 14 21 13 3 51
% within Classification_Pre 27,5% 41,2% 25,5% 5,9% 100,0%
% within Classification_Post 46,7% 50,0% 59,1% 50,0% 51,0%
3 Count 4 13 6 2 25
% within Classification_Pre 16,0% 52,0% 24,0% 8,0% 100,0%
% within Classification_Post 13,3% 31,0% 27,3% 33,3% 25,0%
4 Count 0 1 1 1 3
% within Classification_Pre 0,0% 33,3% 33,3% 33,3% 100,0%
% within Classification_Post 0,0% 2,4% 4,5% 16,7% 3,0%
Total Count 30 42 22 6 100
% within Classification_Pre 30,0% 42,0% 22,0% 6,0% 100,0%
% within Classification_Post 100,0% 100,0% 100,0% 100,0% 100,0%
Table 13. Crosstabs Classification_Pre compared to Classification_validated
Classification_validated
Total 1 2 3 4
Classification_Pre 1 Count 11 5 1 4 21
% within Classification_Pre 52,4% 23,8% 4,8% 19,0% 100,0%
% within Classification_ validated 24,4% 25,0% 10,0% 16,0% 21,0%
2 Count 22 10 5 14 51
% within Classification_Pre 43,1% 19,6% 9,8% 27,5% 100,0%
% within Classification_ validated 48,9% 50,0% 50,0% 56,0% 51,0%
3 Count 10 5 4 6 25
% within Classification_Pre 40,0% 20,0% 16,0% 24,0% 100,0%
% within Classification_ validated 22,2% 25,0% 40,0% 24,0% 25,0%
4 Count 2 0 0 1 3
% within Classification_Pre 66,7% 0,0% 0,0% 33,3% 100,0%
% within Classification_ validated 4,4% 0,0% 0,0% 4,0% 3,0%
Total Count 45 20 10 25 100
% within Classification_Pre 45,0% 20,0% 10,0% 25,0% 100,0%
% within Classification_ validated 100,0% 100,0% 100,0% 100,0% 100,0%
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Table 14. Crosstabs Classification_PreLf compared to Classification_ validated
Classification_ validated
Total 1 2 3 4
Classification_PreLf 1 Count 11 5 1 3 20
% within Classification_PreLf 55,0% 25,0% 5,0% 15,0% 100,0%
% within Classification_ validated 24,4% 25,0% 10,0% 12,0% 20,0%
2 Count 21 11 2 9 43
% within Classification_PreLf 48,8% 25,6% 4,7% 20,9% 100,0%
% within Classification_ validated 46,7% 55,0% 20,0% 36,0% 43,0%
3 Count 10 4 7 9 30
% within Classification_PreLf 33,3% 13,3% 23,3% 30,0% 100,0%
% within Classification_ validated 22,2% 20,0% 70,0% 36,0% 30,0%
4 Count 3 0 0 4 7
% within Classification_PreLf 42,9% 0,0% 0,0% 57,1% 100,0%
% within Classification_ validated 6,7% 0,0% 0,0% 16,0% 7,0%
Total Count 45 20 10 25 100
% within Classification_PreLf 45,0% 20,0% 10,0% 25,0% 100,0%
% within Classification_ validated 100,0% 100,0% 100,0% 100,0% 100,0%
Table 15. Crosstabs Classification_Post compared to Classification_ validated
Classification_ validated
Total 1 2 3 4
Classification_Post 1 Count 18 8 0 4 30
% within Classification_Post 60,0% 26,7% 0,0% 13,3% 100,0%
% within Classification_ validated 40,0% 40,0% 0,0% 16,0% 30,0%
2 Count 23 11 3 5 42
% within Classification_Post 54,8% 26,2% 7,1% 11,9% 100,0%
% within Classification_ validated 51,1% 55,0% 30,0% 20,0% 42,0%
3 Count 4 1 6 11 22
% within Classification_Post 18,2% 4,5% 27,3% 50,0% 100,0%
% within Classification_ validated 8,9% 5,0% 60,0% 44,0% 22,0%
4 Count 0 0 1 5 6
% within Classification_Post 0,0% 0,0% 16,7% 83,3% 100,0%
% within Classification_ validated 0,0% 0,0% 10,0% 20,0% 6,0%
Total Count 45 20 10 25 100
% within Classification_Post 45,0% 20,0% 10,0% 25,0% 100,0%
% within Classification_ validated 100,0% 100,0% 100,0% 100,0% 100,0%
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8.3 Questionnaires
8.3.1 Dyspnoea scores – filled out by children and parents
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8.3.2 Childhood Asthma Control Test (age <12 years)
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8.3.3 Asthma Control Test (age >12 years)
1: Hoe vaak heb je door je astma op school of thuis minder kunnen doen dan normaal in
de afgelopen 4 weken?
Ο nooit
Ο zelden
Ο soms
Ο meestal
Ο altijd
2: Hoe vaak ben je kortademig geweest in de afgelopen 4 weken?
Ο helemaal niet
Ο 1 of 2 keer per week
Ο 3 tot 6 keer per week
Ο 1 keer per dag
Ο vaker dan 1 keer per dag
3: Hoe vaak ben je ’s nachts of ’s morgens vroeger dan normaal wakker geworden door
astmaklachten (piepen, hoesten, kortademigheid, een drukkend gevoel of pijn op de
borst) in de afgelopen 4 weken?
Ο helemaal niet
Ο 1 of 2 keer
Ο 1 keer per week
Ο 2 tot 3 nachten per week
Ο 4 of meer nachten per week
4: Hoe vaak heb je je blauwe pufje gebruikt om een astma aanval te stoppen in de
afgelopen 4 weken?
Ο helemaal niet
Ο 1 keer per week of minder
Ο een paar keer per week
Ο 1 of 2 keer per dag
Ο 3 keer of vaker per dag
5: Hoe vindt je dat je astma onder controle is de afgelopen 4 weken?
Ο volledig onder controle
Ο goed onder controle
Ο een beetje onder controle
Ο slecht onder controle
Ο helemaal niet onder controle
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8.4 Instruction assessment videos
Doel:
Deze studie is opgezet om de relatie te bestuderen tussen dyspnoe scores van kinderen met
astma gefilmd voor- en na inspanning, door kinderartsen, met simultaan vergeleken longfunctie
metingen.
Op deze manier hopen we inzicht te krijgen in de betrouwbaardheid van de klinische
beoordeling van dyspnoe op basis van videomateriaal.
Videomateriaal:
Er werden 20 kinderen geselecteerd tussen de 4 en 17 jaar aan de hand van inclusie- en exclusie
criteria. Alle kinderen hebben daarbij >24u geleden hun laatste medicatie gehad.
U ziet een video-fragment van voor- en na inspanning van een kind met astma. Deze bestaat uit
een deel wanneer het kind praat en tevens een deel waarin het kind recht in de camera kijkt.
Scoringssysteem:
De pre- en post-inspannings video’s zullen gescored worden op verschillende tekenen van
benauwdheid. Elke observeerder noteert de aanwezigheid en ernst van de volgende klinische
verschijnselen op een gestructureerde wijze; piepen, verlengd expirium, neusvleugelen,
jugulaire- en supraclaviculaire intrekkingen. Deze zullen als een binaire variabele worden
genoteerd (aan- of afwezig). Ook zal er een algehele score worden gegeven aan de hand van de
Likert schaal, variërend van 0 (geen benauwdheid) tot 10 (zeer ernstige benauwdheid). Tevens
zal er een indeling worden gemaakt over de mate van benauwdheid; geen, mild, matig of
ernstige benauwdheid, aan de hand van onderstaande indeling.
Tabel 16. Classificatie van de ernst van inspanningsastma
Ernst van inspanningsastma Maximal daling FEV1 na inspanning (%)
Geen inspanningsastma <10%
Milde inspanningsastma >10% - <25%
Gematigde inspanningsastma >25% - <50% Ernstige inspanningsastma >50% zonder ICS-gebruik
>30% met ICS-gebruik
Opbouw scoringssysteem
De observeerder beoordeelt het kind voorafgaand aan de
inspanning aan de hand van de pre-inspanningsvideo, waarbij er
een inschatting wordt gemaakt of het kind benauwd zal gaan
worden na de inspanning. Vervolgens krijgen de observeerders
de longfunctie voorafgaand aan de inspanning te zien en in de
volgende stap de post-inspanningsvideo. Hierna maken ze
nogmaals een inschatting van de dyspnoe.
Aan de hand van deze scores zal er worden gekeken of het
toevoegen van de longfunctie aan de casus en de pre-
inspanningsvideo (de ‘spreekkamer’ setting) zal zorgen voor een
verbetering van de voorspelling van artsen. Tevens zal gekeken
worden of het toevoegen van een post-inspanningsvideo en
daarmee het door de observeerders zien van de klachten die
optreden tijdens het benauwdheid, het mogelijk maakt de ernst
van EIB in te schatten. Figuur. 13 Beoordelingsmodel
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Casus + pre-inspanningsvideo:
Classification van benauwdheid
Geen (<10%) Mild (≥10 - <25%) Gematigd (≥25 - <50%) Ernstig (≥50%)
Benauwdheidskenmerken
Piepen Aanwezig Afwezig
Verlengd expirium Aanwezig Afwezig
Neusvleugelen Aanwezig Afwezig
Jugulaire intrekkingen Aanwezig Afwezig
Supraclaviculaire intrekkingen Aanwezig Afwezig
Likert scale
Casus + pre-inspanningsvideo + longfunctie
Classification van benauwdheid
Geen (<10%) Mild (≥10 - <25%) Gematigd (≥25 - <50%) Ernstig (≥50%)
Likert scale
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M.H.T. van Hoesel
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Post-inspanningsvideo
Classification van benauwdheid
Geen (<10%) Mild (≥10 - <25%) Gematigd (≥25 - <50%) Ernstig (≥50%)
Benauwdheidskenmerken
Piepen Aanwezig Afwezig
Verlengd expirium Aanwezig Afwezig
Neusvleugelen Aanwezig Afwezig
Jugulaire intrekkingen Aanwezig Afwezig
Supraclaviculaire intrekkingen Aanwezig Afwezig
Likert scale