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phase, compared with that observed in adults with OSA. The REMS-predominant
disease is by far the most usual form of OSA occupying more than 80% of the cases.
In adults, NREMS-predominant disease occupies approximately 80% or more of the
totality of patients being evaluated for OSA (Spruyt and Gozal
2012). The patho-
physiology of the increased variability of pharyngeal dilator muscle activity during
Stage 2 sleep is postulated to arise from alterations in mechanoreceptor/chemore-
ceptor control (Katz and Whit e
2004)
.
284 C. D’Elia et al.
The pharyngeal collapsible segment
is controlled by at least 20 sets of paired
muscles, which can alter its size, shape, and dynamics, and behaves like a Starling
resistor (Ayappa and Rapoport
2003). Collapse occurs when the pressure surround-
ing the collapsible segment of the upper airway, known as critical tissue pressure
(Pcrit), becomes greater than the pressure within the collapsible segment of the
airway and when upstream pressure is lower than Pcrit (Arens and Marcus 2004).
Pcrit is, thus, an objective meas ure of airway collapsibility and was found to be
higher (i.e., less negative) in children with OSA than in those with primary snoring
and correlated with the AHI (Tan et al.
2013).
Intense local and systemic inflammation is present in OSA patients. In the upper
airway, this process may promote oropharyngeal inspiratory muscle dysfunction and
amplify upper airway narrowing and collapsibility thereby worsening the frequency
and duration of apneas during sleep (Hatipoǧlu and Rubinstein 2003).
The pediatric airway is more resistant to collapse compared to the adult airway;
children snore less than adults and have fewer obstructive apneas (Katz and
D’Ambrosio 2008; Marcus et al. 1999a). The upper airway compensatory responses
to subatmospheric pressure loading decreases with age. Obese adolescents with
OSAS manifest blunted upper airway neuromuscular compensatory responses to
decreases in upper airway pressure during sleep. In contrast, obese adolescents
without OSAS maintain protective upper airway reflexes during adolescent devel-
opment (Huang et al.
2012).
The pattern of upper airway muscle recruitment in children with OSAS may be
different from that in adults; children may have greater upper airway muscle
activation, thereby preventing total airway occlusion (Marcus et al. 1999a).
17.3.2 Arousal Threshold
Arousal from sleep immediately opens the airway and normalizes gas exchange
abnormalities. However, arousal may also be considered an adverse epiphenomenon
that potentiates obstructive cycling and interferes with sleep homeostasis (Younes
2004). With a decreased arousal threshold, there is insufficient time for respiratory
stimuli to engage the pharyngeal muscles, reopen the airway prior to awakening, and
disrupt breathing stability. Accordingly, a decreased respiratory arousal threshold is
considered a contributor to OSA pathogenesis. It was hypothesized that repetitive
arousal from sleep led to hypocapnia and subsequent dilator muscle hypotonia and
apneas.
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17 Updates in Pediatric Sleep Apnea 285
However, recent clinical and experimental studies have not demonstrated low
upper airway dilator muscle activity following arousal-induced hypocapnia (Cori
et al. 2017; Malhotra and Jordan 2016). Inconsistences between the hypothesized
adverse effects of arousal and prior research may be due to methodological issues.
The arousal response in prepubertal children with OSA was observed at a
significantly higher inspiratory resistive load and hypercapnia than did controls
(Marcus et al.
1999b, 1998). The etiology of the increased arousal threshold to
respiratory stimuli has not been established and may be a secondary phenomenon.
The arousal threshold was particularly high during REM sleep, which is when
most pediatric OSA occurs. This lack of arousal in children with OSA, and presumed
lack of a ventilatory compensation to loading may account for the preservation of
sleep architecture and contribute to the occurrence of prolonged obstructive
hypoventilation (prolonged periods of partial upper airway obstruction associated
with hypercapnia) (Marcus et al.
1999b). Arousal responses to acoustic
nonrespiratory stimuli seems to be normal in children with OSA (Moreira et al.
2005).
17.3.3 Unstable Ventilatory Control
At sleep onset, the wakefulness drive is lost, and ventilation is primarily governed by
the metabolic chemoreflex control system (Deacon-Diaz and Malhotra 2018). The
contribution of ventilatory control to the pathogenesis of OSA in children is so far
unknown (Domany et al.
2019).
Loop gain (LG) is a dimensionless value quantifying the stability of the ventila-
tory control system; it represents the sensitivity of the feedback loop controlling
ventilation and is defined as the size of a corrective ventilatory response relative to
the size of the ventilatory disturbance that elicits the correction (Bokov et al. 2020).
Components of LG in the system of ventilatory regulation are the controller gain
(CG), which refers to the extent of the ventilatory response to specific variations in
hypercapnia or hypoxia, regulated by chemoreceptors, and the plant gain (PG),
which indicates the impact of the ventilatory response on arterial oxygen and carbon
dioxide levels. Unstable ventilatory control is characterized by high LG and may
contribute to cyclical airway obstruction by promoting airway collapse during
periods of a low ventilatory drive (Deacon and Catcheside 2015).
It was shown that children with moderate to severe OSA had not an increased LG
as compared to those without OSA or with mild OSA. These children with OSA had
a higher PG compared to children without OSA, and PG was positively associated
with the severity of OSA (Domany et al. 2019; Bokov et al. 2020).
High PG, acting in concert with a highly collapsible upper airway and low arousal
threshold, may contribute significantly toward increasing the severity of OSA, even
when controller gain is low (Khoo et al.
2020). Raised PG might exacerbate OSA
severity through a feedback instability pathway that is different from the classical
pathway that involves high chemoreflex loop gain (Khoo et al. 2020).
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286 C. D’Elia et al.
Factors such as lung volume, pulmonary blood flow, and the ability to eliminate
CO2 measured by the difference between the inspired and expired CO2 are major
determinants of PG. Accordingly, an abnormally elevated PG may result from
abnormal lung volumes, a reduced ability to eliminate CO2 adequately such as in
ventilation/perfusion mismatch (VQM), and decreased pulmonary blood flow
(Domany et al.
2019).
In most OSA patients the main factor affecting plant gain is functional residual
capacity. Reductions in lung stores of either CO2 or O2 will increase plant gain
because smaller tidal volumes will produce greater fluctuations in alveolar gas
tensions (Deacon-Diaz and Malhotra
2018). PG and OSA severity may increase
with certain kinds of VQM where the effective gas-exchanging lung volume is
reduced, such as what may exist in patients with asthma or subjects with develop-
mental lung abnormalities (e.g., alveolar simplification), such as in down syndrome
(Khoo et al.
2020).
The reversibility of the elevated PG in children with OSA after
adenotonsillectomy and with improvement in OSA suggests that obstructive breath-
ing during sleep might be responsible for the increase in PG (Domany et al.
2019).
There is no evidence to suggest that lung volumes or plant gain are inherently
different in OSA patients independent of other factors known to alter lung volume,
such as obesity (Deacon-Diaz and Malhotra
2018).
17.3.4 Anatomic Factors
The anatomic predisposing factors for OSA differ over the lifespan. In infants, high
nasal resistance, reduced airway stiffness, highly compliant chest wall, spontaneous
neck flexion, airway edema from gastroesophageal reflux disease, laryngomalacia,
altered facial skeletal development, glossoptosis, macroglossia are important risk
factors (Arens et al.
2021). Adenotonsillar hypertrophy (AH) and obesity are the
main risk factors in childhood and adolescence, respectively (Arens and Marcus
2004).
Compared with controls, children with OSA have smaller upper airway cross-
sectional area (Arens et al. 2005) and this is noted in all age groups, probably
predisposing to airway collapse during sleep (Arens and Marcus 2004).
External factors impact the size of the upper airway, particularly when it is in a
retropalatal or retroglossal position. Three of these factors are particularly promi-
nent: fat deposits (related to the body mass index), craniofacial features (related to
genetic and functional factors), and hypertrophied tissues, in part related to local
inflammation. Genetic and environmental factors can both have an influence on
these external factors (Huang and Guilleminault
2017).
Fluctuations in the airway area during tidal breathing are significantly greater in
children with OSA, maybe due to increased airway complianc e although resistive
pressure loading is another probable explanation (Arens et al.
2005).
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17 Updates in Pediatric Sleep Apnea 287
Children with syndromic dysmorphology involving craniofacial synostosis,
midface hypoplasia, retro positioning of the mandible or maxilla, and glossoptosis
frequently have OSA. These morphologic alterations in genetic syndromes, such as
Pierre Robin, are well-recognized risk factors, but the etiology is often multifactorial,
and many children have multilevel airway obstruction. In the down syndrome
phenotype, upper airway obstruction may be associated with a combination of
factors such as midfacial hypoplasia, AH, relative macroglossia, enlarged or swollen
nasal turbinates, poor muscle tone, and elevated BMI (Simpson et al. 2018).
The contribution of skeletal abnormalities to the development of OSA in other-
wise normal children is controversial (Katz and D’Ambrosio
2008). No significant
lower face skeletal differences were found between young children with OSA and
matched controls (Arens et al.
2001), although cephalometric studies in children
with OSA frequently report narrower maxilla, mandibular retrognathia, longer lower
facial height, and caudal placement of the hyoid bone (Katz and D’Ambrosio
2008).
These craniofacial skeletal abnormalities may contribute to the development of OSA
in some otherwise nonsyndromic children and also are the effect of craniofacial
growth modification in mouth breathing (MB) children (Zheng et al.
2020).
The low and anterior position of the tongue related to mouth breathing results in a
lack of internal pressure, leading to a reduction of transversal growth of the upper
arch with the development of lateral and posterior crossbite. On the other hand,
mouth breathing is associated with decreased nose prominence and width dimen-
sions compared to normal children. These facial characteristics could lead to a
reduced upper airway space resulting in obstructive apnea events (Galeotti et al.
2018).
The etiology of MB may be multifactorial and attributable to anatomic factors,
including narrow airways, AH, nasal septal deviation, nasal polyps, respiratory
allergies, nasal turbinate hypertrophy, and sleep position (Zheng et al.
2020).
Inherited abnormalities of the craniofacial structure appear to explain at least a
portion of the familial clustering of OSAS, and the genetic basis is suggested by twin
and family studies (Casale et al. 2009).
AH substantially raises pharyngeal resistance and ultimately results in episodic
airway collapse and complex interactions between the anatomical features and other
elements such as upper airway tone and venti latory drive . AH is the most common
cause of OSA in children but a rare cause of OSA in adults.
It was demonstrated that tonsil size does not always correlate well with baseline
OSA severity (Nolan and Brietzke 2011; Tang et al. 2015). In young children, using
magnetic resonance imaging, irrespective of the relationship with the tonsillar
pillars, has shown that the true tonsil size was positively correlated to OSAS severity
(Arens et al. 2001).
The lack of a clear association between subjective tonsil size and OSA disease
severity may be attributed to the difficulty in accurately estimating tonsil size due to
the position of the tonsil in the fossa (endophytic tonsils) or difficulty in accurately
estimating the anterior-posterior dimension of the tonsil (Tang et al. 2015).
The adenoids, located on the roof of the nasopharynx, normally enlarge in size
during infancy and childhood and subsequently progressively reduce in size during
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adolescence and adulthood. In normal children, the airway size grows proportion-
ately with the soft tissues surrounding it. Children with OSA have larger adenoids,
tonsils, and soft palates compared with normal control subjects which decrease the
pharyngeal airway (Arens et al.
2001).
288 C. D’Elia et al.
The disproportionate proliferation o
f the adenoids and tonsils occurs more fre-
quently in some groups of children, including those with allergic rhinitis, asthma,
recurrent upper airway respiratory infections, and those exposure to environmental
tobacco smoke (Evcimik et al.
2015).
There is now ample data confirming that OSA associated with obesity is highly
prevalent in children and adolescents. The association between obesity and OSA
emerges from two sets of observations; the first is the observed high prevalence of
OSA among obese children and adolescents, and the second is the higher proportion
of children with OSA who are obese. Thus, it appears that both conditions can
coexist and yet potentiate the adverse imp act of each. It is believed that the
prevalence of OSA among obese children and adolescents can be as high as 60%
(Narang and Mathew 2012). Increased deposition of fat in the parapharyngeal fat
pads near and within the soft palate contributes to airway obstruction. Obese children
with OSA may also have AH and surgical removal of enlarged tonsils and adenoids
in obese children with OSA results in a marked improvement of the AHI but with
high rates of residual OSA (Katz and D’Ambrosio
2008).
17.4 Assessment and Diagnosis in Pediatric Respiratory
Sleep Medicine
Over the past decades, children presenting with sleep-related respiratory impairment
revealing snoring and large tonsils became less frequent in specialized sleep centers
since these cases are often screened and followed by the primary care providers with
privilege access to ENT surgeon referral for surgery. Meanwhile, several symptoms
more often presented to the specialist are also contextualized in such respiratory-
based pathology even though it could happen to appear in a more subtle presentation.
In these circumstances and depending on the specific age group, may be those major
complaints like “can hardly sleep,”“restless sleep” or “is sleepy during the day”
suggest other problems demanding a careful differential diagnosis and an accurate
assessment of possible comorbid conditions.
Therefore, a variety of questionnaires were developed to evaluate children with
impaired sleep-wake cycles and disturbed sleep. Although not related to sleep-
disordered breathing, it could be relevant to perform on these patients with nocturnal
or sleep-related respiratory difficulties. Yet, some of them are more prone to be used
as screeners by primary care practitioners, while others are preferent directed to
research. As such useful assessment tools are very well described elsewhere, in this
chapter we only cite a few of those questionnaires more widely used and with
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potential additional value for assessment and diagnosis of sleep-related breathing
disturbance in pediatric ages.
17 Updates in Pediatric Sleep Apnea 289
17.5 Children’s Sleep Habits Questionnaire (CSHQ)
Developed by Judith Owens, from Boston, this 45 items questionnaire to be
answered by adult caregivers, this questionnaire covers the most prevalent sleep
disorders in children. CSHQ allows to assessment of bedtime behavior and sleep
onset, sleep duration, the effect of anxiety in sleep and frequent night wakings, sleep-
related breathing disorders, parasomnias, and morning waking/daytime sleepiness.
Parents/caregivers are asked to fill out the Likert-type scale about the child’s typical
behaviors in recent weeks and assign one of the three options for each item. A higher
score indicates a more disturbed sleep (Owens et al. 2000).
17.6 Pediatric Daytime Sleepiness Scale (PDSS)
These eight items self-reported questionnaire was developed by Christopher Drake
and is validated for children between 11 and 15 years old and is used to measure
daytime sleepiness. This is provided in a Likert scale format with five options per
item with a higher score suggesting more daytime sleepiness (Drake et al.
2003).
17.7 Adolescent Sleep Habits Survey
This two-version questionnaire developed by Judith Owens is a relevant tool with
the aim of summarizing an appreciable amount of information on demographics,
medical history, and sleep habits as well as schedules and related sleep behaviors. It
can be applied for children from 4 to 12 grade and the complete version consist of
61–65 questions to be answered in about 25 min. There is no need for calculation and
the user should be familiar with general sleep disorders to proceed with
recommending further assessment as needed (Shahid et al. 2012).
17.8 BEARS Sleep Screening Tool
Is an easy-to-do pediatric sleep screener to be used preferably in the primary care
setting. Developed by Judith Owens, the BEARS has five items surpassing bedtime
issues, excessive daytime sleepiness, night awakenings, regularity of sleep and sleep
duration, and snoring, where parents/caregivers are asked to point out if there are any
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sleep problems referred for each item. When positively answered, further assessment
should be required. No scoring is needed but the interpreter should have a basic
knowledge of sleep medicine (Owens and Dalzell 2005).
290 C. D’Elia et al.
17.9 Obstructive Sleep Apnea-18 (OSA-18)
An 18-item (five subscales) questionnaire developed by Ramon Arturo Franco,
covering five distinct aspects (five items), like sleep disturbance, physical symptoms,
emotional symptoms, daytime function, and caregivers’ concerns. It serves to infer
the impact of pediatric OSA on quality of lif e. It is validated for children ranging
from 6 months to 12 years and takes up to 10 min to be completed. Each item is
cored using a Likert-type scoring system and the caregiver is called to point, from
1 to 7, the frequency of a list of symptoms for the last 4 weeks. A total symptom
score of less than 60 indicates a small impact on health-rel ated quality of life. A
moderate (60–80) and severe impact (more than 60) would be inferred accordingly
(Franco et al. 2000).
17.10 Obstructive Sleep Apnea-5 (OSA-5)
A short form of the OSA-18, proposed by Gillian Nixon for the 2–18 years old
population. This questionnaire evalua tes the frequency of symptoms during the last
4 weeks as well as it takes less than 5 min to completed. Total score rage from 0 to
15, with a score of 5 and above indicating OSA with an increasing score meaning a
more likelihood of respiratory impairment during sleep (Soh et al.
2018).
17.11 Clinical Assessment and Featuring Pediatric OSA
Defining normal is not as straightforward as the literature seems to suggest. This is
particularly true in pediatric sleep medicine. Not only the wide range of the standard
deviations is common regarding sleep of younger age groups but also there is a lack
of robust normative data on the different objective tests commonly assumed as
standards. As such, substantial controversial issues remain over many decision
algorithms on the base of different suggested criteria. This implies that a careful
clinical approach is not only useful but mandatory to progress among diagnostic
hypothesis and the final assumption as well as the associated therapeutic decisions.
Disruption of both internal and external factors which depend on human life may
affect sleep in different complex ways allowing to the development of circadian
clock impairments as well as sleep disturbances. The major complaints of pediatric
patients presenting in a sleep clinic are insom nia and hypersomnia. Distinct
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mechanisms may account for: (a) daytime complaints, such as hypersomnia or
fatigue often associated with behavioral, cognitive, and emotional problems, and
(b) nighttime difficulties, such as insomnia or interrupted sleep together with rest-
lessness, respiratory impairments, motor disturbances or parasomnias. The sleep
history with a focus on a systematic sleep examination will allow us to isolate seven
major diagnostic hypotheses and allow us to go further in a m
ore oriented way
through therapeutic management.
17 Updates in Pediatric Sleep Apnea 291
The diagnostic hypothesis at this
stage will be oriented according to details
obtained both from the history and clinical examination. Further support will be
provided from the sleep lab and other tests in sleep-related breathing disorders,
central disorders of hypersomnolence, and sleep-related motor disorders. For
parasomnias, insomnia disorders and circadian rhythm sleep disorders, sleep logs,
and actigraphy measurements would be preferred to confirm the diagnostic
hypothesis.
Although less frequently in younger ages as compared to adulthood, comorbid
conditions may occur and impact either diagnostic strategy or prognosis of sleep
apnea in pediatrics. As such, it is important to consider a global view even if the
focus should be directed to respiratory impairment during sleep.
Parents or friends of patients with SRBD will often report at least the occurrence
of snoring, witness apneas, gasping, or choking during sleep or restless sleep. Night
sweats and morning headaches are common complaints in those patients. The history
of adenotonsillar hypertrophy in preschool or early school years is also common and
comorbid conditions such as obesity, craniofacial abnormalities, and neuroendocrine
disturbances may be crucial role players.
Crosstalk between different pathways and inadequate restorative processes will
turn into evident signs of poor daytime performance. Psychobehavioral problems as
well as developmental issues are also commonly concurrent and as so, these aspects
must be valorized.
Several tools objectively assessing sleep parameters are correlated to the symp-
toms of inadequate sleep and serve as standards for diagnostic assessment in
pediatric sleep medicine. From in-lab polysomnography to unattended sleep studies,
oximetry, spectral analysis of the EEG signal, actigraphy measures, autonomic
assessments, and sound analysis, there are plenty of proposals. Several wearable
devices and software’s were developed in recent years providing a substantial
number of options. However adequate validation and data from carefully taken
clinical studies should be consi dered when managing the available tools either for
diagnosis or for screening purposes.
OSA in children may present in a wide spectrum of clinical features. Snoring,
observed increased effort to breath and respiratory pauses, snorting and gasping,
nighttime sweats, restless sleep, and enuresis. This is often associated with particular
sleeping positions and occurs together with some habits usually observed during
wakefulness like mouth breathing (also more likely to occur at night in these
patients), recurrent infections in the upper airway tract, increased fatigue during
daytime, attention deficit problems, hyperactivity (majorly contributing to a poor
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school performance), increased aggressivity, hearing and speech problems,
increased pain complaints (headaches and others), and excessive daytime sleepiness.
292 C. D’Elia et al.
The differential diagnosis
for pediatric OSA may be helped by an exhaustive and
systematic evaluation of symptoms. Inspiratory sounds are suggestive of snoring
should be considered face to snoring presenting as an isolated symptom or in the
context of upper airway obstructive events. It is, however, crucial to be aware of
other sounds such as stridor and catathrenia which may sometimes confound con-
clusions. On the other hand, and to a certain extent, respiratory pauses during sleep
could be normal in children. As so, it is important to differentiate those silences from
those accompanying central sleep apnea or OSA. Choking or gasping must be
adequately assessed and not be confused with sleep-related laryngospasm or sleep-
related reflux. OSA-associated daytime impairment in a wide range of pediatric ages
would present differently. But other causes could rely on its background as obesity
hypoventilation syndrome, hypersomnia, or insufficient sleep syndrome. Also,
motor events often occurring with OSA as periodic limb movements should be
adequately differentiated from those related to restless leg syndrome, Finally, in the
context of the complaints, history, and objective clinical evaluation, parasomnias
should be considered in these patients also.
17.12 Polysomnography (PSG)
PSG is the gold standard for sleep-related disorders either in adulthood or pediatric
age. The standard overnight PSG assesses sleep parameters utilizing a multi-channel
recording and was already detailed in another chapter of this book. Meanwhile, the
PSG montage may be adequate to each specific patient according to their specific
condition and suspected disorder. On the other hand, although with a great clinical
value, standard PSG is linked to several challenging factors to be overwhelmed
(Marcus et al. 2012). Yet, although with some important limitations, in recent years,
home sleep apnea tests (HSATs) for children are becoming more interesting in the
general clinical setting. With the need of counting on significant discrepancies when
measuring with PSG or HSATs, later ones may have to be very well considered
when applied to the pediatric population, particularly to children and young adoles-
cents. Therefore, ambulatory unattended polysomnography (H-PSG) which has been
involved in such a controversial debate for years, has the advantage of being easier to
perform than standard PSG, and not only evaluate SDB but also a numerous other
sleep disorders (Chesson Jr et al.
2003).
Indeed, the future of pediatric sleep assessment would probably account for
simplifications regarding important technical aspects that would allow for a model
of parents-assisted remote monitoring preserving the major standards for clinical
integration of sleep evaluation in children and young adolescents.
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Parameter Mean SD Median
17 Updates in Pediatric Sleep Apnea 293
17.13 Overnight Pulse Oximetry
Overnight pulse oximetry allows the relatively noninvasive estimation of peripheral
blood hemoglobin oxygen saturations (SpO2) and forms part of the typical
polysomnogram (PSG) for investigation of OSA (Terrill
2020). Compared to PSG,
oximetry is simple, inexpensive, and readily available (Chan et al. 2019).
In clinical practice, obtained data are summarized with simplified indices: the
oxygen desaturation index (ODI) that calculates the number of desaturation events
(also referred to as dips or transient hypoxemic events) per hour which drop 3%
(ODI3) or 4% (ODI4) below baseline levels; the proportion of total recording time
with SpO2 ≤ 90% (T90); and other simple time-series statistics. When used as part
of a PSG, oximetry contributes to the scoring of hypopneas, and consequently, the
apnea–hypopnea index (AHI) that summarizes the severity of sleep-disordered
breathing as the number of apneas and hypopneas per hour. While such simplified
indices are convenient, they likely fail to capture important pathophysiological
characteristics (Terrill 2020).
Normative oximetry parameters in healthy children 6 months to 12 years using
oximetry motion-resistant technology able to exclude motion artifact and with short
averaging times was published recently (Table 17.1) (Ong et al. 2021).
Based on this data, normality was defined as ODI 3% <7/h, to some extent higher
than in previous studies that found in healthy children 2.2/h (95th centile ODI4%)
(Urschitz et al.
2003) and 1.2/h (2–10 years of age, 90th centile ODI3%) (Scholle
et al. 2011).
Nixon et al. observed a correlation between higher oximetry scores and elevated
apnea–hypopnea index (AHI), increased desaturation index, lower minimum arterial
oxygen saturation (SaO2) levels, and a higher respiratory arousal index (Nixon et al.
2004). Based on these findings, the McGill oximetry score was conceived. The
scoring system comprises four severity levels (McGill 1–4), which are determined
Table 17.1 Descriptive statistics for oximetry desaturation events and indices for the entire study
group (n = 66): number of oxygen desaturations >4% and >3% from baseline per hour (ODI4%
and ODI3%), delta index 12 s (DI12s), and percentage time with saturations below 92% and 90%
(Ong et al. 2021)
Mean
95% CI
Median
95% CI
90th
centile
95th
centile
97.5th
centile
ODI4% 1.14 0.84 0.93–
1.34
0.92 0.73–1.15 2.60 3.00 3.38
ODI3% 2.90 1.65 2.50–
3.29
2.58 1.96–3.10 5.65 6.43 7.06
ODI12s 0.35 0.09 0.33–
0.38
0.34 0.31–0.38 0.48 0.53 0.57
Time < 92% 0.02 0.03 0.01–
0.03
0.00 0.00–0.01 0.05 0.11 0.15
Time < 90% 0.005 0.015 0.002–
0.009
0.00 0.00–0.00 0.01 0.05 0.07
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