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Clinical examination
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Mandible
Transducer
Hyoid bone
Figure 2. Ultrasound examination of the neck in OSA.
suggest motor neuron disease. Evidence of muscle fatigability may point towards
myasthenia gravis; 35% of these patients will have OSA. Proximal lower extremity
weakness, facial weakness, ptosis and wasting of temporalis muscles is indicative of
myotonic dystrophy; both type 1 and 2 are strongly associated with OSA.
Point-of-care ultrasound in OSA
With the advent of point-of-care ultrasound (POCUS) examination of the cardiac,
lung and abdominal systems, investigators have recently begun assessing the role of
POCUS in the diagnosis of OSA. Potential advantages of POCUS in clinical assessment
are that it can be performed by the bedside and it uses minimal resources.
Most ultrasound studies in OSA involve examination of the neck; with the patient in
the supine position, a curved probe is used to examine the neck in the sagittal (figure 2)
and coronal planes. This position facilitates measurement of airway parameters such
as tongue thickness (TT), tongue area (TA) and distance between lingual arteries (DLA).
Non-airway parameters such as carotid intimal thickness and abdominal fat thickness
have also been assessed. Studies demonstrate that TT, TA and DLA are increased in
OSA patients.
Although ultrasound shows potential in the diagnosis of OSA, its role has yet to be
fully defined. Concerns about current studies include small patient numbers, lack of
standardised measurements, whether ultrasound examination should be performed
in the awake or sleep state, and whether it is feasible for a bedside clinician to obtain
these measurements.
At this point, it seems unlikely that ultrasound examination alone will be sucient
to diagnose OSA. Nevertheless, its diagnostic utility may be optimised through
combination with other bedside assessments such as questionnaires and neck
circumference.
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Clinical examination
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Further reading
• Epstein LJ, et al. (2009). Clinical guideline for the evaluation, management and long-term care
of obstructive sleep apnea in adults. J Clin Sleep Med; 5: 263–276.
• Friedman M, et al. (2017). Updated Friedman staging system for obstructive sleep apnea. Adv
Otorhinolaryngol; 80: 41–48.
• Hussein SA, et al. (2020). Role of ultrasonography in assessment of anatomic upper airway
changes in patients with obstructive sleep apnea. Adv Respir Med; 88: 548–557.
• Ismail K, et al. (2015). OSA and pulmonary hypertension: time for a new look. Chest; 147:
847–861.
• Kennedy B, et al. (2021). Endocrine diseases: diabetes mellitus, diseases of the thyroid,
acromegaly, polycystic ovarian syndrome. In: Claudio B, et al., eds. ESRS Sleep Medicine
Textbook. 2nd Edn. Regensburg, European Sleep Research Society.
• Mallampati SR, et al. (1985). A clinical sign to predict dicult tracheal intubation: a prospective
study. Can Anaesth Soc J; 32: 429–434.
• Manlises CO, et al. (2020). Dynamic tongue area measurements in ultrasound images for
adults with obstructive sleep apnea. J Sleep Res; 29: e13032.
• Marin JM, et al. (2010). Outcomes in patients with chronic obstructive pulmonary disease
and obstructive sleep apnea: the overlap syndrome. Am J Respir Crit Care Med; 182: 325–331.
• Marin JM, et al. (2012). Association between treated and untreated obstructive sleep apnea
and risk of hypertension. JAMA; 307: 2169–2176.
• Nuckton TJ, et al. (2006). Physical examination: Mallampati score as an independent predictor
of obstructive sleep apnea. Sleep; 29: 903–908.
• Ryan S, et al. (2019). Adipose tissue as a key player in obstructive sleep apnoea. Eur Respir Rev;
28: 190006.
• Schwab RJ, et al. (1995). Upper airway and so tissue anatomy in normal subjects and patients
with sleep-disordered breathing. Significance of the lateral pharyngeal walls. Am J Respir Crit
Care Med; 152: 1673–1689.
• Schwartz AR, et al. (2008). Obesity and obstructive sleep apnea: pathogenic mechanisms and
therapeutic approaches. Proc Am Thorac Soc; 5: 185–192.
• Singh M, et al. (2019). Point-of-care ultrasound for obstructive sleep apnea screening: are we
there yet? A systematic review and meta-analysis. Anesth Analg; 129: 1673–1691.
105ERS Handbook: Respiratory Sleep Medicine
Comorbidities
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Silke Ryan
OSA is frequently associated with comorbidities, including pulmonary, cardiovascular,
metabolic, neoplastic, neuropsychiatric or renal diseases. While many of these
conditions arise as a consequence of shared risk factors, such as obesity, age or
smoking, there is also substantial evidence of independent relationships. However,
many studies have been cross-sectional in design, limiting the ability to establish
causality, or have used only single metrics of disease severity such as the AHI in the
evaluation, ignoring additional relevant parameters. Nonetheless, there is growing
support of the detrimental impact of OSA in the pathophysiology of numerous
diseases and various relationships are in fact bidirectional. This chapter provides an
overview of the most relevant comorbidities.
Pulmonary diseases
OSA is a frequent occurrence in pulmonary diseases. Particularly relevant is the highly
prevalent co-existence with COPD, also termed ‘overlap syndrome’. COPD has a
complex relationship with OSA, with some factors (such as dynamic hyperinflation or
low BMI, which occur in the predominant emphysema phenotype) being protective
against OSA and other factors (such as rostral fluid shi or cigarette smoking,
characteristic of the predominant chronic bronchitis phenotype) promoting OSA. The
recognition of overlap syndrome has important clinical implications, as such patients
experience even greater degrees of oxygen desaturation during sleep when compared
Key points
• OSA is associated with a multitude of comorbidities and there is growing
evidence of bidirectional relationships.
• OSA is an independent risk factor for the development, progression and
control of numerous cardiovascular and metabolic diseases, which represent
the principal morbidity and mortality of OSA.
• The hallmark features of OSA (intermittent hypoxia and sleep fragmentation)
play key roles in the pathogenesis of comorbid conditions.
• The benefit of CPAP therapy on the incidence and control of OSAassociated diseases remains uncertain; thus, there is an urgent need for the
identification of eective, multifactorial treatment approaches.
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to individuals with OSA or COPD alone. Typically, overlap patients demonstrate a
pattern of intermittent desaturations from a baseline hypoxaemia, which is likely to
be an important contributory factor in the development of the frequently occurring
pulmonary hypertension (PH) in this patient group. Patients with the overlap syndrome
are at a higher risk of mortality, cardiovascular events or COPD exacerbations, due to
synergistic pathogenic eects arising from oxidative stress, systemic inflammation,
vascular endothelial dysfunction, accelerated atherosclerosis and sympathetic
excitation. However, OSA is frequently under-recognised by COPD patients and
clinicians, and early diagnosis and management (which may include positive pressure
ventilation) are imperative in avoiding adverse outcomes.
OSA is also a common comorbidity in patients with interstitial lung disease (ILD) and
there is growing evidence of a negative impact on a range of outcomes including
quality of life, cognitive impairment, disease progression and mortality. Similar to
COPD, the worsening hypoxaemia during sleep and exercise in subjects with both
conditions in contrast to either condition alone contributes to the development of PH.
OSA is believed to add to the pathogenesis of ILD predominantly through intermittent
hypoxia (IH) causing inflammation and oxidative stress, intrathoracic pressure swings
leading to mechanical injuries, and recurrent microaspirations as a consequence of
gastro-oesophageal reflux. Conversely, ILD may also promote the development of OSA
through low lung volumes contributing to upper airway collapsibility, increased BMI
as a consequence of systemic corticosteroid treatment, and diminished gas exchange
promoting higher loop gain.
CVD
CVD represents the principal morbidity and cause of mortality in OSA and, adjusted
for numerous confounding factors, OSA has been identified to be independently
associated with the development and progression of numerous cardiovascular
complications. Corroborated by large population studies and meta-analyses, the
association is particularly strong for hypertension in a dose-dependent fashion, and
also extends to subjects with mild disease. Notably, hypertension in OSA has several
distinctive characteristics, with a commonly non-dipping nocturnal BP pattern, a
predominant diastolic elevation and resistance to anti-hypertensive pharmacotherapy.
Furthermore, the hypertension in OSA is frequently masked and, thus, screening with
ambulatory 24-h BP monitoring is generally recommended. CPAP therapy reduces BP
and benefit appears strongest in younger subjects, those with more severe oxygen
desaturations or uncontrolled hypertension and in more CPAP-compliant patients.
OSA also has an intimate bidirectional relationship with HF, which can partly be
explained by shared risk factors including age, increased BMI or sedentary lifestyle.
Unifying mechanisms, especially fluid retention, oen make it dicult to establish
cause and eect. Sleep apnoea is highly prevalent in HF cohorts and, besides
obstructive events, there is also an increased occurrence of central apnoeas,
particularly in subjects with reduced ejection fraction. Furthermore, OSA is associated
with increased HF incidence, progression, hospitalisation and mortality.
Several studies and meta-analyses have also supported an independent causal
relationship of OSA with other CVDs, including coronary artery disease, cerebrovascular
disease and atrial fibrillation (AF), leading to an increased occurrence of cardiac events
and cardiovascular mortality. However, OSA is a heterogeneous condition, and several
cluster analyses have detected a variety of dierent phenotypes with distinctive
susceptibility to adverse cardiovascular complications. Identification of the dierent
phenotypes is a major research goal for the detection of eective treatment strategies.
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Comorbidities
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The pathogenesis of CVDs in OSA is complex and involves a multitude of triggering and
modifying factors. The OSA-typical pattern of IH plays a central role through activation
of multiple mechanistic pathways such as sympathetic excitation, inflammation,
oxidative stress or metabolic dysregulation. Furthermore, obstructive apnoeas lead to
substantial intrathoracic pressure swings, leading to deleterious alteration in cardiac
haemodynamics. In support, various population studies have demonstrated an
independent association of markers identifying the severity of IH with cardiovascular
outcomes. Furthermore, a large body of experimental studies using rodent models
has revealed detrimental eects of IH on numerous CVD processes, including vascular
remodelling, atherosclerotic plaque burden, BP, cardiac dysfunction or myocardial
infarct size.
The benefit of CPAP therapy on CVDs remains uncertain and large randomised
controlled studies have failed to demonstrate a reduction in cardiovascular events and
mortality in subjects with known CVD. These negative results may be partly explained
by poor adherence to CPAP therapy and, subsequently, a meta-analysis concluded that
there was a significant reduction in major adverse cerebrovascular and cardiovascular
events in patients using CPAP for >4 h per night. Moreover, CPAP has demonstrated its
positive eects on early CVD processes such as endothelial dysfunction and, thus, may
be predominantly beneficial in primary prevention. Furthermore, CPAP therapy needs
to be incorporated within a holistic treatment approach including pharmacological
treatments for CVDs and lifestyle modifications.
Metabolic diseases
Over the last decade, compelling evidence has accumulated of the bidirectional
relationship between OSA and metabolic dysfunction, in particular with alterations
in glucose metabolism. Several cross-sectional and longitudinal studies have
demonstrated an independent association of OSA with the prevalence and incidence
of type 2 diabetes, insulin resistance and metabolic syndrome. In addition, the
presence of OSA may contribute to poor diabetic control and, conversely, metabolic
disorders such as diabetes or components of the metabolic syndrome facilitate
upper airway collapse. Obesity, characteristic of metabolic disorders, is associated
with fat deposition within and surrounding the upper airway and also promotes
OSA through reduction in lung volumes and leptin resistance. Furthermore,
diabetes-associated peripheral neuropathy may attenuate the eect of protective
pharyngeal reflexes.
Both IH and sleep fragmentation, through activation of inflammatory pathways,
oxidative stress and sympathetic activation, are likely to play important roles in the
pathogenesis of metabolic disorders in OSA and have been shown to lead to insulin
resistance in rodents. Fast-growing evidence points to the visceral adipose tissue
as an important target organ and, interestingly, IH induces a pro-inflammatory
phenotype of the adipose tissue with subsequent impairment of the insulin signalling
pathway, changes which bear a striking similarity to the adipose tissue dysfunction
seen in obesity. Also, in rodents, IH promotes insulin resistance in liver and skeletal
muscle, induces pancreatic β-cell dysfunction and alters the composition of the gut
microbiota, which collectively result in metabolic perturbations.
CPAP is insucient to modify metabolic outcome, particularly in obese subjects.
Strategies combining CPAP with weight-loss intervention are superior in improving
insulin resistance than either treatment alone. However, weight loss is dicult to
maintain through lifestyle interventions alone. Thus, pharmacological interventions
such as glucagon-like peptide (GLP)-1 analogues or bariatric surgery in conjunction
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with lifestyle modification and CPAP may improve the incidence and control of
metabolic disorders in OSA. However, such management strategies need to be
evaluated in large randomised controlled trials.
Cancer
Growing evidence derived from epidemiological and experimental studies has linked
OSA to the incidence and progression of malignant solid tumours. However, various
confounding factors (such as age, obesity or smoking) and methodological limitations
have made it dicult to prove an independent relationship and, thus, this topic remains
under debate. However, OSA may promote specific cancer types and this evidence
has particularly arisen for cutaneous melanoma. In vivo studies employing models
of IH and sleep fragmentation have provided strong support of a causality in the OSA
and cancer relationship. A hypoxic microenvironment is a common feature of solid
tumours and associated with poor prognosis. IH augments the deleterious eects in
a dose-dependent manner, leading to enhanced growth, migration, invasiveness and
metastasis. Similar to the development of other adverse consequences, the activation
of pro-inflammatory and hypoxic pathways and the generation of reactive oxygen
species by IH probably play key roles in the pathophysiology of cancer progression.
Furthermore, there is fast-growing evidence that IH contributes to a tumourpromoting immune response. However, most studies have focused on melanoma
and lung adenocarcinoma; therefore, caution is advised before extrapolating those
results to cancers in general. Additionally, the interaction of IH or sleep fragmentation
with other important modifying factors such as age or obesity has so far been largely
ignored. Future experimental studies need to take such parameters into account to
adequately model the target population of OSA.
Depression
OSA and depression are intimately linked, which is perhaps not too surprising as
sucient sleep is an important basis for mental well-being. Both conditions exhibit
similar symptoms including fatigue and poor concentration and memory and, as
a consequence, distinction between OSA and depression is oen dicult, and it
remains unknown whether the occurrence of depressive symptoms is a direct result
of OSA alone or is rather due to the associated symptoms. Depression has been
reported to occur in up to 40% of OSA subjects, but a correlation with OSA severity
has not been consistently identified. A meta-analysis of 22 studies reported a clinically
relevant improvement in depressive symptomatology and suicidal ideation with OSA
treatment in a dose-dependent fashion, but whether this occurs as a result beyond
improvement of sleep remains unknown at this stage.
Renal disease
OSA is a frequent occurrence in patients with chronic kidney disease (CKD) and, in
end-stage disease, prevalence rates of over 50% have been reported. Furthermore,
there is evidence that OSA contributes to a progressive decline in glomerular
filtration rates, with a higher morbidity and mortality in dialysis patients. Whether
OSA independently adds to the pathophysiology of CKD remains a subject under
debate. Renal hypoxia is an important mediator of decline in kidney function and
the IH of OSA may exacerbate those eects. Furthermore, IH may indirectly lead
to tubulointerstitial injury through inflammatory, oxidative stress and sympathetic
nervous system pathways. Moreover, OSA has been associated with the
activation of the renin–angiotensin–aldosterone system, which is a well-defined
pathophysiological factor in renal ischaemia. However, the occurrence of frequently
109ERS Handbook: Respiratory Sleep Medicine
Comorbidities
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shared comorbidities, particularly hypertension, has brought into question the
significance of these implications, and CPAP therapy has failed to demonstrate a
sustained benefit on renal function.
CKD is also a well-described promoting factor of OSA, and potential pathophysiological
mechanisms include increased chemoreflex sensitivity, reduced clearance of uraemic
toxins, and hypervolaemia. Consequently, aggressive treatment of end-stage CKD
with dialysis or ultrafiltration has been shown to decrease OSA severity.
Summary
In summary, OSA is a systemic disease with a heavy burden of comorbidities. While
many relationships arise as a consequence of shared risk factors, there is increasing
evidence of independent associations and, in particular, OSA has emerged as a risk
factor for the development and progression of various cardiometabolic diseases leading
to substantial morbidity and mortality. Many comorbidities may also contribute to the
pathophysiology of OSA through diering mechanisms. A detailed understanding of
the bidirectional relationships of OSA and the varying comorbidities is a crucial step
for the detection of eective treatment strategies.
Further reading
• Almendros I, et al. (2020). Obesity, sleep apnea, and cancer. Int J Obes; 44: 1653–1667.
• Baillieul S, et al. (2022). Sleep apnoea and ischaemic stroke: current knowledge and future
directions. Lancet Neurol; 21: 78–88.
• Belaidi E, et al. (2022). Cardiac consequences of intermittent hypoxia: a matter of dose?
A systematic review and meta-analysis in rodents. Eur Respir Rev; 31: 210269.
• Cowie MR, et al. (2021). Sleep disordered breathing and cardiovascular disease: JACC state-of-
the-art review. J Am Coll Cardiol; 78: 608–624.
• Gaines J, et al. (2018). Obstructive sleep apnea and the metabolic syndrome: the road to
clinically-meaningful phenotyping, improved prognosis, and personalized treatment. Sleep
Med Rev; 42: 211–219.
• Gleeson M, et al. (2022). Bidirectional relationships of comorbidity with obstructive sleep
apnoea. Eur Respir Rev; 31: 210256.
• Gozal D, et al. (2020). Sleep apnoea adverse eects on cancer: true, false, or too many
confounders? Int J Mol Sci; 21: 8779.
• Harki O, et al. (2022). Intermittent hypoxia-related alterations in vascular structure and
function: a systematic review and meta-analysis of rodent data. Eur Respir J; 59: 2100866.
• Khor YH, et al. (2021). Interstitial lung disease and obstructive sleep apnea. Sleep Med Rev;
58: 101442.
• McNicholas WT (2017). COPD–OSA overlap syndrome: evolving evidence regarding
epidemiology, clinical consequences, and management. Chest; 152: 1318–1326.
• McNicholas WT (2019). Obstructive sleep apnoea and comorbidity – an overview of the
association and impact of continuous positive airway pressure therapy. Expert Rev Respir Med;
13: 251–261.
• Ryan S (2018). Mechanisms of cardiovascular disease in obstructive sleep apnoea. J Thorac Dis;
10: Suppl. 34, S4201–S4211.
• Ryan S, et al. (2019). Adipose tissue as a key player in obstructive sleep apnoea. Eur Respir Rev;
28: 190006.
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• Ryan S, et al. (2020). Understanding the pathophysiological mechanisms of cardiometabolic
complications in obstructive sleep apnoea: towards personalised treatment approaches.
Eur Respir J; 56: 1902295.
• Voulgaris A, et al. (2019). Chronic kidney disease in patients with obstructive sleep apnea.
A narrative review. Sleep Med Rev; 47: 74–89.
111ERS Handbook: Respiratory Sleep Medicine
Identification of high-risk
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patients
Walter T. McNicholas
OSA is highly prevalent, aecting up to one billion adults worldwide according to some
estimates. However, many aected subjects are not at significant risk of morbidity or
mortality and a major challenge in this disorder is to identify patients that are at high
risk of comorbidity and/or driving risk. The identification of SDB on an overnight sleep
study, typically measured by the AHI, provides only part of the required information
in this context, and it is widely recognised that mild OSA on a sleep study carries little
independent clinical risk of comorbidity. Furthermore, recent randomised controlled
trials (RCTs) that failed to show benefit from nasal CPAP therapy in the secondary
prevention of CVD in non-sleepy subjects with moderate/severe OSA have cast some
doubt on the independent relationship between OSA and cardiovascular comorbidity.
These considerations require a reassessment of the variables that may help to identify
high-risk OSA patients.
Cardiometabolic comorbidity
While many reports have identified an increased prevalence of cardiometabolic disease
in patients with OSA, there remains uncertainty regarding an independent relationship,
especially since important confounding factors such as obesity complicate this
assessment. Most reports evaluating the relationship of OSA with comorbidity have
used the AHI as the primary measure of OSA severity, but more recent reports have
identified other variables as important factors, such as hypoxia, daytime sleepiness
and elevated BP, especially nocturnal (figure 1). These aspects have prompted a
move to consider OSA ‘beyond the AHI’, and to consider other important variables
in the identification of high-risk patients. Furthermore, there is increasing evidence
of a bidirectional relationship between OSA and comorbidity, especially for HF and
end-stage renal disease, which further complicates the assessment of independent
relationships between OSA and comorbidity.
Key points
• OSA should be assessed by multiple variables beyond the traditional metric of
the AHI.
• Patients at high risk of cardiometabolic comorbidity may be better identified
by other OSA-related variables, such as hypoxia and non-dipping nocturnal BP.
• Sleepiness is a better indicator of driving risk than AHI.
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Identification of high-risk patients
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AHI Sleepiness
Cardiometabolic
risk assessment
Hypoxia
Figure 1. Major OSA-related variables relevant to the identification of high-risk patients.
Nocturnal
BP non-dipping
Factors relevant to the identification of high-risk patients
AHI
Although there have been doubts raised in recent years regarding the primacy of
the AHI in evaluating comorbidity risk, this variable remains the most widely studied
measure of OSA severity. Most reports indicate that mild OSA, traditionally expressed
as an AHI of 5–15 events·h−1, does not carry a clinically significant independent risk of
comorbidity, but higher levels of AHI may do so. In particular, the Lausanne cohort study,
which is a general population-based study involving over 2000 subjects drawn from
the population of Lausanne, Switzerland, reported that increased comorbidity was only
evident in the population cohort with an AHI >20 events·h−1. Thus, the AHI remains a
relevant variable, among others, in the overall assessment of high-risk patients.
Hypoxia
Oxygen desaturation is a typical feature of apnoea and hypopnoea, and the frequency
of desaturations, typically expressed as the oxygen desaturation index (ODI), provides
an important additional measure of OSA severity. Although desaturation is directly
linked to apnoea/hypopnoea, the extent of desaturation varies with the length of the
event and the starting saturation. Thus, a high AHI could be associated with relatively
modest desaturation if the events are relatively short and/or the baseline saturation is
high; conversely, a moderate AHI could be associated with more severe desaturation
if the events are relatively prolonged and/or the baseline saturation is low, such as in
a grossly obese patient. Thus, aspects of hypoxia that are relevant to comorbidity risk
include the intermittent nature of oxygen desaturation during apnoea/hypopnoea,
expressed by the ODI, and the overall severity of hypoxia, which can be quantified in
dierent ways.
Additional measures of hypoxia, such as the cumulative time spent below certain
oxygen saturation levels, e.g. 90% (CT90), provide additional information that can
help predict comorbidity risk. Several recent reports have indicated that measures of
oxygen desaturation such as the ODI and CT90 are superior to the AHI in predicting
comorbidity risk. The oxygen saturation during sleep provides a wealth of potential
information and is a subject of much investigation at present. Recent reports have
also focused on the hypoxic burden associated with OSA by quantifying the total
desaturation associated with SDB events. As oxygen saturation is relatively easy
to measure, especially compared to the AHI, this measure is likely to become an
increasingly important parameter in ambulatory diagnostic systems.
113ERS Handbook: Respiratory Sleep Medicine
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