Obstructive sleep apnoea: from respiratory events to coronary microvascular dysfunction

Obstructive sleep apnea, chronic obstructive pulmonary disease and hypertensive microvascular disease: a cross-sectional observational cohort study

Hypertensive microvascular disease is associated with an increased risk of diastolic heart failure, vascular dementia and progressive renal impairment. This study examined whether individuals with obstructive sleep apnoea (OSA) had more retinal hypertensive microvascular disease than those with chronic obstructive pulmonary disease (COPD) and hospital controls. This was a single-centre, cross-sectional, observational study of participants recruited consecutively from a general respiratory clinic and a general medical clinic. OSA was diagnosed on overnight polysomnography study (apnoea:hypopnoea index ≥ 5), and controls with COPD had a forced expiratory volume/forced vital capacity (forced expiratory ratio) < 70%. Individuals with both OSA and COPD were excluded. Hospital controls had no COPD on respiratory function testing and no OSA on specialist physician questioning. Study participants completed a medical questionnaire, and underwent resting BP measurement, and retinal photography with a non-mydriatic camera. Images were deidentified and graded for microvascular retinopathy (Wong and Mitchell classification), and arteriole and venular calibre using a semiautomated method at a grading centre. Individuals with OSA (n = 79) demonstrated a trend to a higher mean arterial pressure than other hospital patients (n = 143) (89.2 ± 8.9 mmHg, p = 0.02), and more microvascular retinopathy (p < 0.001), and narrower retinal arterioles (134.2 ± 15.9 μm and 148.0 ± 16.2 μm respectively, p < 0.01). Microvascular retinopathy and arteriolar narrowing were still more common in OSA than hospital controls, after adjusting for age, BMI, mean arterial pressure, smoking history and dyslipidaemia (p < 0.01, p < 0.01, respectively). Individuals with OSA demonstrated a trend to a higher mean arterial pressure than those with COPD (n = 132, 93.2 ± 12.2 mmHg and 89.7 ± 12.8 mmHg respectively, p = 0.07), and more microvascular retinopathy (p = 0.0001) and narrower arterioles (134.2 ± 15.9 and 152.3 ± 16.8, p < 0.01). Individuals with OSA alone had more systemic microvascular disease than those with COPD alone or other hospital patients without OSA and COPD, despite being younger in age.

Severe obstructive sleep apnea is associated with coronary microvascular dysfunction and obstruction in patients with ST-elevation myocardial infarction

BACKGROUND

Coronary microvascular dysfunction and obstruction (CMVO) is a strong predictor of a poor prognosis in patients with ST-segment elevation myocardial infarction (STEMI). Although research has suggested that obstructive sleep apnea (OSA) exacerbates CMVO after primary percutaneous coronary intervention, data supporting a correlation between OSA and CMVO are limited. This study was performed to investigate whether OSA is associated with CMVO, detected as microvascular obstruction on cardiovascular magnetic resonance images, in patients with STEMI.

METHODS

Patients (N = 249) with a first STEMI underwent primary percutaneous coronary intervention. CMVO was evaluated on cardiovascular magnetic resonance images based on the presence of microvascular obstruction. OSA was classified into four levels of severity based on the respiratory event index (REI): absent (REI of <5), mild (REI of ≥5 to <15), moderate (REI of ≥15 to <30) and severe (REI of ≥30).

RESULTS

The REI was significantly higher in the presence of microvascular obstruction (n = 139) than in its absence (n = 110) (REI of 12.8 vs. 10.7, respectively; p = 0.023). Microvascular obstruction was observed in 42%, 58%, 57% and 70% of patients in the absent, mild, moderate and severe OSA groups, respectively. Multiple logistic regression analysis showed that severe OSA was associated with increased odds of microvascular obstruction (odds ratio (OR), 5.10; 95% confidence interval (CI),1.61-16.2; p = 0.006). Mild and moderate OSA were also associated with increased odds of microvascular obstruction (mild OSA: OR, 2.88; 95% CI, 1.19-7.00; p = 0.019 and moderate OSA: OR, 3.79; 95% CI, 1.43-10.1; p = 0.008).

CONCLUSION

Severe OSA was associated with CMVO after primary percutaneous coronary intervention in patients with STEMI.

Cardiovascular Disease in Patients with Chronic Obstructive Pulmonary Disease, Obstructive Sleep Apnoea Syndrome and Overlap Syndrome

Chronic obstructive pulmonary disease (COPD) and obstructive sleep apnoea syndrome (OSAS) are among the most prevalent chronic respiratory disorders. Accumulating data suggest that there is a significant burden of cardiovascular disease (CVD) in patients with COPD and OSAS, affecting negatively patients' quality of life and survival. Overlap syndrome (OS), i.e. the co-existence of both COPD and OSAS in the same patient, has an additional impact on the cardiovascular system multiplying the risk of morbidity and mortality. The underlying mechanisms for the development of CVD in patients with either OSAS or COPD and OS are not entirely elucidated. Several mechanisms, in addition to smoking and obesity, may be implicated, including systemic inflammation, increased sympathetic activity, oxidative stress and endothelial dysfunction. Early diagnosis and proper management of these patients might reduce cardiovascular risk and improve patients' survival. In this review, we summarize the current knowledge regarding epidemiological aspects, pathophysiological mechanisms and present point-to-point specific associations between COPD, OSAS, OS and components of CVD, namely, pulmonary hypertension, coronary artery disease, peripheral arterial disease and stroke.

Reduced Coronary Flow Reserve Is Associated with Impaired Ventricular-vascular Interaction in Patients with Obstructive Sleep Apnea

Background and Objectives

Obstructive sleep apnea (OSA) is associated with cardiac and arterial damage and adverse cardiovascular outcomes. We aimed to determine whether coronary flow reserve (CFR), which represents microvascular dysfunction, might be associated with the ventricular-vascular coupling index (VVI), which represents the afterload-adjusted contractility in patients with OSA.

Methods

We enrolled 281 patients (257 males; mean age, 43±11 years) with newly diagnosed OSA. Transthoracic echocardiography was performed, and adenosine-associated CFR was measured in the left anterior descending coronary artery. We evaluated the differences between the patients with normal CFR ≥2.5 and reduced CFR <2.5. VVI was calculated using the effective arterial elastance (Ea) and left ventricular (LV) end-systolic elastance (Ees) as follows: 10×Ea/Ees.

Results

The normal CFR group (n=214) showed increased Ees (7.28±2.31 vs. 8.14±2.33 mmHg/mL, p=0.016) and preserved VVI (3.17±1.53 vs. 2.78±1.20, p=0.044) compared with the reduced CFR group (n=67). There were no differences in LV dimension, LV ejection fraction, left atrial-volume index, E/e′, left atrial strain and LV global longitudinal strain between the 2 groups (all p>0.05). CFR was significantly correlated to Ees (r=0.139; p=0.023) and VVI (r=−0.137; p=0.025).

Conclusions

Reduced CFR is associated with decreased Ees and impaired VVI in OSA patients. It suggests the necessity of more intensive observation in OSA patients with reduced CFR to improve cardiovascular outcomes.

Advanced polysomnographic analysis for OSA: A pathway to personalized management?

Obstructive sleep apnea (OSA) is a highly heterogeneous disorder, with diverse pathways to disease, expression of disease, susceptibility to co-morbidities and response to therapy, and is ideally suited to precision medicine approaches. Clinically, the content of the information-rich polysomnogram (PSG) is not currently fully utilized in determining patient management. Novel PSG parameters such as hypoxic burden, pulse transit time, cardiopulmonary coupling and the frequency representations of PSG sensor signals could predict a variety of cardiovascular disease, cancer and neurodegeneration co-morbidities. The PSG can also be used to identify key pathophysiological parameters such as loop gain, arousal threshold and muscle compensation which can enhance understanding of the causes of OSA in an individual, and thereby guide choices on therapy. Machine learning methods performing their own parameter extraction coupled with large PSG data sets offer an exciting opportunity for discovering new links between the PSG variables and disease outcomes. By exploiting existing and emerging analytical methods, the PSG may offer a pathway to personalized management for OSA.

Opportunities for utilizing polysomnography signals to characterize obstructive sleep apnea subtypes and severity

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder with many pathophysiological pathways to disease. Currently, the diagnosis and classification of OSA is based on the apnea-hypopnea index, which poorly correlates to underlying pathology and clinical consequences. A large number of in-laboratory sleep studies are performed around the world every year, already collecting an enormous amount of physiological data within an individual. Clinically, we have not yet fully taken advantage of this data, but combined with existing analytical approaches, we have the potential to transform the way OSA is managed within an individual patient. Currently, respiratory signals are used to count apneas and hypopneas, but patterns such as inspiratory flow signals can be used to predict optimal OSA treatment. Electrocardiographic data can reveal arrhythmias, but patterns such as heart rate variability can also be used to detect and classify OSA. Electroencephalography is used to score sleep stages and arousals, but specific patterns such as the odds-ratio product can be used to classify how OSA patients responds differently to arousals.

OBJECTIVE

In this review, we examine these and many other existing computer-aided polysomnography signal processing algorithms and how they can reflect an individual's manifestation of OSA.

SIGNIFICANCE

Together with current technological advance, it is only a matter of time before advanced automatic signal processing and analysis is widely applied to precision medicine of OSA in the clinical setting.