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Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea.

ABSTRACT: BACKGROUND:Obstructive sleep apnoea (OSA) is a heterogeneous disorder, and improved understanding of physiologic phenotypes and their clinical implications is needed. We aimed to determine whether routine polysomnographic data can be used to identify OSA phenotypes (clusters) and to assess the associations between the phenotypes and cardiovascular outcomes. METHODS:Cross-sectional and longitudinal analyses of a multisite, observational US Veteran (n=1247) cohort were performed. Principal components-based clustering was used to identify polysomnographic features in OSA's four pathophysiological domains (sleep architecture disturbance, autonomic dysregulation, breathing disturbance and hypoxia). Using these features, OSA phenotypes were identified by cluster analysis (K-means). Cox survival analysis was used to evaluate longitudinal relationships between clusters and the combined outcome of incident transient ischaemic attack, stroke, acute coronary syndrome or death. RESULTS:Seven patient clusters were identified based on distinguishing polysomnographic features: 'mild', 'periodic limb movements of sleep (PLMS)', 'NREM and arousal', 'REM and hypoxia', 'hypopnoea and hypoxia', 'arousal and poor sleep' and 'combined severe'. In adjusted analyses, the risk (compared with 'mild') of the combined outcome (HR (95% CI)) was significantly increased for 'PLMS', (2.02 (1.32 to 3.08)), 'hypopnoea and hypoxia' (1.74 (1.02 to 2.99)) and 'combined severe' (1.69 (1.09 to 2.62)). Conventional apnoea-hypopnoea index (AHI) severity categories of moderate (15?AHI<30) and severe (AHI ?30), compared with mild/none category (AHI <15), were not associated with increased risk. CONCLUSIONS:Among patients referred for OSA evaluation, routine polysomnographic data can identify physiological phenotypes that capture risk of adverse cardiovascular outcomes otherwise missed by conventional OSA severity classification.

SUBMITTER: Zinchuk AV

PROVIDER: S-EPMC6693344 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea.

Zinchuk Andrey V AV Jeon Sangchoon S Koo Brian B BB Yan Xiting X Bravata Dawn M DM Qin Li L Selim Bernardo J BJ Strohl Kingman P KP Redeker Nancy S NS Concato John J Yaggi Henry K HK

Thorax 20170921 5

<h4>Background</h4>Obstructive sleep apnoea (OSA) is a heterogeneous disorder, and improved understanding of physiologic phenotypes and their clinical implications is needed. We aimed to determine whether routine polysomnographic data can be used to identify OSA phenotypes (clusters) and to assess the associations between the phenotypes and cardiovascular outcomes.<h4>Methods</h4>Cross-sectional and longitudinal analyses of a multisite, observational US Veteran (n=1247) cohort were performed. Pr ...[more]

PMID: 28935698

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Project description:The purpose of this study was to evaluate the correlation between severity of obstructive sleep apnoea syndrome (OSAS), cardiovascular disease and metabolic syndrome. We recruited 1185 patients with OSAS who underwent a complete ENT examination, including nasolaryngeal fibre optic endoscopy with Müller's manoeuvre, overnight cardio-respiratory monitoring, Epworth Sleepiness Scale (ESS) to measure daytime sleepiness, body mass index (BMI), measurement of blood pressure and blood tests.SUBSEQUENTLY, SUBJECTS WERE DIVIDED INTO THREE SUBGROUPS ACCORDING TO THE APNOEA HYPOPNOEA INDEX (AHI): mild OSAS (AHI 5-15), moderate OSAS (AHI 15-30) and severe OSAS (AHI > 30). In the sample collected, 347 (262 males and 85 females) of 1185 patients suffered from mild OSAS, 363 (269 males and 94 females) from moderate OSAS and 475 (330 males and 145 females) from severe OSAS. In the group suffering from mild OSAS, we found: 127 patients affected by hypertension, 48 with diabetes, 11 with dyslipidaemia and 32 with metabolic syndrome. In the group with moderate OSAS there were 157 patients with hypertension, 63 with diabetes, 72 with dyslipidaemia and 47 with metabolic syndrome. In the group suffering from severe OSAS there were 244 patients with hypertension, 138 with diabetes, 47 with dyslipidaemia and 90 with metabolic syndrome. For data analysis, we used the Spearman correlation test adjusted according to Sidak between the dependent variable AHI and the independent variables BMI, ESS, average SO2 (SO(2med)), hypertension, diabetes mellitus, dyslipidaemia and metabolic syndrome. The results show different patterns of correlation in terms of statistical significance: BMI ?(s) = 0.26, SO(2med) ?(s) = -0:51, hypertension ?(s) = -0.05, dyslipidaemia ?(s) = 0.22 for women, and BMI ?(s) = 0.53, ESS ?(s) = 0.28, SO(2med) ?(s) = -0.50, hypertension ?(s) = 0.17, diabetes mellitus ?(s) = 0.28 and metabolic syndrome ?(s) = 0.26 for men. The results of the study confirm the existence of a statistically significant correlation between the severity of OSAS and BMI, ESS, average SO2, hypertension, diabetes mellitus, dyslipidaemia and metabolic syndrome.

Project description:The roles of central nervous mechanisms and cortical output in obstructive sleep apnoea remain unclear. We addressed corticomuscular coupling between cortical sensorimotor areas and lower facial motor units as a mechanistic pathway and as a possible surrogate marker of corticoperipheral motor control in obstructive sleep apnoea. In this exploratory cross-sectional retrospective study, we analysed EEG (C3 and C4 leads) and chin EMG from polysomnography recordings in 86 participants (22 females; age range: 26-81?years): 27 with mild (respiratory disturbance index = 5-15 events/h), 21 with moderate (15-30 events/h) and 23 with severe obstructive sleep apnoea (>30 events/h) and 15 control subjects (<5 events/h). By computing C3-/C4-EEG-chin EMG coherence of signal dynamics in time and frequency domains, we investigated corticomuscular coupling between cortical sensorimotor areas and lower facial motor units with increasing obstructive sleep apnoea severity during the entire sleeping time, during different sleep stages and during obstructive respiratory events, including 5?s before (stable breathing) and after events (breathing resumption). In addition, we studied a possible influence of body mass index and autonomic nervous system activation. We found that both average and respiratory event-specific corticomuscular coupling between cortical sensorimotor areas and lower facial motor units weakened significantly with increasing obstructive sleep apnoea severity, was strongest during N3 and weakened in N1, N2 and rapid eye movement stages (in decreasing order). Coupling increases significantly during the obstructive respiratory events compared with coupling just before and following them. Results were independent of body mass index or autonomic nervous system activation. We conclude that obstructive respiratory events in obstructive sleep apnoea are very strongly associated both quantitatively and temporally with the degree of disconnection within the cortical sensorimotor areas-lower facial motor units pathway. This quite coordinated activity pattern suggests a cortical sensorimotor area-driven obstructive respiratory event pattern generator and a central motor output disorder in obstructive sleep apnoea.

Dataset Information

Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea.

Publications

Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea.

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