Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea

Andrey V. Zinchuk, Sangchoon Jeon, Brian B. Koo, Xiting Yan, Dawn Bravata, Li Qin, Bernardo J. Selim, Kingman P. Strohl, Nancy S. Redeker, John Concato, Henry K. Yaggi

Research output: Contribution to journalArticle

24 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)472-480
Number of pages9
JournalThorax
Volume73
Issue number5
DOIs
StatePublished - May 1 2018
Externally publishedYes

Fingerprint

Obstructive Sleep Apnea
Phenotype
Sleep
Apnea
Arousal
Cluster Analysis
Extremities
Transient Ischemic Attack
Veterans
Acute Coronary Syndrome
Survival Analysis
Respiration
Cross-Sectional Studies
Stroke
Hypoxia

Keywords

  • cardiovascular diseases
  • cluster analysis
  • heterogeneity
  • mortality
  • obstructive sleep apnea (OSA)
  • phenotype

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine

Cite this

Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea. / Zinchuk, Andrey V.; Jeon, Sangchoon; Koo, Brian B.; Yan, Xiting; Bravata, Dawn; Qin, Li; Selim, Bernardo J.; Strohl, Kingman P.; Redeker, Nancy S.; Concato, John; Yaggi, Henry K.

In: Thorax, Vol. 73, No. 5, 01.05.2018, p. 472-480.

Research output: Contribution to journalArticle

Zinchuk, AV, Jeon, S, Koo, BB, Yan, X, Bravata, D, Qin, L, Selim, BJ, Strohl, KP, Redeker, NS, Concato, J & Yaggi, HK 2018, 'Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea', Thorax, vol. 73, no. 5, pp. 472-480. https://doi.org/10.1136/thoraxjnl-2017-210431
Zinchuk, Andrey V. ; Jeon, Sangchoon ; Koo, Brian B. ; Yan, Xiting ; Bravata, Dawn ; Qin, Li ; Selim, Bernardo J. ; Strohl, Kingman P. ; Redeker, Nancy S. ; Concato, John ; Yaggi, Henry K. / Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea. In: Thorax. 2018 ; Vol. 73, No. 5. pp. 472-480.
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AU - Zinchuk, Andrey V.

AU - Jeon, Sangchoon

AU - Koo, Brian B.

AU - Yan, Xiting

AU - Bravata, Dawn

AU - Qin, Li

AU - Selim, Bernardo J.

AU - Strohl, Kingman P.

AU - Redeker, Nancy S.

AU - Concato, John

AU - Yaggi, Henry K.

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N2 - 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.

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