Observational studyThorax2018
Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea.
Observational study in Thorax, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 132 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
132 citing papers in PubMed, 2 syntheses or guidelines pooled it, 231 citations in OpenAlex.
- Pharmacological responsiveness of periodic limb movements in patients with restless legs syndrome: a systematic review and meta-analysis.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2023Pooled it
- Periodic limb movements during sleep and risk of hypertension: A systematic review.Sleep medicine · 2023Pooled it
- Trial
- Heterogeneous Effects of Continuous Positive Airway Pressure in Non-Sleepy Obstructive Sleep Apnea on Cardiovascular Disease Outcomes:Annals of the American Thoracic Society · 2024Trial
- Physiological Traits and Adherence to Sleep Apnea Therapy in Individuals with Coronary Artery Disease.American journal of respiratory and critical care medicine · 2021Trial
- Sleep architecture, obstructive sleep apnea and functional outcomes in adults with a history of Tick-borne encephalitis.PloS one · 2021Trial
- Perceived Stress, Subjective, and Objective Symptoms of Disturbed Sleep in Men and Women with Stable Heart Failure.Behavioral sleep medicineTrial
- Comparing Demographic and Clinical Features of Obstructive Sleep Apnea Patients With and Without Sleepiness: A Cross-Sectional Study.Brain and behavior · 2026Article
- Long-range interdependencies aware signal analysis for rapid and accurate obstructive sleep apnea prediction.Nature communications · 2026Article
- The Global Initiative for Obstructive Sleep Apnea (GIFOSA): Rationale, Strategic Framework, and Call to Action.Pulmonary therapy · 2026Review
- Article
- Polysomnographic arousal index and periodic limb movement index in patients undergoing coronary artery bypass grafting: an exploratory case-comparison study.Sleep & breathing = Schlaf & Atmung · 2026Article
- A foundation model for sleep-based risk stratification and clinical outcomes.Nature communications · 2026Article
- Physiological phenotypes of obstructive sleep apnea identified by cluster analysis: Association with type 2 diabetes.Journal of diabetes investigation · 2026Article
- Distinguishing Age-specific Patterns in Comorbidities of Obstructive Sleep Apnea Using Real-World Data.medRxiv : the preprint server for health sciences · 2026Article
- Beyond the Apnea-Hypopnea Index: Circulating Biomarkers and Device-Based Metrics for Cardiometabolic Risk Stratification in Obstructive Sleep Apnea.Journal of clinical medicine · 2026Review
- "Phenotyping obstructive sleep apnea: a pathway to precision medicine".Sleep & breathing = Schlaf & Atmung · 2026Review
- Integrating phenotypic information of obstructive sleep apnea and deep representation of sleep-event sequences for cardiovascular risk prediction.BMC medical informatics and decision making · 2026Article
- A perspective on precision medicine in obstructive sleep apnea: from pathophysiological phenotyping to integrated management pathways.Frontiers in medicine · 2026Article
- Incretin-Based Therapies in Obesity-Related Obstructive Sleep Apnea: A Narrative Review of Evidence Tiers and Mechanistic Plausibility.Nature and science of sleep · 2026Review
72 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundObstructive 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.
methodsCross-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.
resultsSeven 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.
conclusionsAmong 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.